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  • 1. About Face 3 The Essentials of Interaction Design Alan Cooper, Robert Reimann, and Dave Cronin
  • 2. About Face 3
  • 3. About Face 3 The Essentials of Interaction Design Alan Cooper, Robert Reimann, and Dave Cronin
  • 4. About Face 3: The Essentials of Interaction Design Published by Wiley Publishing, Inc. 10475 Crosspoint Boulevard Indianapolis, IN 46256 Copyright © 2007 Alan Cooper Published by Wiley Publishing, Inc., Indianapolis, Indiana Published simultaneously in Canada ISBN: 978-0-470-08411-3 Manufactured in the United States of America 10 9 8 7 6 5 4 3 2 1 No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sec- tions 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Pub- lisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600. Requests to the Publisher for permis- sion should be addressed to the Legal Department, Wiley Publishing, Inc., 10475 Crosspoint Blvd., Indianapolis, IN 46256, (317) 572-3447, fax (317) 572-4355, or online at Limit of Liability/Disclaimer of Warranty: The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation warranties of fitness for a particular purpose. No warranty may be created or extended by sales or promotional materials. The advice and strategies contained herein may not be suitable for every situation. This work is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional services. If professional assistance is required, the services of a competent pro- fessional person should be sought. Neither the publisher nor the author shall be liable for damages arising here- from. The fact that an organization or Website is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Website may provide or recommendations it may make. Further, readers should be aware that Internet Websites listed in this work may have changed or disappeared between when this work was written and when it is read. For general information on our other products and services or to obtain technical support, please contact our Cus- tomer Care Department within the U.S. at (800) 762-2974, outside the U.S. at (317) 572-3993 or fax (317) 572-4002. Library of Congress Cataloging-in-Publication Data: Cooper, Alan, 1952- About face 3 : the essentials of interaction design / Alan Cooper, Robert Reimann, and Dave Cronin. p. cm. Includes bibliographical references. ISBN 978-0-470-08411-3 (pbk.) 1. User interfaces (Computer systems) 2. Human-computer interaction. I. Reimann, Robert. II. Cronin, Dave, 1972- III. Title. IV. Title: About face three. QA76.9.U83C6596 2007 005.4’38--dc22 2007004977 Trademarks: Wiley, the Wiley logo, and related trade dress are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates, in the United States and other countries, and may not be used without written per- mission. All other trademarks are the property of their respective owners. Wiley Publishing, Inc., is not associated with any product or vendor mentioned in this book. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books.
  • 5. For Sue, my best friend through all the adventures of life. For Maxwell Aaron Reimann. For Gretchen. And for Cooperistas past, present, and future; and for those visionary IxD practitioners who have helped create a new design profession.
  • 6. About the Authors Alan Cooper is a pioneering software inventor, programmer, designer, and theorist. He is credited with having produced “probably the first serious business software for microcomputers” and is well known as the “Father of Visual Basic.” For the last 15 years his software design consulting company, Cooper, has helped many compa- nies invent new products and improve the behavior of their technology. At Cooper, Alan led the development of a new methodology for creating successful software that he calls the Goal-Directed process. Part of that effort was the invention of per- sonas, a practice that has been widely adopted since he first published the technique in his second book, The Inmates are Running the Asylum, in 1998. Cooper is also a well known writer, speaker, and enthusiast for humanizing technology. Robert Reimann has spent the past 15 years pushing the boundaries of digital products as a designer, writer, lecturer, and consultant. He has led dozens of inter- action design projects in domains including e-commerce, portals, desktop produc- tivity, authoring environments, medical and scientific instrumentation, wireless, and handheld devices for startups and Fortune 500 clients alike. As director of design R&D at Cooper, Reimann led the development and refinement of many of the Goal-Directed Design methods described in About Face. In 2005, Reimann became the first President of IxDA, the Interaction Design Association (, a global nonprofit professional organization for Interaction Designers. He is currently manager of user experience at Bose Corporation. Dave Cronin is the director of interaction design at Cooper, where he’s helped design products to serve the needs of people such as surgeons, museum visitors, marketers, investment portfolio managers, online shoppers, hospital staff, car dri- vers, dentists, financial analysts, manufacturing planners, the elderly, and the infirm. At Cooper, he has also contributed substantially to the ongoing process of developing and refining the Goal-Directed Design methods described in this book.
  • 7. Credits Executive Editor Graphics and Production Specialists Chris Webb Sean Decker, Brooke Graczyk, Stephanie D. Jumper, Development Editors Jennifer Mayberry, Barbara Moore, Sara Shlaer Ronald Terry Sydney Jones Quality Control Technician Production Editor Christy Pingleton Eric Charbonneau Book Designers Copy Editor Rebecca Bortman and Nick Myers Foxxe Editorial Services Illustrators Editorial Manager Rebecca Bortman and Nick Myers Mary Beth Wakefield Proofreading and Indexing Production Manager Aptara Tim Tate Anniversary Logo Design Vice President and Executive Group Richard Pacifico Publisher Richard Swadley Cover Design Rebecca Bortman and Nick Myers Vice President and Executive Publisher Joseph B. Wikert Project Coordinator Erin Smith
  • 8. Contents About the Authors vi Foreword: The Postindustrial World xxi Acknowledgments xxv Introduction to the Third Edition xxvii Part I Understanding Goal-Directed Design 1 Chapter 1 Goal-Directed Design 3 Digital Products Need Better Design Methods 3 The creation of digital products today 4 Why are these products so bad? 8 The Evolution of Design in Manufacturing 11 Planning and Designing Behavior 13 Recognizing User Goals 13 Goals versus tasks and activities 15 Designing to meet goals in context 16 The Goal-Directed Design Process 17 Bridging the gap 18 A process overview 20 Goals, not features, are the key to product success 25 Chapter 2 Implementation Models and Mental Models 27 Implementation Models 27 User Mental Models 28 Represented Models 29 Most Software Conforms to Implementation Models 32 User interfaces designed by engineers follow the implementation model 32 Mathematical thinking leads to implementation model interfaces 34 Mechanical-Age versus Information-Age Represented Models 35 Mechanical-Age representations 35 New technology demands new representations 36 Mechanical-Age representations degrade user interaction 36 Improving on Mechanical-Age representations: An example 37
  • 9. x Contents Chapter 3 Beginners, Experts, and Intermediates 41 Perpetual Intermediates 42 Designing for Different Experience Levels 44 What beginners need 45 Getting beginners on board 46 What experts need 47 What perpetual intermediates need 47 Chapter 4 Understanding Users: Qualitative Research 49 Qualitative versus Quantitative Research 50 The value of qualitative research 50 Types of qualitative research 52 Ethnographic Interviews: Interviewing and Observing Users 58 Contextual inquiry 58 Improving on contextual inquiry 59 Preparing for ethnographic interviews 59 Conducting ethnographic interviews 63 Other Types of Research 68 Focus groups 69 Market demographics and market segments 69 Usability and user testing 70 Card sorting 72 Task analysis 72 Chapter 5 Modeling Users: Personas and Goals 75 Why Model? 76 Personas 77 Strengths of personas as a design tool 78 Personas are based on research 80 Personas are represented as individual people 81 Personas represent groups of users 82 Personas explore ranges of behavior 83 Personas must have motivations 83 Personas can also represent nonusers 84 Personas and other user models 84 When rigorous personas aren’t possible: Provisional personas 86 Goals 88 Goals motivate usage patterns 88 Goals should be inferred from qualitative data 88 User goals and cognitive processing 89 The three types of user goals 92 User goals are user motivations 94 Types of goals 94 Successful products meet user goals first 96 Constructing Personas 97 Step 1: Identify behavioral variables 98 Step 2: Map interview subjects to behavioral variables 99 Step 3: Identify significant behavior patterns 99
  • 10. Contents xi Step 4: Synthesize characteristics and relevant goals 100 Step 5: Check for completeness and redundancy 101 Step 6: Expand description of attributes and behaviors 102 Step 7: Designate persona types 104 Other Models 106 Workflow models 106 Artifact models 107 Physical models 107 Chapter 6 The Foundations of Design: Scenarios and Requirements 109 Scenarios: Narrative as a Design Tool 110 Scenarios in design 111 Using personas in scenarios 112 Different types of scenarios 112 Persona-based scenarios versus use cases 113 Requirements: The “What” of Interaction Design 114 Requirements Definition Using Personas and Scenarios 115 Step 1: Creating problem and vision statements 116 Step 2: Brainstorming 117 Step 3: Identifying persona expectations 118 Step 4: Constructing context scenarios 119 Step 5: Identifying requirements 122 Chapter 7 From Requirements to Design: The Framework and Refinement 125 The Design Framework 125 Defining the interaction framework 127 Defining the visual design framework 136 Defining the industrial design framework 139 Refining the Form and Behavior 141 Design Validation and Usability Testing 142 When to test: Summative and formative evaluations 144 Conducting formative usability tests 144 Designer involvement in usability studies 145 Part II Designing Behavior and Form 147 Chapter 8 Synthesizing Good Design: Principles and Patterns 149 Interaction Design Principles 150 Principles operate at different levels of detail 150 Behavioral and interface-level principles minimize work 151 Design Values 151 Ethical interaction design 152 Purposeful interaction design 153 Pragmatic interaction design 154 Elegant interaction design 154 Interaction Design Patterns 156 Architectural patterns and interaction design 156 Recording and using interaction design patterns 157 Types of interaction design patterns 158
  • 11. xii Contents Chapter 9 Platform and Posture 161 Posture 162 Designing Desktop Software 163 Designing for the Web 174 Informational Web sites 175 Transactional Web sites 177 Web applications 178 Internet-enabled applications 181 Intranets 181 Other Platforms 182 General design principles 182 Designing for handhelds 189 Designing for kiosks 191 Designing for television-based interfaces 195 Designing for automotive interfaces 197 Designing for appliances 198 Designing for audible interfaces 199 Chapter 10 Orchestration and Flow 201 Flow and Transparency 201 Designing Harmonious Interactions 203 Chapter 11 Eliminating Excise 223 GUI Excise 224 Excise and expert users 225 Training wheels 225 “Pure” excise 226 Visual excise 226 Determining what is excise 228 Stopping the Proceedings 228 Errors, notifiers, and confirmation messages 228 Making users ask permission 230 Common Excise Traps 231 Navigation Is Excise 232 Navigation among multiple screens, views, or pages 233 Navigation between panes 233 Navigation between tools and menus 235 Navigation of information 236 Improving Navigation 237 Reduce the number of places to go 238 Provide signposts 238 Provide overviews 241 Provide appropriate mapping of controls to functions 242 Inflect your interface to match user needs 245 Avoid hierarchies 247
  • 12. Contents xiii Chapter 12 Designing Good Behavior 249 Designing Considerate Products 250 Considerate products take an interest 251 Considerate products are deferential 252 Considerate products are forthcoming 252 Considerate products use common sense 253 Considerate products anticipate human needs 253 Considerate products are conscientious 253 Considerate products don’t burden you with their personal problems 254 Considerate products keep us informed 255 Considerate products are perceptive 255 Considerate products are self-confident 256 Considerate products don’t ask a lot of questions 256 Considerate products fail gracefully 256 Considerate products know when to bend the rules 257 Considerate products take responsibility 259 Designing Smart Products 260 Putting the idle cycles to work 260 Smart products have a memory 261 Task coherence 263 Actions to remember 265 Applying memory to your applications 266 Chapter 13 Metaphors, Idioms, and Affordances 269 Interface Paradigms 270 Implementation-centric interfaces 270 Metaphoric interfaces 271 Idiomatic interfaces 273 Further Limitations of Metaphors 276 Finding good metaphors 276 The problems with global metaphors 276 Macs and metaphors: A revisionist view 279 Building Idioms 280 Manual Affordances 282 Semantics of manual affordances 284 Fulfilling user expectations of affordances 284 Chapter 14 Visual Interface Design 287 Art, Visual Interface Design, and Other Design Disciplines 288 Graphic design and user interfaces 289 Visual information design 289 Industrial design 290 The Building Blocks of Visual Interface Design 290 Shape 291 Size 291 Value 291 Hue 292
  • 13. xiv Contents Orientation 292 Texture 292 Position 293 Principles of Visual Interface Design 293 Use visual properties to group elements and provide clear hierarchy 294 Provide visual structure and flow at each level of organization 296 Use cohesive, consistent, and contextually appropriate imagery 302 Integrate style and function comprehensively and purposefully 306 Avoid visual noise and clutter 307 Keep it simple 308 Text in visual interfaces 310 Color in visual interfaces 311 Visual interface design for handhelds and other devices 312 Principles of Visual Information Design 313 Enforce visual comparisons 314 Show causality 314 Show multiple variables 314 Integrate text, graphics, and data in one display 315 Ensure the quality, relevance, and integrity of the content 315 Show things adjacently in space, not stacked in time 316 Don’t de-quantify quantifiable data 317 Consistency and Standards 317 Benefits of interface standards 317 Risks of interface standards 318 Standards, guidelines, and rules of thumb 318 When to violate guidelines 319 Consistency and standards across applications 319 Part III Designing Interaction Details 321 Chapter 15 Searching and Finding: Improving Data Retrieval 323 Storage and Retrieval Systems 324 Storage and Retrieval in the Physical World 324 Everything in its place: Storage and retrieval by location 324 Indexed retrieval 325 Storage and Retrieval in the Digital World 326 Relational Databases versus Digital Soup 330 Organizing the unorganizable 330 Problems with databases 331 The attribute-based alternative 332 Natural Language Output: An Ideal Interface for Attribute-Based Retrieval 333 Chapter 16 Understanding Undo 335 Users and Undo 335 User mental models of mistakes 336 Undo enables exploration 336 Designing an Undo Facility 337
  • 14. Contents xv Types and Variants of Undo 338 Incremental and procedural actions 338 Blind and explanatory Undo 339 Single and multiple Undo 339 Redo 341 Group multiple Undo 342 Other Models for Undo-Like Behavior 343 Comparison: What would this look like? 343 Category-specific Undo 344 Deleted data buffers 346 Versioning and reversion 346 Freezing 348 Undo-Proof Operations 348 Chapter 17 Rethinking Files and Save 349 What’s Wrong with Saving Changes to Files? 350 Problems with the Implementation Model 352 Closing documents and removing unwanted changes 352 Save As 353 Archiving 355 Implementation Model versus Mental Model 355 Dispensing with the Implementation Model 356 Designing with a Unified File Model 357 Automatically saving 358 Creating a copy 359 Naming and renaming 359 Placing and moving 360 Specifying the stored format 360 Reversing changes 361 Abandoning all changes 361 Creating a version 361 A new File menu 362 A new name for the File menu 363 Communicating status 363 Are Disks and File Systems a Feature? 364 Time for Change 365 Chapter 18 Improving Data Entry 367 Data Integrity versus Data Immunity 367 Data immunity 368 What about missing data? 369 Data entry and fudgeability 371 Auditing versus Editing 371 Chapter 19 Pointing, Selecting, and Direct Manipulation 375 Direct Manipulation 375 Pointing Devices 377 Using the mouse 378 Mouse buttons 380
  • 15. xvi Contents Pointing and clicking with a mouse 382 Mouse-up and mouse-down events 385 Pointing and the Cursor 386 Pliancy and hinting 386 Selection 390 Command ordering and selection 390 Discrete and contiguous selection 392 Insertion and replacement 395 Visual indication of selection 396 Drag-and-Drop 397 Visual feedback for drag-and-drop 399 Other drag-and-drop interaction issues 402 Control Manipulation 408 Palette Tools 409 Modal tools 409 Charged cursor tools 410 Object Manipulation 411 Repositioning 411 Resizing and reshaping 413 3D object manipulation 415 Object Connection 420 Chapter 20 Window Behaviors 423 PARC and the Alto 423 PARC’s Principles 425 Visual metaphors 425 Avoiding modes 425 Overlapping windows 426 Microsoft and Tiled Windows 427 Full-Screen Applications 427 Multipaned Applications 428 Designing with Windows 430 Unnecessary rooms 430 Necessary rooms 433 Windows pollution 434 Window States 436 MDI versus SDI 437 Chapter 21 Controls 439 Avoiding Control-Laden Dialog Boxes 439 Imperative Controls 440 Buttons 440 Butcons 441 Hyperlinks 442 Selection Controls 443 Check boxes 443 Flip-flop buttons: A selection idiom to avoid 445 Radio buttons 446
  • 16. Contents xvii Combutcons 447 List controls 449 Combo boxes 455 Tree controls 457 Entry Controls 457 Bounded and unbounded entry controls 457 Spinners 459 Dials and Sliders 460 Thumbwheels 462 Other bounded entry controls 462 Unbounded entry: Text edit controls 463 Display Controls 468 Text controls 468 Scrollbars 469 Splitters 471 Drawers and levers 472 Chapter 22 Menus 473 A Bit of History 473 The command-line interface 474 Sequential hierarchical menus 474 The Lotus 1-2-3 interface 476 Drop-down and pop-up menus 478 Menus Today: The Pedagogic Vector 479 Standard menus for desktop applications 481 File (or document) 482 Edit 482 Windows 483 Help 483 Optional Menus 484 View 484 Insert 484 Settings 484 Format 484 Tools 485 Menu Idioms 485 Cascading menus 485 Menus 486 The ribbon 487 Bang menus 488 Disabled menu items 489 Checkmark menu items 489 Icons on menus 490 Accelerators 490 Access keys 491 Menus on other platforms 492
  • 17. xviii Contents Chapter 23 Toolbars 493 Toolbars: Visible, Immediate Commands 493 Toolbars versus Menus 494 Toolbars and Toolbar Controls 495 Icons versus text on toolbars 495 The problem with labeling butcons 496 Explaining Toolbar Controls 496 Balloon help: A first attempt 497 ToolTips 497 Disabling toolbar controls 498 Evolution of the Toolbar 499 State-indicating toolbar controls 499 Menus on toolbars 499 Movable toolbars 500 Customizable toolbars 501 The ribbon 502 Contextual toolbars 503 Chapter 24 Dialogs 505 Appropriate Uses for Dialog Boxes 505 Dialog Box Basics 507 Modal Dialog Boxes 509 Modeless Dialog Boxes 509 Modeless dialog issues 510 Two solutions for better modeless dialogs 510 Four Different Purposes for Dialogs 516 Property dialog boxes 516 Function dialog boxes 517 Process dialog boxes 518 Eliminating process dialogs 520 Bulletin dialog boxes 522 Managing Content in Dialog Boxes 523 Tabbed dialogs 523 Expanding dialogs 526 Cascading dialogs 527 Chapter 25 Errors, Alerts, and Confirmation 529 Error Dialogs 529 Why we have so many error messages 530 What’s wrong with error messages 530 Eliminating error messages 534 Aren’t there exceptions? 536 Improving error messages: The last resort 537 Alert Dialogs: Announcing the Obvious 539 Confirmation Dialog 541 The dialog that cried “Wolf!” 542 Eliminating confirmations 543
  • 18. Contents xix Replacing Dialogs: Rich Modeless Feedback 544 Rich visual modeless feedback 545 Audible feedback 547 Chapter 26 Designing for Different Needs 551 Command Vectors and Working Sets 551 Immediate and pedagogic vectors 552 Working sets and personas 552 Graduating Users from Beginners to Intermediates 553 World vectors and head vectors 553 Memorization vectors 554 Personalization and Configuration 555 Idiosyncratically Modal Behavior 557 Localization and Globalization 558 Galleries and Templates 559 Help 560 The index 560 Shortcuts and overview 561 Not for beginners 561 Modeless and interactive help 561 Wizards 561 “Intelligent” agents 562 Afterword: On Collaboration 565 Appendix A Design Principles 569 Appendix B Bibliography 575 Index 581
  • 19. Foreword: The Postindustrial World The industrial age is over. Manufacturing, the primary economic driver of the past 175 years, no longer dominates. While manufacturing is bigger than ever, it has lost its leadership to digital technology, and software now dominates our economy. We have moved from atoms to bits. We are now in the postindustrial age. More and more products have software in them. My stove has a microchip in it to manage the lights, fan, and oven temperature. When the deliveryman has me sign for a package, it’s on a computer, not a pad of paper. When I shop for a car, I am really shopping for a navigation system. More and more businesses are utterly dependent on software, and not just the obvi- ous ones like and Microsoft. Thousands of companies of all sizes that provide products and services across the spectrum of commerce use software in every facet of their operations, management, planning, and sales. The back-office systems that run big companies are all software systems. Hiring and human resource management, investment and arbitrage, purchasing and supply chain management, point-of-sale, operations, and decision support are all pure software systems these days. And the Web dominates all sales and marketing. Live humans are no longer the front line of businesses. Software plays that role instead. Vendors, customers, colleagues, and employees all communicate with companies via soft- ware or software-mediated paths. The organizational structures and management techniques that have worked so well in the past for manufacturing-based companies are failing us today in the postindustrial age. They fail because they focus on the transformation and move- ment of things made out of atoms. There are only finite amounts of desirable atoms and it takes lots of energy to transform and transport them. Software—made out of bits, not atoms—is qualitatively different. There is an infinite quantity of bits and virtually no energy is needed to transform, transport, or even replicate them.
  • 20. xxii Foreword: The Postindustrial World The people who make software are different as well. The average computer pro- grammer and the average assembly line worker are qualitatively different in their aptitude, attitude, training, language, tools, and value systems. The most effective ways of supervising, tracking, and managing programmers are dramatically differ- ent from those used so successfully with blue-collar workers of an earlier age. Get- ting programmers to do what is best for the company requires skills unknown to the industrial-age executive. Reducing the cost of manufacturing was the essential contribution of industrializa- tion. Thus the best and brightest minds of an earlier age applied themselves to reducing the amount of money spent creating products. In the postindustrial age, the costs of raw materials, product assembly, and shipping are equally low for all players. The only significant leverage to lower manufacturing costs comes through automation, planning, and business intelligence: that is, software. In other words, instead of saving a dollar on the construction of each widget, you save a million dollars by making the precisely needed quantity of the most desirable product. Once a software program has been successfully written, it can be reproduced an unlimited number of times for virtually nothing. There is little benefit in reducing the cost of writing it. Reducing the amount one spends on software construction usually means compromising the quality, so the primary business equation of the industrial age is reversed today. The best and brightest minds of today apply them- selves to increasing the effectiveness of software and the quality of its behavior. Keep in mind that all modern financial accounting systems focus on tracking man- ufacturing costs and no longer accurately represent the state of our software-dom- inated businesses. Making executive decisions on these erroneous numbers causes significant waste of time, money, and opportunity. It’s no wonder that companies struggle with software. Very capable executives find that their intentions are subtly but significantly altered somewhere along the path from conception to release. What appeared to be a sound plan turns out to be inad- equate for shepherding the software construction process. It’s time to let go of obsolete industrial-age management methods and adopt interaction design as the primary tool for designing and managing software construction. Since About Face was first published in 1995, the practice of interaction design has grown and matured enormously. Dominated for so long by simple ex post facto, trial-and-error methods, interaction design—along with its many siblings and variants—has matured into a clear, dependable, effective tool for determining what behavior will succeed. The invention and development of personas, the refinement of written behavioral blueprints, and the entire practice of Goal-Directed™ Design, have made high-quality software behavior achievable by any organization with the will to create it.
  • 21. Foreword: The Postindustrial World xxiii What’s more, interaction design has emerged as an incredibly powerful software construction management tool. Because it is a description of the software as it will be when it is finally written, it acts as a blueprint, not only helping program- mers know what to build but also helping managers measure the progress of the programmers. Interaction design has also shown its power as a marketing tool, communicating with great clarity and specificity about exactly whom will be using the product and why. Getting to the root of customer motivations is manna for marketers, and the qualitative research and analysis aspects of Goal-Directed Design provide signifi- cant market insight. Especially since the Web revolution—when tossing common sense overboard seemed to be the path to instant riches—I’ve heard many intelligent people who really should know better say, “It is simply not possible to know what the user wants!” While this assertion certainly absolves them of not, in fact, knowing what the user wants, it is boldly, obviously, incredibly false. At my company, Cooper, clients bring our designers into the complex worlds of finance, health care, phar- maceuticals, human resources, programming tools, museums, consumer credit, and any number of disparate fields. Our teams, none of whom have any training in—or typically even any exposure to—the particular subject matter at hand, rou- tinely become sufficiently expert in only a few weeks to astonish our clients. We can do this because our point of departure is relentlessly human-centered, rather than technology-centered. Interaction design is a tool for “Knowing what the user wants.” Armed with that knowledge, you can create better, more successful, bit-empowered products, and you can sell them for more money. What’s more, you will reach your market with a loyalty-inducing, better solution. Time and time again we have seen feature-loaded products early to market get trounced by later entries whose behavior has been bet- ter thought out. Imagine getting that thinking done before the first release ever has a chance to commit you to a nonoptimal strategy. Nothing succeeds like success, and the success of the practical application of the principles and methods put forth in this book—and others like it—are clearly demonstrating that software isn’t really as soft as many people first thought, and that thorough user research and detailed planning are more necessary than ever in the postindustrial age. If you are committed to improving the world by improving the behavior of digital products and services, then I welcome you to the world of About Face. —Alan Cooper
  • 22. Acknowledgments We’d like to express our deepest gratitude to the following individuals, without whom this new edition of About Face would not have been possible: Chris Webb at Wiley, who saw the time was right for a new edition; Sue Cooper, who shared that vision; and Sara Shlaer at Wiley, who has patiently helped us shape multiple edi- tions of this book. We would also like to thank the following colleagues and Cooper designers for their contributions to this volume and the previous, for which we are greatly indebted: Kim Goodwin, who has contributed significantly to the development and expres- sion of the concepts and methods described in these pages; Rebecca Bortman and Nick Myers who overhauled the book and cover designs, as well as the illustrations; Hugh Dubberly, for his help in developing the principles at the end of Chapter 8 and for his assistance in clarifying the Goal-Directed process with early versions of the diagrams found in Chapter 1; Gretchen Anderson, Elaine Montgomery, and Doug LeMoine for their contributions on user and market research in Chapter 4; Rick Bond for his many insights about usability testing featured in Chapter 7; Ernest Kinsolving and Joerg Beringer at SAP for their contributions on the posture of Web portals in Chapter 9; Chris Weeldreyer for his insights into the design of embedded systems in Chapter 9; Wayne Greenwood for his contributions on con- trol mapping in Chapter 10; and Nate Fortin and Nick Myers for their contribu- tions on visual interface design and branding in Chapter 14. We would also like to thank Elizabeth Bacon, Steve Calde, John Dunning, David Fore, Nate Fortin, Kim Goodwin, Wayne Greenwood, Noah Guyot, Lane Halley, Ernest Kinsolving, Daniel Kuo, Berm Lee, Doug LeMoine, Tim McCoy, Elaine Montgomery, Nick Myers, Chris Noessel, Ryan Olshavsky, Angela Quail, Suzy Thompson, and Chris Weeldreyer for their contributions to the Cooper designs and illustrations featured in this volume. We are grateful to clients David West at Shared Healthcare Systems, Mike Kay and Bill Chang at Fujitsu Softek, John Chaffins at CrossCountry, Chris Twogood at Teradata, and Chris Dollar at McKesson for granting us permission to use examples
  • 23. xxvi Acknowledgments from the Cooper design projects featured in this book. We wish also to thank the many other clients who have had the vision and the foresight to work with us and support us in their organizations. We would also like to acknowledge the following authors and industry colleagues who have influenced or clarified our thinking over the years: Christopher Alexander, Edward Tufte, Kevin Mullet, Victor Papanek, Donald Norman, Larry Constantine, Challis Hodge, Shelley Evenson, Clifford Nass, Byron Reeves, Stephen Pinker, and Terry Swack. Finally, it should be noted that the parts of Chapter 5 concerned with cognitive pro- cessing originally appeared in an article by Robert Reimann on, and are used with permission.
  • 24. Introduction to the Third Edition This book is about interaction design—the practice of designing interactive digi- tal products, environments, systems, and services. Like many design disciplines, interaction design is concerned with form. However, first and foremost, interaction design focuses on something that traditional design disciplines do not often explore: the design of behavior. Most design affects human behavior: Architecture is concerned with how people use physical space, and graphic design often attempts to motivate or facilitate a response. But now, with the ubiquity of silicon-enabled products—from computers to cars and phones—we routinely create products that exhibit complex behavior. Take something as basic as an oven. Before the digital age, the operation of an oven was quite simple—it involved turning a single knob to the correct position. There was one position for off, and one position for any oven temperature one might want to use. Every single time a person turned that knob to a given position, the same thing happened. One might call this “behavior,” but it is certainly quite simple and mechanistic behavior. Compare this to our modern-day ovens with silicon chips and LCD screens. They are endowed with buttons that say non-cooking- related things like Start, Cancel, Program, as well as the more expected Bake and Broil. What happens when you press any one of these buttons is quite a lot less pre- dictable than what happened when you turned the knob on your old gas range. In fact, the results of pressing one of the buttons is entirely dependent on the state of the oven and what other buttons you might have pressed previously. This is what we mean by complex behavior. This emergence of products with complex behavior has given rise to a new disci- pline. Interaction design borrows theory and technique from traditional design, usability, and engineering disciplines. But it is greater than a sum of its parts, with its own unique methods and practices. And to be clear—it is very much a design
  • 25. xxviii Introduction to the Third Edition discipline, quite different from science and engineering. While it should always be practiced in a rational and considered manner, interaction design is about synthe- sis and imagining things as they might be, not necessarily as they currently are. Interaction design is also an inherently humanistic enterprise. It is concerned most significantly with satisfying the needs and desires of the people who will interact with a product or service. In this book we describe a particular approach to inter- action design that we call the Goal-Directed method. We’ve found that when a designer focuses on people’s goals—the reasons why they use a product in the first place—as well as their expectations, attitudes, and aptitudes, they can devise solu- tions that people find powerful and pleasurable. As even the most casual observer of developments in technology must have noticed, interactive products can become very complex very quickly. While a mechanical device may be capable of a dozen visible states, a digital product may be capable of being in thousands of different states (if not more!). This complexity can be a nightmare for users and designers alike. To tame this complexity, we rely on a very systematic and rational approach. This doesn’t mean that we don’t also value and encourage inventiveness and creativity. On the contrary, we find that a methodical approach helps us clearly identify opportunities for revolutionary thinking, and provides a way of assessing the effectiveness of our ideas. According to Gestalt Theory, people perceive a thing not as a set of individual fea- tures and attributes but as a unified whole in a relationship with its surroundings. As a result, it isn’t possible to effectively design an interactive product by decom- posing it into a list of atomic requirements and coming up with a design solution for each. Even a relatively simple product must be considered in totality and in light of its context in the world. Again, we’ve found that a methodical approach helps provide the holistic perspective necessary to create products that people find useful and engaging. A Brief History of Interaction Design In the late 1970s and early 1980s a dedicated and visionary set of researchers, engi- neers, and designers in the San Francisco Bay Area were busy inventing how people would interact with computers in the future. At Xerox Parc, SRI, and eventually Apple Computer, people had begun discussing what it meant to create useful and usable “human interfaces” to digital products. In the mid-1980s, two industrial designers, Bill Moggridge and Bill Verplank, who were working on the first laptop computer, the GRiD Compass, coined the term interaction design for what they were doing, but it would be another 10 years before other designers rediscovered this term and brought it into mainstream use.
  • 26. Introduction to the Third Edition xxix At the time About Face was first published in August 1995, the landscape of interaction design was still a frontier wilderness. A small cadre of people brave enough to hold the title user interface designer operated under the shadow of software engineering, rather like the tiny, quick-witted mammals that scrambled under the shadows of hulking tyrannosaurs. “Software design,” as the first edition of About Face referred to it, was poorly understood and underappreciated, and, when it was practiced at all, it was usu- ally practiced by programmers. A handful of uneasy technical writers, trainers, and product support people, along with a rising number of practitioners from another nascent field—usability—realized that something needed to change. The amazing growth and popularity of the Web drove that change, seemingly overnight. Suddenly, “ease of use” was a term on everyone’s lips. Traditional design professionals, who had dabbled in digital product design during the short-lived popularity of “multimedia” in the early nineties, leapt to the Web en masse. Seem- ingly new design titles sprang up like weeds: information designer, information architect, user experience strategist, and interaction designer. For the first time ever, C-level executive positions were established to focus on creating user-centered products and services, such as the chief experience officer. Universities scrambled to offer programs to train designers in these disciplines. Meanwhile, usability and human factors practitioners also rose in stature and are now recognized as advo- cates for better-designed products. Although the Web knocked interaction design idioms back by more than a decade, it inarguably placed user requirements on the radar of the corporate world for good. Since the second edition of About Face was published in 2003, the user expe- rience of digital products has become front page news in the likes of Time magazine and BusinessWeek, and institutions such as Harvard Business School and Stanford have recognized the need to train the next generation of MBAs and technologists to incorporate design thinking into their business and development plans. People are tired of new technology for its own sake. Consumers are sending a clear message that what they want is good technology: technology that has been designed to pro- vide a compelling and effective user experience. In August 2003, five months after the second edition of About Face proclaimed the existence of a new design discipline called interaction design, Bruce “Tog” Tognazz- ini made an impassioned plea to the nascent community to create a nonprofit pro- fessional organization, and a mailing list and steering committee were founded shortly thereafter by Challis Hodge, David Heller, Rick Cecil, and Jim Jarrett. In September of 2005, IxDA, the Interaction Design Association ( was officially incorporated. At the time of writing, it has over 2000 members in over 20 countries. We’re pleased to say that Interaction Design is finally beginning to come into its own as both a discipline and a profession.
  • 27. xxx Introduction to the Third Edition Why Call It Interaction Design? The first edition of About Face described a discipline called software design and equated it with another discipline called user interface design. Of these two terms, user interface design has certainly had better longevity. We still use it occasionally in this book, specifically to connote the arrangement of widgets on the screen. How- ever, what is discussed in this book is a discipline broader than the design of user interfaces. In the world of digital technology, form, function, content, and behavior are so inextricably linked that many of the challenges of designing an interactive product go right to the heart of what a digital product is and what it does. As we’ve discussed, interaction designers have borrowed practices from more established design disciplines, but have also evolved beyond them. Industrial designers have attempted to address the design of digital products, but like their counterparts in graphic design, their focus has traditionally been on the design of static form, not the design of interactivity, or form that changes and reacts to input over time. These disciplines do not have a language with which to discuss the design of rich, dynamic behavior and changing user interfaces. In recent years, a number of new terms have been proposed for this type of design. As the World Wide Web gained prominence, information architecture (IA) emerged as a discipline dedicated to solving problems dealing with navigation to and the “findability” of content, mostly (though not exclusively) within the context of Web sites. While clearly a close relative of interaction design, mainstream IA still retains a somewhat limited, Web-centric view of organizing and navigating content using pages, links, and minimally interactive widgets. However, recent industry trends such as Web 2.0 and rich Internet applications have begun to open the eyes of Web designers, causing them to look beyond archaic browser interaction idioms. We believe this awakening is bringing information architects’ concerns ever more closely in alignment with those of interaction designers. Another term that has gained popularity is user experience (UX). There are many who advocate for the use of this term as an umbrella under which many different design and usability disciplines collaborate to create products, systems, and ser- vices. This is a laudable goal with great appeal, but it does not in itself directly address the core concern of interaction design as discussed in this volume: how specifically to design the behavior of complex interactive systems. While it’s useful to consider the similarities and synergies between creating a customer experience at a physical store and creating one with an interactive product, we believe there are specific methods appropriate to designing for the world of bits. We also wonder whether it is actually possible to design an experience. Designers of all stripes hope to manage and influence the experiences people have, but this is done
  • 28. Introduction to the Third Edition xxxi by carefully manipulating the variables intrinsic to the medium at hand. A graphic designer creating a poster uses an arrangement of type, photos, and illustrations to help create an experience, a furniture designer working on a chair uses materials and construction techniques to help create an experience, and an interior designer uses layout, lighting, materials, and even sound to help create an experience. Extending this thinking to the world of digital products, we find it useful to think that we influence people’s experiences by designing the mechanisms for interacting with a product. Therefore, we have chosen Moggridge’s term, interaction design (now abbreviated by many in the industry as IxD), to denote the kind of design this book describes. Of course, there are many cases where a design project requires careful attention to the orchestration of a number of design disciplines to achieve an appropriate user experience (see Figure 1). It is to these situations that we feel the term experience design is most applicable. Content Form Information architects Industrial designers Copywriters Graphic designers Animators Sound designers Behavior Interaction designers Figure 1 One can think of user experience design (UX) of digital products as consisting of three overlapping concerns: form, behavior, and content. Interaction design is focused on the design of behavior, but is also concerned with how that behavior relates to form and content. Similarly, information architecture is focused on the structure of content, but is also concerned with behaviors that provide access to content, and the way the content is presented to the user. Industrial design and graphic design are concerned with the form of products and services, but also must ensure that their form supports use, which requires attention to behavior and content.
  • 29. xxxii Introduction to the Third Edition Working with the Product Team In addition to defining interaction design in terms of its primary concern with behavior and its relationships with other design disciplines, we also often find it necessary to define how interaction design should fit within an organization. We believe that establishing a rigorous product development process that incorporates design as an equal partner with engineering, marketing, and business management, and that includes well-defined responsibilities and authority for each group, greatly increases the value a business can reap from design. The following division of responsibilities, balanced by an equal division of authority, can dramatically improve design success and organizational support of the product throughout the development cycle and beyond: The design team has responsibility for users’ satisfaction with the product. Many organizations do not currently hold anyone responsible for this. To carry out this responsibility, designers must have the authority to decide how the product will look, feel, and behave. They also need access to information: They must observe and speak to potential users about their needs, to engineers about technologi- cal opportunities and constraints, to marketing about opportunities and require- ments, and to management about the kind of product to which the organization will commit. The engineering team has responsibility for the implementation and fabrication of the product. For the design to deliver its benefit, engineering must have the responsibility for building, as specified, the form and behaviors that the designers define, while keeping on budget and on schedule. Engineers, therefore, require a clear description of the product’s form and behaviors, which will guide what they build and drive their time and cost estimates. This description must come from the design team. Engineers must also contribute to discussions of technical con- straints and opportunities, as well as the feasibility of proposed design solutions. The marketing team has responsibility for convincing customers to purchase the product, so they must have authority over all communications with the customer, as well as input into the product definition and design. In order to do this, the team members need access to information, including the results of designers’ research, as well as research of their own. (It’s worth noting that, as we discuss further in Chapters 4 and 5, customers and users are often different people with different needs.) Management has responsibility for the profitability of the resulting product, and therefore has the authority to make decisions about what the other groups will work on. To make those decisions, management needs to receive clear informa- tion from the other groups: design’s research and product definition, marketing’s research and sales projections, and engineering’s estimations of the time and cost to create the product.
  • 30. Introduction to the Third Edition xxxiii What This Book Is and What It Is Not In this book, we attempt to provide readers with effective and practical tools for interaction design. These tools consist of principles, patterns, and processes. Design principles encompass broad ideas about the practice of design, as well as rules and hints about how to best use specific user interface and interaction design idioms. Design patterns describe sets of interaction design idioms that are common ways to address specific user requirements and design concerns. Design processes describe how to go about understanding and defining user requirements, how to then trans- late those requirements into the framework of a design, and finally how to best apply design principles and patterns to specific contexts. Although books are available that discuss design principles and design patterns, few books discuss design processes, and even fewer discuss all three of these tools and how they work together to create effective designs. Our goal with this volume has been to create a book that weaves all three of these three tools together. While help- ing you design more effective and useful dialog boxes and menus, this book will simultaneously help you understand how users comprehend and interact with your digital product, and understand how to use this knowledge to drive your design. Integrating design principles, processes, and patterns is the key to designing effec- tive product interactions and interfaces. There is no such thing as an objectively good user interface—quality depends on the context: who the user is, what she is doing, and what her motivations are. Applying a set of one-size-fits-all principles makes user interface creation easier, but it doesn’t necessarily make the end result better. If you want to create good design solutions, there is no avoiding the hard work of really understanding the people who will actually interact with your prod- uct. Only then is it useful to have at your command a toolbox of principles and pat- terns to apply in specific situations. We hope this book will both encourage you to deepen your understanding of your product’s users, and teach you how to translate that understanding into superior product designs. This book does not attempt to present a style guide or set of interface standards. In fact, you’ll learn in Chapter 14 why the utility of such tools is limited and relevant only to specific circumstances. That said, we hope that the process and principles described in this book are compatible companions to the style guide of your choice. Style guides are good at answering what, but generally weak at answering why. This book attempts to address these unanswered questions. We discuss four main steps to designing interactive systems in this book: research- ing the domain, understanding the users and their requirements, defining the framework of a solution, and filling in the design details. Many practitioners would
  • 31. xxxiv Introduction to the Third Edition add a fifth step: validation, testing the effectiveness of a solution with users. This is part of a discipline widely known as usability. While this is an important and worthwhile component to many interaction design initiatives, it is a discipline and practice in its own right. We briefly discuss design validation and usability testing in Chapter 7, but urge you to refer to the significant and ever-growing body of usability literature for more detailed information about conducting and analyzing usability tests. Changes from the Previous Editions Much in the world of interface design has changed since the first edition of About Face was published in 1995. However, much remains the same. The third edition of About Face retains what still holds true, updates those things that have changed, and provides new material reflecting not only how the industry has changed in the last 11 years but also new concepts that we have developed in our practice to address the changing times. Here are some highlights of the major changes you will find in the third edition of About Face: The book has been reorganized to present its ideas in a more easy-to-use refer- ence structure. The book is divided into three parts: The first deals with process and high-level ideas about users and design, the second deals with high-level interaction design principles, and the third deals with lower-level interface design principles. The first part describes the Goal-Directed Design process in much greater detail than in the second edition, and more accurately reflects current practices at Cooper, including research techniques, the creation of personas, and how to use personas and scenarios to synthesize interaction design solutions. Throughout the book, we attempt to more explicitly discuss visual interface design concepts, methods and issues, as well as issues related to a number of platforms beyond the desktop. Terminology and examples in the book have been updated to reflect the current state of the art in the industry, and the text as a whole has been thoroughly edited to improve clarity and readability. We hope that readers will find these additions and changes provide a fresh look at the topics at hand.
  • 32. Introduction to the Third Edition xxxv Examples Used in This Book This book is about designing all kinds of interactive digital products. However, because interaction design has its roots in software for desktop computers, and the vast majority of today’s PCs run Microsoft Windows, there is certainly a bias in the focus our discussions—this is where the greatest need exists for understanding how to create effective, Goal-Directed user interfaces. Having said this, most of the material in this book transcends platform. It is equally applicable to all desktop platforms—Mac OS, Linux, and others—and the majority of it is relevant even for more divergent platforms such as kiosks, handhelds, embedded systems, and others. A good portion of examples in this book are from the Microsoft Word, Excel, PowerPoint, Outlook, and Internet Explorer, and Adobe Photoshop and Illustrator. We have tried to stick with examples from these mainstream applications for two reasons. First, readers are likely to be at least slightly familiar with the examples. Second, it’s important to show that the user interface design of even the most finely honed products can be significantly improved with a Goal-Directed approach. We have included a few examples from more exotic applications as well, in places where they were particularly illustrative. A few examples in this new edition come from now moribund software or OS ver- sions. These examples illustrate particular points that the authors felt were useful enough to retain in this edition. The vast majority of examples are from contem- porary software and OS releases. Who Should Read This Book While the subject matter of this book is broadly aimed at students and practition- ers of interaction design, anyone concerned about users interacting with digital technology will gain insights from reading this book. Programmers, designers of all stripes involved with digital product design, usability professionals, and project managers will all find something useful in this volume. People who have read ear- lier editions of About Face or The Inmates Are Running the Asylum will find new and updated information about design methods and principles here. We hope this book informs you and intrigues you, but most of all, we hope it makes you think about the design of digital products in new ways. The practice of interaction design is constantly evolving, and it is new and varied enough to generate a wide vari- ety of opinions on the subject. If you have an interesting opinion or just want to talk to us, we’d be happy to hear from you at,, and
  • 33. Part I Understanding Goal-Directed Design Chapter 1 Chapter 5 Goal-Directed Design Modeling Users: Personas and Goals Chapter 2 Implementation Models and Chapter 6 Mental Models The Foundations of Design: Scenarios and Requirements Chapter 3 Beginners, Experts, and Chapter 7 Intermediates From Requirements to Design: The Framework and Refinement Chapter 4 Understanding Users: Qualitative Research
  • 34. 1 Goal-Directed Design This book has a simple premise: If we design and construct products in such a way that the people who use them achieve their goals, these people will be satisfied, effective, and happy and will gladly pay for the products and recommend that oth- ers do the same. Assuming that this can be achieved in a cost-effective manner, it will translate into business success. On the surface, this premise sounds quite obvious and straightforward: Make peo- ple happy, and your products will be a success. Why then are so many digital prod- ucts so difficult and unpleasant to use? Why aren’t we all happy and successful? Digital Products Need Better Design Methods Most digital products today emerge from the development process like a creature emerging from a bubbling tank. Developers, instead of planning and executing with a mind towards satisfying the needs of the people who purchase and use their products, end up creating technologically focused solutions that are difficult to use and control. Like mad scientists, they fail because they have not imbued their cre- ations with humanity.
  • 35. 4 Part I: Understanding Goal-Directed Design Design, according to industrial designer Victor Papanek, is the conscious and intu- itive effort to impose meaningful order. We propose a somewhat more detailed defi- nition of human-oriented design activities: Understanding users’ desires, needs, motivations, and contexts Understanding business, technical, and domain opportunities, requirements, and constraints Using this knowledge as a foundation for plans to create products whose form, content, and behavior is useful, usable, and desirable, as well as economically viable and technically feasible This definition is useful for many design disciplines, although the precise focus on form, content, and behavior will vary depending on what is being designed. For example, an informational Web site may require particular attention to content, whereas the design of a chair is primarily concerned with form. As we discussed in the Introduction, interactive digital products are uniquely imbued with complex behavior. When performed using the appropriate methods, design can provide the missing human connection in technological products. But clearly, most current approaches to the design of digital products aren’t working as advertised. The creation of digital products today Digital products come into this world subject to the push and pull of two, often opposing, forces — developers and marketers. While marketers are adept at under- standing and quantifying a marketplace opportunity, and at introducing and posi- tioning a product within that market, their input into the product design process is often limited to lists of requirements. These requirements often have little to do with what users actually need or desire and have more to do with chasing the com- petition, managing IT resources with to-do lists, and making guesses based on mar- ket surveys — what people say they’ll buy. (Contrary to what you might suspect, few users are able to clearly articulate their needs. When asked direct questions about the products they use, most tend to focus on low-level tasks or workarounds to product flaws.) Unfortunately, reducing an interactive product to a list of hun- dreds of features doesn’t lend itself to the kind of graceful orchestration that is required to make complex technology useful. Adding “easy to use” to the list of requirements does nothing to improve the situation.
  • 36. Chapter 1: Goal-Directed Design 5 Developers, on the other hand, often have no shortage of input into the product’s final form and behavior. Because they are in charge of construction, they decide exactly what gets built. And they, too, have a different set of imperatives than the product’s eventual users. Good developers are focused on solving challenging tech- nical problems, following good engineering practices, and meeting deadlines. They are often given incomplete, confusing, and sometimes contradictory instructions and are forced to make significant decisions about the user experience with little time or background. Thus, the people who are most often responsible for the creation of our digital products rarely take into account the users’ goals, needs, or motivations, and at the same time tend to be highly reactive to market trends and technical constraints. This can’t help but result in products that lack a coherent user experience. We’ll soon see why goals are so important in addressing this issue. The results of poor product vision are, unfortunately, digital products that irritate, reduce productivity, and fail to meet user needs. Figure 1-1 shows the evolution of the development process and where, if at all, design has historically fit in. Most of digital product development is stuck in the first, second, or third step of this evolu- tion, where design either plays no real role or it becomes a surface-level patch on shoddy interactions — “lipstick on the pig,” as one of our clients once referred to it. The design process, as we will soon discuss, should precede coding and testing to ensure that products truly meet the needs of users. In the dozen years since the publication of the first edition of this book, software and interactive products have certainly improved. Many companies have begun to focus on serving the needs of people with their products, and are spending the time and money to do upfront design. Many more companies are still failing to do this, and as they maintain their focus on technology and marketing data, they continue to create the kind of digital products we’ve all grown to despise. Here are a few symptoms of this affliction. Digital products are rude Digital products often blame users for making mistakes that are not their fault, or should not be. Error messages like the one in Figure 1-2 pop up like weeds announcing that the user has failed yet again. These messages also demand that the user acknowledge his failure by agreeing: OK.
  • 37. 6 Part I: Understanding Goal-Directed Design Programmers Build/Test Ship Managers Programmers Initiate Build /Test Ship Managers Programmers QA Designers Build Test “Look Ship Initiate & Feel” Managers mandate Designers specs Programmers code QA product feasibility bug input Initiate Users Design feedback Build report Test Users Ship Figure 1-1 The evolution of the software development process. The first diagram depicts the early days of the software industry when smart programmers dreamed up products, and then built and tested them. Inevitably, professional managers were brought in to help facilitate the process by translating market opportunities into product requirements. As depicted in the third diagram, the industry matured, testing became a discipline in its own right, and with the popularization of the graphical user interface (GUI), graphic designers were brought in to create icons and other visual elements. The final diagram shows the Goal-Directed approach to software development where decisions about a product’s capabilities, form, and behavior are made before the expensive and challenging construction phase.
  • 38. Chapter 1: Goal-Directed Design 7 Figure 1-2 Thanks for sharing. Why didn’t the program notify the library? What did it want to notify the library about? Why is it telling us? And what are we OKing, anyway? It is not OK that the program failed! Digital products and software frequently interrogate users, peppering them with a string of terse questions that they are neither inclined or prepared to answer: “Where did you hide that file?” Patronizing questions like “Are you sure?” and “Did you really want to delete that file or did you have some other reason for pressing the Delete key?” are equally irritating and demeaning. Our software-enabled products also fail to act with a basic level of decency. They forget information we tell them and don’t do a very good job of anticipating our needs. For example, the feature-rich Palm Treo smartphone doesn’t anticipate that a user might want to add the phone number of someone who has just called to an existing contact. It doesn’t take a lot of research or imagination to deduce that this is something that many users will want to do, but nevertheless one is forced to go through a complicated maze involving copying the phone number, navigating to the contact in question, and pasting into the appropriate field. Digital products require people to think like computers Digital products regularly assume that people are technology literate. For example, in Microsoft Word, if a user wants to rename a document she is editing, she must know that she must either close the document, or use the “Save As...” menu command (and remember to delete the file with the old name). These behaviors are not consistent with the way a normal person thinks about renaming something; rather, they require that a person change her thinking to be more like the way a computer works. Digital products are also often obscure, hiding meaning, intentions, and actions from users. Programs often express themselves in incomprehensible jargon that cannot be fathomed by normal users (“How many stop bits?”) and are sometimes incomprehensible even to experts (“Please specify IRQ.”).
  • 39. 8 Part I: Understanding Goal-Directed Design Digital products exhibit poor behavior If a 10-year-old child behaved like some software programs or devices, he’d be sent to his room without supper. Programs forget to shut the refrigerator door, leave shoes in the middle of the floor, and can’t remember what you told them only five minutes earlier. For example, if you save a Microsoft Word document, print it, and then try to close it, the program once again asks you if you want to save it! Evidently the act of printing caused the program to think the document had changed, even though it did not. Sorry, Mom, I didn’t hear you. Programs often require us to step out of the main flow of tasks to perform func- tions that should fall immediately to hand. Dangerous commands, however, are often presented right up front where unsuspecting users can accidentally trigger them. The overall appearance of many programs is overly complex and confusing, making navigation and comprehension difficult. Digital products require humans to do the heavy lifting Computers and their silicon-enabled brethren are supposed to be labor-saving devices, but every time we go out into the field to watch real people doing their jobs with the assistance of technology, we are struck and horrified by how much work they are forced to do to manage the operation of software. This work can be any- thing from manually keying values from one window into another, to copying and pasting between applications that don’t otherwise speak to each other, to the ubiq- uitous clicking and pushing and pulling of windows around the screen to access hidden functionality that people use every day to do their job. Why are these products so bad? So what, then, is the real problem? Why is the technology industry generally so inept at designing the interactive parts of digital products? There are three primary reasons: ignorance about users, a conflict of interest between serving human needs and construction priorities, and the lack of a process for understanding human needs as an aid to developing appropriate product form and behavior. Ignorance about users It’s a sad truth that the digital technology industry doesn’t have a good under- standing of what it takes to make users happy. In fact, most technology products get built without much understanding of the users. We might know what market seg- ment our users are in, how much money they make, how much money they like to
  • 40. Chapter 1: Goal-Directed Design 9 spend on weekends, and what sort of cars they buy. Maybe we even have a vague idea what kind of jobs they have and some of the major tasks that they regularly perform. But does any of this tell us how to make them happy? Does it tell us how they will actually use the product we’re building? Does it tell us why they are doing whatever it is they might need our product for, why they might want to choose our product over our competitors, or how we can make sure they do? Unfortunately, it does not. We’ll soon see how to address the issue of understanding users and their behaviors with products. Conflicting interests A second problem affects the ability of vendors and manufacturers to make users happy. There is an important conflict of interest in the world of digital product development: The people who build the products — programmers — are usually also the people who design them. Programmers are often required to choose between ease of coding and ease of use. Because programmers’ performance is typ- ically judged by their ability to code efficiently and meet incredibly tight deadlines, it isn’t difficult to figure out what direction most software-enabled products take. Just as we would never permit the prosecutor in a legal trial to also adjudicate the case, we should make sure that the people designing a product are not the same people building it. Even with appropriate skills and the best intentions, it simply isn’t possible for a programmer to advocate effectively for the user, the business, and the technology all at the same time. The lack of a process The third reason the digital technology industry isn’t cranking out successful prod- ucts is that it has no reliable process for doing so. Or, to be more accurate, it doesn’t have a complete process for doing so. Engineering departments follow — or should follow — rigorous engineering methods that ensure the feasibility and quality of the technology. Similarly, marketing, sales, and other business units follow their own well-established methods for ensuring the commercial viability of new products. What’s left out is a repeatable, predictable, and analytical process for transforming an understanding of users into products that both meet their needs and excite their imaginations. When we think about complex mechanical devices, we take for granted that they have been carefully designed for use, in addition to being engineered. Most manu- factured objects are quite simple, and even complex mechanical products are quite
  • 41. 10 Part I: Understanding Goal-Directed Design simple when compared to most software and software-enabled products that can be compiled from over one million lines of code (compare this to a mechanical artifact of overwhelming complexity such as the space shuttle, which has 250,000 parts, only a small percentage of which are moving parts). Yet most software has never undergone a rigorous design process from a user-centered perspective. In the worst case, decisions about what a digital product will do and how it will communicate with users is simply a byproduct of its construction. Programmers, deep in their thoughts of algorithms and code, end up “designing” product behav- iors and user interfaces the same way that miners end up “designing” the landscape with cavernous pits and piles of rubble. In unenlightened development organiza- tions, the digital product interaction design process alternates between the acci- dental and the nonexistent. Sometimes organizations do adopt a design process, but it isn’t quite up to the task. Many programmers today embrace the notion that integrating customers directly into the development process on a frequent basis can solve human interface design problems. Although this has the salutary effect of sharing the responsibility for design with the user, it ignores a serious methodological flaw: a confusion of domain knowledge with design knowledge. Customers, although they might be able to articulate the problems with an interaction, are not often capable of visual- izing the solutions to those problems. Design is a specialized skill, just like programming. Programmers would never ask users to help them code; design prob- lems should be treated no differently. In addition, customers who purchase a prod- uct may not be the same people who use it from day to day, a subtle but important distinction. This doesn’t mean that designers shouldn’t be interested in getting feedback on their proposed solutions. However, each member of the product team should respect the others’ areas of expertise. Imagine a patient who visits his doctor with a horrible stomachache. “Doctor,” he says, “it really hurts. I think it’s my appendix. You’ve got to take it out as soon as possible.” Of course, a responsible physician wouldn’t per- form the surgery without question. The patient can express the symptoms, but it takes the doctor’s professional knowledge to make the correct diagnosis. To better understand how to create a workable process that brings user-centered design to digital products, it’s useful to understand a bit more about the history of design in manufacturing and about how the challenges of interactive products have substantially changed the demands on design.
  • 42. Chapter 1: Goal-Directed Design 11 The Evolution of Design in Manufacturing In the early days of industrial manufacturing, engineering and marketing processes alone were sufficient to produce desirable products: It didn’t take much more than good engineering and reasonable pricing to produce a hammer, diesel engine, or tube of toothpaste that people would readily purchase. As time progressed, manufacturers of consumer products realized that they needed to differentiate their products from functionally identical products made by competitors, so design was introduced as a means to increase user desire for a product. Graphic designers were employed to create more effective packaging and advertising, and industrial designers were engaged to create more comfortable, useful, and exciting forms. The conscious inclusion of design heralded the ascendance of the modern triad of product development concerns identified by Larry Keeley of the Doblin Group: capability, viability, and desirability (see Figure 1-3). If any one of these three foun- dations is significantly weak in a product, it is unlikely to stand the test of time. Now enter the computer, the first machine created by humans that is capable of almost limitless behavior when properly coded into software. The interesting thing about this complex behavior, or interactivity, is that it completely alters the nature of the products it touches. Interactivity is compelling to humans, so compelling that other aspects of an interactive product become marginal. Who pays attention to the black box that sits under your desk — it is the interactive screen, keyboard, and mouse to which users pay attention. Yet, the interactive behaviors of software and other digital products, which should be receiving the lion’s share of design attention, all too frequently receive no attention at all. The traditions of design that corporations have relied on to provide the critical pil- lar of desirability for products don’t provide much guidance in the world of inter- activity. Design of behavior is a different kind of problem that requires greater knowledge of context, not just rules of visual composition and brand. Design of behavior requires an understanding of the user’s relationship with the product from before purchase to end-of-life. Most important of all is the understanding of how the user wishes to use the product, in what ways, and to what ends.
  • 43. 12 Part I: Understanding Goal-Directed Design Desirability Capability What do What can people need? A successful product we build? is desirable and viable and buildable Viability What will sustain a business? Designers Management Technologists User model Business model Technology model ▶ motivations ▶ funding model ▶ core technologies ▶ behaviors ▶ income/expense ▶ technology components ▶ attitudes & aptitudes projections, etc ▶ build vs. buy Product design Business plan Technology plan ▶ design schedule ▶ marketing plan ▶ engineering schedule ▶ form and behavior spec ▶ launch plan ▶ engineering spec ▶ distribution plan User effectiveness & Sustainable business Project delivery Customer adoption Overall product success You can apply this to companies who have struggled to find the balance: Novell Apple Microsoft Novell emphasized Apple has emphasized Microsoft is one of the technology and gave desirability but has best run businesses little attention to made many business ever, but it has not been desirability. This made blunders. Nevertheless, able to create highly it vulnerable to it is sustained by the desirable products. This competition. loyalty created by its provides an opening for attention to the user competition. experiences. Figure 1-3 Building successful digital products. The diagram indicates the three major processes that need to be followed in tandem to create successful technology products. This book addresses the first and foremost issue: how to create a product people will desire.
  • 44. Chapter 1: Goal-Directed Design 13 Planning and Designing Behavior The planning of complex digital products, especially ones that interact directly with humans, requires a significant upfront effort by professional designers, just as the planning of complex physical structures that interact with humans requires a significant upfront effort by professional architects. In the case of architects, that planning involves understanding how the humans occupying the structure live and work, and designing spaces to support and facilitate those behaviors. In the case of digital products, the planning involves understanding how the humans using the product live and work, and designing product behavior and form that supports and facilitates the human behaviors. Architecture is an old, well-established field. The design of product and system behavior — interaction design — is quite new, and only in recent years has it begun to come of age as a discipline. Interaction design isn’t merely a matter of aesthetic choice; rather, it is based on an understanding of users and cognitive principles. This is good news because it makes the design of behavior quite amenable to a repeatable process of analysis and synthesis. It doesn’t mean that the design of behavior can be automated, any more than the design of form or content can be automated, but it does mean that a sys- tematic approach is possible. Rules of form and aesthetics mustn’t be discarded, of course, but they must work in harmony with the larger concern of achieving user goals via appropriately designed behaviors. This book presents a set of methods to address the needs of this new kind of behavior- oriented design, which addresses the goals (Rudolf, 1998) and motivations of users: Goal-Directed Design. To understand Goal-Directed Design, we first need to better understand user goals and how they provide the key to designing appropriate interac- tive behavior. Recognizing User Goals So what are user goals? How can we identify them? How do we know that they are real goals, rather than tasks they are forced to do by poorly designed tools or busi- ness processes? Are they the same for all users? Do they change over time? We’ll try to answer those questions in the remainder of this chapter. Users’ goals are often quite different from what we might guess them to be. For example, we might think that an accounting clerk’s goal is to process invoices efficiently. This is probably not true. Efficient invoice processing is more likely the goal of the clerk’s employer. The clerk is more likely concentrating on goals like appearing competent at his job and keeping himself engaged with his work while
  • 45. 14 Part I: Understanding Goal-Directed Design performing routine and repetitive tasks, although he may not verbally (or even consciously) acknowledge this. Regardless of the work we do and the tasks we must accomplish, most of us share these simple, personal goals. Even if we have higher aspirations, they are still more personal than work related: winning a promotion, learning more about our field, or setting a good example for others, for instance. Products designed and built to achieve business goals alone will eventually fail; per- sonal goals of users need to be addressed. When the user’s personal goals are met by the design, business goals are far more effectively achieved, for reasons we’ll explore in more detail in later chapters. If you examine most commercially available software, Web sites, and digital products today, you will find that their user interfaces fail to meet user goals with alarming fre- quency. They routinely: Make users feel stupid Cause users to make big mistakes Require too much effort to operate effectively Don’t provide an engaging or enjoyable experience Most of the same software is equally poor at achieving its business purpose. Invoices don’t get processed all that well. Customers don’t get serviced on time. Decisions don’t get properly supported. This is no coincidence. The companies that develop these products don’t have the right priorities. Most focus their attention far too narrowly on implementation issues, which distract them from the needs of users. Even when businesses become sensitive to their users, they are often powerless to change their products because the conventional development process assumes that the user interface should be addressed after coding begins — sometimes even after it ends. But just as you cannot effectively design a building after construction begins, you cannot easily make a program serve users’ goals once there is a signifi- cant and inflexible code base in place. Finally, when companies do focus on the users, they tend to pay too much attention to the tasks that users engage in and not enough attention to their goals in per- forming those tasks. Software can be technologically superb and perform each business task with diligence, yet still be a critical and commercial failure. We can’t ignore technology or tasks, but they play only a part in a larger schema that includes designing to meet user goals.
  • 46. Chapter 1: Goal-Directed Design 15 Goals versus tasks and activities Goals are not the same as tasks or activities. A goal is an expectation of an end con- dition, whereas both activities and tasks are intermediate steps (at different levels of organization) that help someone to reach a goal or set of goals. Donald Norman describes a hierarchy in which activities are composed of tasks, which are in turn composed of actions, which are then themselves composed of operations. Using this scheme, Norman advocates “Activity-Centered Design” (ACD), which focuses first and foremost on understanding activities. His claim is that humans adapt to the tools at hand, and understanding the activities that peo- ple perform with a set of tools can more favorably influence the design of those tools. The foundation of Norman’s thinking comes from Activity Theory, a Soviet- era Russian theory of psychology that emphasizes understanding who people are by understanding how they interact with the world, and which has in recent years been adapted to the study of human-computer interaction, most notably by Bonnie Nardi. Norman concludes, correctly, that the traditional task-based focus of digital prod- uct design has yielded inadequate results. Many developers and usability profes- sionals still approach the design of interfaces by asking, “What are the tasks?” Although this may get the job done, it won’t produce much more than an incre- mental improvement: It won’t provide a solution that differentiates your product in the market, and very often won’t really satisfy the user. While Norman’s ACD takes some important steps in the right direction by high- lighting the importance of the user’s context, we do not believe that it goes quite far enough. While a method like ACD can be very useful in properly breaking down the “what” of user behaviors, it really doesn’t address what should be the first question asked by any designer: Why is a user performing an activity, task, action, or operation in the first place? Goals motivate people to perform activities; under- standing goals allows you to understand the expectations and aspirations of your users, which can in turn help you decide which activities are truly relevant to your design. Task and activity analysis is useful at the detail level, but only after user goals have been analyzed. Asking, “What are the user’s goals?” lets you understand the meaning of activities to your users, and thus create more appropriate and satisfac- tory designs. If you’re still unsure about the difference between goals and activities or tasks, there is an easy way to tell the difference between them. Since goals are driven by human motivations, they change very slowly — if at all — over time. Activities and tasks are much more transient, since they are based almost entirely on whatever technology is
  • 47. 16 Part I: Understanding Goal-Directed Design at hand. For example, when traveling from St. Louis to San Francisco, a person’s goals are likely to include traveling quickly, comfortably, and safely. In 1850, a settler wishing to travel quickly and comfortably would have made the journey in a covered wagon; in the interest of safety, he would have brought along his trusty rifle. Today, a businessman traveling from St. Louis to San Francisco makes the journey in a jet aircraft and, in the interest of safety, he is required to leave his firearms at home. The goals of the settler and businessman remain unchanged, but their activities and tasks have changed so completely with the changes in technology that they are, in some respects, in direct opposition. Design based solely on understanding activities or tasks runs the risk of trapping the design in a model imposed by an outmoded technology, or using a model that meets the goals of a corporation without meeting the goals of their users. Looking through the lens of goals allows you to leverage available technology to eliminate irrelevant tasks and to dramatically streamline activities. Understanding users’ goals can help designers eliminate the tasks and activities that better technology renders unnecessary for humans to perform. Designing to meet goals in context Many designers assume that making interfaces easier to learn should always be a design target. Ease of learning is an important guideline, but in reality, as Brenda Laurel notes, the design target really depends on the context — who the users are, what they are doing, and what goals they have. You simply can’t create good design by following rules disconnected from the goals and needs of the users of your product. Let us illustrate: Take an automated call-distribution system. The people who use this product are paid based on how many calls they handle. Their most important concern is not ease of learning, but the efficiency with which users can route calls, and the rapidity with which those calls can be completed. Ease of learning is also important because it affects the happiness and, ultimately, the turnover rate of employees, so both ease and throughput should be considered in the design. But there is no doubt that throughput is the dominant demand placed on the system by the users and, if necessary, ease of learning should take a back seat. A program that walks the user through the call-routing process step by step each time merely frustrates him after he’s learned the ropes. On the other hand, if the product in question is a kiosk in a corporate lobby helping visitors find their way around, ease of use for first-time users is clearly a major goal. A general guideline of interaction design that seems to apply particularly well to productivity tools is that good design makes users more effective. This guideline takes
  • 48. Chapter 1: Goal-Directed Design 17 into account the universal human goal of not looking stupid, along with more particular goals of business throughput and ease of use that are relevant in most business situations. It is up to you as a designer to determine how you can make the users of your prod- uct more effective. Software that enables users to perform their tasks without addressing their goals rarely helps them be truly effective. If the task is to enter 5000 names and addresses into a database, a smoothly functioning data-entry applica- tion won’t satisfy the user nearly as much as an automated system that extracts the names from the invoicing system. Although it is the user’s job to focus on her tasks, the designer’s job is to look beyond the task to identify who the most important users are, and then to deter- mine what their goals might be and why. The design process, which we describe in the remainder of this chapter and detail in the remaining chapters of Part I, pro- vides a structure for determining the answers to these questions, a structure by which solutions based on this information can be systematically achieved. The Goal-Directed Design Process Most technology-focused companies don’t have an adequate process for user- centered design, if they have a process at all. But even the more enlightened organi- zations, those that can boast of an established process, come up against some criti- cal issues that result from traditional ways of approaching the problems of research and design. In recent years, the business community has come to recognize that user research is necessary to create good products, but the proper nature of that research is still in question in many organizations. Quantitative market research and market segmen- tation is quite useful for selling products but falls short of providing critical infor- mation about how people actually use products — especially products with complex behaviors (see Chapter 4 for a more in-depth discussion of this topic). A second problem occurs after the results have been analyzed: Most traditional methods don’t provide a means of translating research results into design solutions. A hundred pages of user survey data don’t easily translate into a set of product requirements, and they say even less about how those requirements should be expressed in terms of a meaningful and appropriate interface structure. Design remains a black box: “A miracle happens here.” This gap between research results and the ultimate design solution is the result of a process that doesn’t connect the dots from user to final product. We’ll soon see how to address this problem with Goal-Directed methods.
  • 49. 18 Part I: Understanding Goal-Directed Design Bridging the gap As we have briefly discussed, the role of design in the development process needs to change. We need to start thinking about design in new ways, and start thinking dif- ferently about how product decisions are made. Design as product definition Design has, unfortunately, become a limiting term in the technology industry. For many developers and managers, the word has come to mean what happens in the third process diagram shown in Figure 1-1: a visual facelift on the implementation model (see Chapter 2). But design, when properly deployed (as in the fourth process diagram shown in Figure 1-1), both identifies user requirements and defines a detailed plan for the behavior and appearance of products. In other words, design provides true product definition, based on goals of users, needs of business, and constraints of technology. Designers as researchers If design is to become product definition, designers need to take on a broader role than that assumed in traditional design, particularly when the object of this design is complex, interactive systems. One of the problems with the current development process is that roles in the process are overspecialized: Researchers perform research, and designers perform design (see Figure 1-4). The results of user and market research are analyzed by the usability and market researchers and then thrown over the transom to designers or programmers. What is missing in this model is a systematic means of translating and synthesizing the research into design solutions. One of the ways to address this problem is for designers to learn to be researchers. Market Research Design of Form performed by market analysts and ethnographers ? ? performed by graphic/GUI and industrial designers Figure 1-4 A problematic design process. Traditionally, research and design have been separated, with each activity handled by specialists. Research has, until recently, referred primarily to market research, and design is too often limited to visual design or skin-deep industrial design. More recently, user research has expanded to include qualitative, ethnographic data. Yet, without including designers in the research process, the connection between research data and design solutions remains tenuous at best.
  • 50. Chapter 1: Goal-Directed Design 19 There is a compelling reason for involving designers in the research process. One of the most powerful tools designers bring to the table is empathy: the ability to feel what others are feeling. The direct and extensive exposure to users that proper user research entails immerses designers in the users’ world, and gets them thinking about users long before they propose solutions. One of the most dangerous prac- tices in product development is isolating designers from the users because doing so eliminates empathic knowledge. Additionally, it is often difficult for pure researchers to know what user information is really important from a design perspective. Involving designers directly in research addresses both issues. In the authors’ practice, designers are trained in the research techniques described in Chapter 4 and perform their research without further support or collaboration. This is a satisfactory solution, provided that your team has the time and resources to train your designers fully in these techniques. If not, a cross-disciplinary team of designers and dedicated user researchers is appropriate. Although research practiced by designers takes us part of the way to Goal-Directed Design solutions, there is still a translation gap between research results and design details. The puzzle is missing several pieces, as we will discuss next. Between research and design: Models, requirements, and frameworks Few design methods in common use today incorporate a means of effectively and systematically translating the knowledge gathered during research into a detailed design specification. Part of the reason for this has already been identified: Design- ers have historically been out of the research loop and have had to rely on third- person accounts of user behaviors and desires. The other reason, however, is that few methods capture user behaviors in a manner that appropriately directs the definition of a product. Rather than providing infor- mation about user goals, most methods provide information at the task level. This type of information is useful for defining layout, workflow, and translation of func- tions into interface controls, but is less useful for defining the basic framework of what a product is, what it does, and how it should meet the broad needs of the user. Instead we need an explicit, systematic process to bridge the gap between research and design for defining user models, establishing design requirements, and translat- ing those into a high-level interaction framework (see Figure 1-5). Goal-Directed Design seeks to bridge the gap that currently exists in the digital product develop- ment process, the gap between user research and design, through a combination of new techniques and known methods brought together in more effective ways.
  • 51. 20 Part I: Understanding Goal-Directed Design A process overview Goal-Directed Design combines techniques of ethnography, stakeholder inter- views, market research, detailed user models, scenario-based design, and a core set of interaction principles and patterns. It provides solutions that meet the needs and goals of users, while also addressing business/organizational and technical impera- tives. This process can be roughly divided into six phases: Research, Modeling, Requirements Definition, Framework Definition, Refinement, and Support (see Figure 1-5). These phases follow the five component activities of interaction design identified by Gillian Crampton Smith and Philip Tabor — understanding, abstracting, structuring, representing, and detailing — with a greater emphasis on modeling user behaviors and defining system behaviors. Research Modeling Requirements Framework Refinement Support users users definition of user, definition of of behaviors, development and the and use business, and design structure form, and needs domain context technical needs and flow content Figure 1-5 The Goal-Directed Design process. The remainder of this chapter provides a high-level view of the five phases of Goal- Directed Design, and Chapters 4–7 provide more detailed discussion of the meth- ods involved in each of these phases. See Figure 1-6 for a more detailed diagram of the process, including key collaboration points and design concerns. Research The Research phase employs ethnographic field study techniques (observation and contextual interviews) to provide qualitative data about potential and/or actual users of the product. It also includes competitive product audits, reviews of market research and technology white papers and brand strategy, as well as one-on-one interviews with stakeholders, developers, subject matter experts (SMEs), and tech- nology experts as suits the particular domain. One of the principal outcomes of field observation and user interviews is an emer- gent set of behavior patterns — identifiable behaviors that help categorize modes of use of a potential or existing product. These patterns suggest goals and motiva- tions (specific and general desired outcomes of using the product). In business and technical domains, these behavior patterns tend to map into professional roles; for consumer products, they tend to correspond to lifestyle choices. Behavior patterns and the goals associated with them drive the creation of personas in the Modeling phase. Market research helps select and filter valid personas that fit business
  • 52. Chapter 1: Goal-Directed Design 21 models. Stakeholder interviews, literature reviews, and product audits deepen the designers’ understanding of the domain and elucidate business goals, brand attrib- utes, and technical constraints that the design must support. Chapter 4 provides a more detailed discussion of Goal-Directed research techniques. Modeling During the Modeling phase, behavior and workflow patterns discovered through analysis of the field research and interviews are synthesized into domain and user models. Domain models can include information flow and workflow diagrams. User models, or personas, are detailed, composite user archetypes that represent distinct groupings of behaviors, attitudes, aptitudes, goals, and motivations observed and identified during the Research phase. Personas serve as the main characters in a narrative, scenario-based approach to design that iteratively generates design concepts in the Framework Definition phase, provides feedback that enforces design coherence and appropriateness in the Refinement phase, and represents a powerful communication tool that helps devel- opers and managers to understand design rationale and to prioritize features based on user needs. In the Modeling phase, designers employ a variety of methodologi- cal tools to synthesize, differentiate, and prioritize personas, exploring different types of goals and mapping personas across ranges of behavior to ensure there are no gaps or duplications. Specific design targets are chosen from the cast of personas through a process of comparing goals and assigning a hierarchy of priority based on how broadly each persona’s goals encompass the goals of other personas. A process of designating persona types determines the amount of influence each persona has on the even- tual form and behavior of the design. A detailed discussion of persona and goal development can be found in Chapter 5. Requirements Definition Design methods employed by teams during the Requirements Definition phase provide the much-needed connection between user and other models and the framework of the design. This phase employs scenario-based design methods with the important innovation of focusing the scenarios not on user tasks in the abstract, but first and foremost on meeting the goals and needs of specific user per- sonas. Personas provide an understanding of which tasks are truly important and why, leading to an interface that minimizes necessary tasks (effort) while maximiz- ing return. Personas become the main characters of these scenarios, and the design- ers explore the design space via a form of role-playing.
  • 53. 22 Part I: Understanding Goal-Directed Design For each interface/primary persona, the process of design in the Requirements Definition phase involves an analysis of persona data and functional needs (expressed in terms of objects, actions, and contexts), prioritized and informed by persona goals, behaviors, and interactions with other personas in various contexts. This analysis is accomplished through an iteratively refined context scenario that starts with a “day in the life” of the persona using the product, describing high-level product touch points, and thereafter successively defining detail at ever-deepening levels. In addition to these scenario-driven requirements, designers consider the personas’ skills and physical capabilities as well as issues related to the usage envi- ronment. Business goals, desired brand attributes, and technical constraints are also considered and balanced with persona goals and needs. The output of this process is a requirements definition that balances user, business, and technical requirements of the design to follow. Framework Definition In the Framework Definition phase, designers create the overall product concept, defining the basic frameworks for the product’s behavior, visual design, and — if applicable — physical form. Interaction design teams synthesize an interaction framework by employing two other critical methodological tools in conjunction with context scenarios. The first is a set of general interaction design principles that provide guidance in determining appropriate system behavior in a variety of contexts. Chapters 2 and 3 and the whole of Part II are devoted to high-level inter- action design principles appropriate to the Framework Definition phase. The second critical methodological tool is a set of interaction design patterns that encode general solutions (with variations dependent on context) to classes of pre- viously analyzed problems. These patterns bear close resemblance to the concept of architectural design patterns first developed by Christopher Alexander, and more recently brought to the programming field by Erich Gamma, et al. Interaction design patterns are hierarchically organized and continuously evolve as new contexts arise. Rather than stifling designer creativity, they often provide needed leverage to approach difficult problems with proven design knowledge. After data and functional needs are described at this high level, they are translated into design elements according to interaction principles and then organized, using patterns and principles, into design sketches and behavior descriptions. The output of this process is an interaction framework definition, a stable design concept that provides the logical and gross formal structure for the detail to come. Successive iterations of more narrowly focused scenarios provide this detail in the Refinement phase. The approach is often a balance of top-down (pattern-oriented) design and bottom-up (principle-oriented) design.
  • 54. Chapter 1: Goal-Directed Design 23 When the product takes physical form, interaction designers and industrial design- ers begin by collaborating closely on various input vectors and approximate form factors the product might take, using scenarios to consider the pros and cons of each. As this is narrowed to a couple of options that seem promising, industrial designers begin producing early physical prototypes to ensure that the overall interaction concept will work. It’s critical at this early stage that industrial design- ers not go off and create concepts independent of the product’s behavior. As soon as an interaction framework begins to emerge, visual interface designers produce several options for a visual framework, which is sometimes also referred to as a visual language strategy. They use brand attributes as well as an under- standing of the overall interface structure to develop options for typography, color palettes, and visual style. Refinement The Refinement phase proceeds similarly to the Framework Definition phase, but with increasing focus on detail and implementation. Interaction designers focus on task coherence, using key path (walkthrough) and validation scenarios focused on storyboarding paths through the interface in high detail. Visual designers define a system of type styles and sizes, icons, and other visual elements that provide a com- pelling experience with clear affordances and visual hierarchy. Industrial designers, when appropriate, finalize materials and work closely with engineers on assembly schemes and other technical issues. The culmination of the Refinement phase is the detailed documentation of the design, a form and behavior specification, deliv- ered in either paper or interactive media as context dictates. Chapter 6 discusses in more detail the use of personas, scenarios, principles, and patterns in the Require- ments Definition, Framework Definition, and Refinement phases. Development Support Even a very well-conceived and validated design solution can’t possibly anticipate every development challenge and technical question. In our practice, we’ve learned that it’s important to be available to answer developers’ questions as they arise during the construction process. It is often the case that as the development team prioritizes their work and makes trade-offs to meet deadlines, the design must be adjusted, requiring scaled-down design solutions. If the interaction design team is not available to create these solutions, developers are forced to do this under time pressure, which has the potential to gravely compromise the integrity of the prod- uct’s design.
  • 55. 24 Part I: Understanding Goal-Directed Design Initiate Design Build Test Ship Goal-Directed Design Stakeholder Activity Concerns Collaboration Deliverable Scope Objectives, timelines, financial Research Meetings Document define project goals constraints, process, milestones Capabilities & Statement & schedule Scoping of Work Audit Business & marketing plans, Review existing work branding strategy, market research, & product product portfolio plans, competitors, relevant technologies Stakeholder Product vision, risks opportunities, Interviews Interviews constraints, logistics, users with stakeholders Understand product & users vision & constraints User interviews Users, potential users, behaviors, Check-in & observations attitudes, aptitudes, motivations, Preliminary Understand user environments, tools, challenges Research findings needs & behavior Personas Patterns in user & customer Modeling Check-in User & customer behaviors, attitudes, aptitudes, Personas archetypes goals, environments, tools, challenges Other Models Workflows among multiple Represent domain factors people, environments, artifacts beyond individual users & customers Context Scenarios How the product fits into the Requirements Definition Check-in Tell stories about personas life & environment & Scenarios & ideal user helps them achieve their goals Requirements experiences Requirements Functional & data needs, user Presentation Document Describe necessary mental models, design imperatives, User & Domain User & Domain capabilities of the product vision, business Analysis Analysis product requirements, technology Design Framework Elements Information, functions, Check-ins Define manifestations mechanisms, actions, domain Design of information object models Framework & functionality Framework Object relationships, conceptual Design overall groupings, navigation sequencing, structure of user principles & patterns, flow, experience sketches, storyboards Key Path & How the design fits into an ideal Validation Scenarios sequence of user behaviors, & Describe how the accommodates a variety of likely persona interacts with conditions Presentation the product Design Vision Detailed design Design Support Refinement Appearance, idioms, interface, Check-ins Document Refine & specify details widgets, behavior, information, Design Form & visualization, brand, experience, Refinement Behavior language, storyboards Specification Design Maintaining conceptual Design Collaborative Revision modification integrity of the design under Design Form & Accommodate new changing technology constraints Behavior constraints & timeline Specification Figure 1-6 A more detailed look at the Goal-Directed Design process.
  • 56. Chapter 1: Goal-Directed Design 25 Goals, not features, are the key to product success Developers and marketers often use the language of features and functions to dis- cuss products. This is only natural. Developers build software function by function, and a list of features is certainly one way to express a product’s value to potential customers (though this is clearly limiting, as well). The problem is that these are abstract concepts that only provide limited insight into how human beings can be effective and happy while using technology. Reducing a product’s definition to a list of features and functions ignores the real opportunity — orchestrating technological capability to serve human needs and goals. Too often the features of our products are a patchwork of nifty technological innovations structured around a marketing requirements document or organization of the development team with too little attention paid to the overall user experience. The successful interaction designer must maintain her focus on users’ goals amid the pressures and chaos of the product-development cycle. Although we discuss many other techniques and tools of interaction in this book, we always return to users’ goals. They are the bedrock upon which interaction design should be practiced. The Goal-Directed process, with its clear rationale for design decisions, makes col- laboration with developers and businesspeople easier, and ensures that the design in question isn’t guesswork, the whim of a creative mind, or just a reflection of the team members’ personal preferences. DESIGN Interaction design is not guesswork. principle Goal-Directed Design is a powerful tool for answering the most important ques- tions that crop up during the definition and design of a digital product: Who are my users? What are my users trying to accomplish? How do my users think about what they’re trying to accomplish? What kind of experiences do my users find appealing and rewarding? How should my product behave? What form should my product take? How will users interact with my product? How can my product’s functions be most effectively organized? How will my product introduce itself to first-time users?
  • 57. 26 Part I: Understanding Goal-Directed Design How can my product put an understandable, appealing, and controllable face on technology? How can my product deal with problems that users encounter? How will my product help infrequent and inexperienced users understand how to accomplish their goals? How can my product provide sufficient depth and power for expert users? The remainder of this book is dedicated to answering these questions. We share tools tested by years of experience with hundreds of products that can help you identify key users of your products, understand them and their goals, and translate this understanding into effective and appealing design solutions.
  • 58. 2 Implementation Models and Mental Models The computer industry makes frequent use of the term computer literacy. Pundits talk about how some people have it and some don’t, how those who have it will suc- ceed in the information economy, and how those who lack it will inevitably fall between the socioeconomic cracks. Computer literacy, however, is nothing more than a euphemism for forcing human beings to stretch their thinking to under- stand an alien, machine logic rather than having software-enabled products stretch to meet people’s ways of thinking. In this chapter, we discuss how a poor under- standing of users and the specific ways they approach digital products has exacer- bated the computer-literacy divide, and how software that better matches how people think and work can help solve the problem. Implementation Models Any machine has a mechanism for accomplishing its purpose. A motion picture projector, for example, uses a complicated sequence of intricately moving parts to create its illusion. It shines a very bright light through a translucent, miniature
  • 59. 28 Part I: Understanding Goal-Directed Design image for a fraction of a second. It then blocks out the light for a split second while it moves another miniature image into place. Then it unblocks the light again for another moment. It repeats this process with a new image 24 times per second. Software-enabled products don’t have mechanisms in the sense of moving parts; these are replaced with algorithms and modules of code that communicate with each other. The representation of how a machine or a program actually works has been called the system model by Donald Norman and others; we prefer the term implementation model because it describes the details of the way a program is implemented in code. User Mental Models From the moviegoer’s point of view, it is easy to forget the nuance of sprocket holes and light-interrupters while watching an absorbing drama. Many moviegoers, in fact, have little idea how the projector actually works, or how this differs from the way a television works. The viewer imagines that the projector merely throws a picture that moves onto the big screen. This is called the user’s mental model, or conceptual model. People don’t need to know all the details of how a complex mechanism actually works in order to use it, so they create a cognitive shorthand for explaining it, one that is powerful enough to cover their interactions with it, but that doesn’t neces- sarily reflect its actual inner mechanics. For example, many people imagine that, when they plug their vacuum cleaners and blenders into outlets in the wall, the electricity flows like water from the wall to the appliances through the little black tube of the electrical cord. This mental model is perfectly adequate for using house- hold appliances. The fact that the implementation model of household electricity involves nothing resembling a fluid actually traveling up the cord and that there is a reversal of electrical potential 120 times per second is irrelevant to the user, although the power company needs to know the details. In the digital world, however, the differences between a user’s mental model and the implementation model are often quite distinct. We tend to ignore the fact that our cellular telephone doesn’t work like a landline phone; instead, it is actually a radio transceiver that might swap connections between a half-dozen different cellular base antennas in the course of a two-minute call. Knowing this doesn’t help us to understand how to use the phone.
  • 60. Chapter 2: Implementation Models and Mental Models 29 The discrepancy between implementation and mental models is particularly stark in the case of software applications, where the complexity of implementation can make it nearly impossible for the user to see the mechanistic connections between his actions and the program’s reactions. When we use a computer to digitally edit sound or to create video special effects like morphing, we are bereft of analogy to the mechanical world, so our mental models are necessarily different from the implementation model. Even if the connections were visible, they would remain inscrutable to most people. Represented Models Software (and any digital product that relies on software) has a behavioral face it shows to the world that is created by the programmer or designer. This representa- tion is not necessarily an accurate description of what is really going on inside the computer, although unfortunately, it frequently is. This ability to represent the com- puter’s functioning independent of its true actions is far more pronounced in soft- ware than in any other medium. It allows a clever designer to hide some of the more unsavory facts of how the software is really getting the job done. This disconnection between what is implemented and what is offered as explanation gives rise to a third model in the digital world, the designer’s represented model — the way the designer chooses to represent a program’s functioning to the user. Donald Norman refers to this simply as the designer’s model. In the world of software, a program’s represented model can (and often should) be quite different from the actual processing structure of the program. For example, an operating system can make a network file server look as though it were a local disk. The model does not represent the fact that the physical disk drive may be miles away. This concept of the represented model has no widespread counterpart in the mechanical world. The relationship between the three models is shown in Figure 2-1. The closer the represented model comes to the user’s mental model, the easier he will find the program to use and to understand. Generally, offering a represented model that follows the implementation model too closely significantly reduces the user’s ability to learn and use the program, assuming (as is almost always the case) that the user’s mental model of his tasks differs from the implementation model of the software.
  • 61. 30 Part I: Understanding Goal-Directed Design Implementation Model Represented Models Mental Model reflects technology worse better reflects userís vision Figure 2-1 The way engineers must build software is often a given, dictated by various technical and business constraints. The model for how the software actually works is called the implementation model. The way users perceive the jobs they need to do and how the program helps them do it is their mental model of interaction with the software. It is based on their own ideas of how they do their jobs and how computers might work. The way designers choose to represent the working of the program to the user is called the represented model, which, unlike the other two models, is an aspect of software over which designers have great control. One of the most important goals of the designer should be to make the represented model match the mental model of users as closely as possible. It is therefore critical that designers understand in detail the way their target users think about the work they do with the software. We tend to form mental models that are simpler than reality; so if we create repre- sented models that are simpler than the actual implementation model, we help the user achieve a better understanding. Pressing the brake pedal in your car, for exam- ple, may conjure a mental image of pushing a lever that rubs against the wheels to slow you down. The actual mechanism includes hydraulic cylinders, tubing, and metal pads that squeeze on a perforated disk, but we simplify all that out of our minds, creating a more effective, albeit less accurate, mental model. In software, we imagine that a spreadsheet scrolls new cells into view when we click on the scroll- bar. Nothing of the sort actually happens. There is no sheet of cells out there, but a tightly packed data structure of values, with various pointers between them, from which the program synthesizes a new image to display in real time. Understanding how software actually works always helps someone to use it, but this understanding usually comes at a significant cost. One of the most significant ways in which computers can assist human beings is by putting a simple face on complex processes and situations. As a result, user interfaces that are consistent with users’ mental models are vastly superior to those that are merely reflections of the imple- mentation model.
  • 62. Chapter 2: Implementation Models and Mental Models 31 DESIGN User interfaces should be based on user mental models rather principle than implementation models. In Adobe Photoshop, users can adjust the color balance and brightness of an illus- tration using a feature called Variations. Instead of offering numeric fields for enter- ing color data — the implementation model — the Variations interface shows a set of thumbnail images, each with a different color balance (see Figure 2-2). A user can click on the image that best represents the desired color setting. The interface more closely follows his mental model, because the user — likely a graphic artist — is thinking in terms of how his image looks, not in terms of abstract numbers. Figure 2–2 Adobe Photoshop has a great example of software design to match user mental models. The Variations interface shows a set of thumbnail images, varying color balance and brightness by adjustable increments. A user can click on the image that best represents the desired color setting. This image then becomes the new default for more varied thumbnails. The interface follows the mental model of graphic artists who are after a particular look, not a set of abstract numerical values.
  • 63. 32 Part I: Understanding Goal-Directed Design If the represented model for software closely follows users’ mental models, it elim- inates needless complexity from the user interface by providing a cognitive frame- work that makes it evident to the user how his goals and needs can be met. DESIGN Goal-directed interactions reflect user mental models. principle A user’s mental model doesn’t necessarily have to be true or accurate, but it should enable him to work effectively. For example, most nontechnical computer users imagine that their video screen is the heart of their computer. This is only natural because the screen is what they stare at all the time and is the place where they see what the computer is doing. If you point out to a user that the computer is actually a little chip of silicon in that black box sitting under his desk, he will probably shrug and ignore this pointless (to him) bit of information. The fact that the CPU isn’t the same thing as the video display doesn’t help him think about how he interacts with his computer, even though it is a more technically accurate concept. Most Software Conforms to Implementation Models It is much easier to design software that reflects its implementation model. From the developer’s perspective, it’s perfectly logical to provide a button for every function, a field for every data input, a page for every transaction step, and a dialog for every code module. But while this adequately reflects the infrastructure of engineering efforts, it does little to provide coherent mechanisms for a user to achieve his goals. In the end, what is produced alienates and confuses the user, rather like the ubiqui- tous external ductwork in the dystopian setting of Terry Gilliam’s movie Brazil (which is full of wonderful tongue-in-cheek examples of miserable interfaces). User interfaces designed by engineers follow the implementation model User interfaces and interactions designed by engineers, who know precisely how software works, quite often lead to a represented model that is very consistent with its implementation model. To the engineers, such models are logical, truthful, and accurate; unfortunately, they are not very intelligible or effective for users. The majority of users don’t much care how a program is actually implemented.
  • 64. Chapter 2: Implementation Models and Mental Models 33 A good example of a digital product that conforms to implementation models is the typical component home theater system, which requires the user to know exactly how all of the components are wired together in order to switch, say, between view- ing a DVD and tuning a cable TV channel. In most products, users need to switch video sources, and sometimes even switch between multiple remote controls, to access the functions they need simply to watch their television. A more mental- model-centered alternative, adopted by some newer products, is to keep track of the component configuration in the remote, so that the user can simply pick “Watch TV,” and the remote sends the appropriate commands to the TV, cable box, DVD player, and surround audio system without the user needing to know what’s going on behind the scenes. Even the Windows user interface slips into the implementation model sometimes. If you drag a file between directories on the same hard drive, the program inter- prets this as a MOVE, meaning that the file is removed from the old directory and added to the new directory, closely following the mental model. However, if you drag a file from hard drive C to hard drive D, the action is interpreted as a COPY, meaning that the file is added to the new directory but not removed from the old directory. This behavior is rooted in the implementation model — the way the underlying file system actually works. When the operating system moves a file from one directory to another on the same drive, it merely relocates the file’s entry in the disk’s table of contents. It never actually erases and rewrites the file. But when it moves a file to another physical drive, it must physically copy the data onto the new drive. To conform to the user’s mental model, it should then erase the original even though that contradicts the implementation model. This inconsistency in the computer’s response to two seemingly similar user actions has the potential to create significant cognitive dissonance (confusion resulting from two contradictory images of reality) for users, which in turn makes this simple interaction difficult to learn. For a user to ultimately be able to achieve a desired result, he must understand that the computer’s behavior depends on the physical nature of the particular storage devices. Because treating the drag of a file from one disk to another as a COPY function can be desirable behavior, especially when copying files from a hard drive to removable media such as USB flash drives, many people aren’t aware that it is an inconsistent side effect of the implementation model. As computers mature and logical volumes represent more than just physical drives, the side effects stop being useful and instead become irritating because we have to memorize the idiosyncratic behavior of each volume type.
  • 65. 34 Part I: Understanding Goal-Directed Design Mathematical thinking leads to implementation model interfaces Interaction designers must shield users from implementation models. Just because a technique is well suited to solving a problem in software construction doesn’t necessarily mean that it is well suited to be a mental model for the user. Just because your car is constructed of welded metal parts doesn’t mean that you must be skilled with a welding torch to drive it. Most of the data structures and algorithms used to represent and manipulate infor- mation in software are logic tools based on mathematical algorithms. All program- mers are fluent in these algorithms, including such things as recursion, hierarchical data structures, and multithreading. The problem arises when the user interface attempts to accurately represent the concepts of recursion, hierarchical data, or multithreading. Mathematical thinking is an implementation model trap that is particularly easy for programmers to fall into. They solve programming problems by thinking math- ematically, so they naturally see these mathematical models as appropriate terms for inventing user interfaces. Nothing could be further from the truth. DESIGN Users don’t understand Boolean logic. principle For example, one of the most durable and useful tools in the programmer’s toolbox is Boolean algebra. It is a compact mathematical system that conveniently describes the behavior of the strictly on-or-off universe inside all digital computers. There are only two main operations: AND and OR. The problem is that the English language has an and and an or and they are usually interpreted — by nonprogrammers — as the exact opposite of the Boolean AND and OR. If the program expresses itself with Boolean notation, the user can be expected to misinterpret it. For example, this problem crops up frequently when querying databases. If we want to extract from a file of employees those who live in Arizona along with those who live in Texas, we would say to a human in English, “Find all my employees in Arizona and Texas.” To express this properly to a database in Boolean algebraic terms, we would say, “Find employees in Arizona OR Texas.” No employee lives in two states at once, so saying, “Find employees in Arizona AND Texas” is nonsensi- cal. In Boolean, this will almost always return nothing.
  • 66. Chapter 2: Implementation Models and Mental Models 35 Any application that interacts with users in Boolean is doomed to suffer severe user-interface problems. It is unreasonable to expect users to penetrate the confu- sion. They are well trained in English, so why should they have to express things in an unfamiliar language that, annoyingly, redefines key words. Mechanical-Age versus Information- Age Represented Models We are experiencing an incredible transformation from the age of industrial, mechanical artifacts to an age of digital, information objects. The change has only begun, and the pace is accelerating rapidly. The upheaval that society under- went as a result of industrialization will likely be dwarfed by that associated with the Information Age. Mechanical-Age representations It is only natural for us to try to draw the imagery and language of an earlier era that we are comfortable with into a new, less certain one. As the history of the industrial revolution shows, the fruits of new technology can often only be expressed at first with the language of an earlier technology. For example, we called railroad engines iron horses and automobiles were labeled horseless carriages. Unfortunately, this imagery and language colors our thinking more than we might admit. Naturally, we tend to use old representations in our new environments. Sometimes, the usage is valid because the function is identical, even if the underpinning tech- nology is different. For example, when we translate the process of typewriting with a typewriter into word processing on a computer, we are using a Mechanical-Age representation of a common task. Typewriters used little metal tabs to slew the car- riage rapidly over several spaces until it came to rest on a particular column. The process, as a natural outgrowth of the technology, was called tabbing or setting tabs. Word processors also have tabs because their function is the same; whether you are working on paper rolled around a platen or on images on a video screen, you need to rapidly slew to a particular margin offset. Sometimes, however, Mechanical-Age representations shouldn’t be translated ver- batim into the digital world. We don’t use reins to steer our cars, or a tiller, although both of these were tried in the early days of autos. It took many years to develop a steering idiom that was appropriate for the car. In word processors, we don’t need to load a new blank page after we fill the previous one; rather, the document scrolls continuously, with visual markers for page breaks.
  • 67. 36 Part I: Understanding Goal-Directed Design New technology demands new representations Sometimes tasks, processes, concepts, and even goals arise solely because new tech- nology makes them possible for the first time. With no reason to exist beforehand, they were not conceived of in advance. When the telephone was first invented, for example, it was, among other things, touted as a means to broadcast music and news, although it was personal communication that became the most popular and widely developed. Nobody at the time would ever have conceived of the telephone as being a ubiquitous personal object that people would carry in their pockets and purses and that would ring annoyingly in the midst of theater performances. With our Mechanical-Age mindset, we have a hard time seeing appropriate Infor- mation-Age representations — at first. The real advantages of the software prod- ucts that we create often remain invisible until they have a sizable population of users. For example, the real advantage of e-mail isn’t simply that it’s faster than postal mail — the Mechanical-Age view — but rather that it promotes the flatten- ing and democratization of the modern business organization — the Information- Age advantage. The real advantage of the Web isn’t cheaper and more efficient communication and distribution — the Mechanical-Age view. Instead, it is the cre- ation of virtual communities — the Information-Age advantage that was revealed only after it materialized in our grasp. Because we have a hard time seeing how digital products will be used, we tend to rely too much on representations from the past, Mechanical Age. Mechanical-Age representations degrade user interaction We encounter a problem when we bring our familiar Mechanical-Age representa- tions over to the computer. Simply put, Mechanical-Age processes and representa- tions tend to degrade user interactions in Information-Age products. Mechanical procedures are easier to perform by hand than they are with computers. For exam- ple, typing an individual address on an envelope using a computer requires signifi- cant overhead compared to addressing the envelope with pen and ink (although the former might look neater). The situation improves only if the process is automated for a large number of instances in batch — 500 envelopes that you need to address. As another example, take a contact list on a computer. If it is faithfully rendered onscreen like a little bound book, it will be much more complex, inconvenient, and difficult to use than the physical address book. The physical address book, for example, stores names in alphabetical order by last name. But what if you want to find someone by her first name? The Mechanical-Age artifact doesn’t help you: You
  • 68. Chapter 2: Implementation Models and Mental Models 37 have to scan the pages manually. So, too, does the faithfully replicated digital ver- sion: It can’t search by first name either. The difference is that, on the computer screen, you lose many subtle visual cues offered by the paper-based book (bent page corners, penciled-in notes). Meanwhile, the scrollbars and dialog boxes are harder to use, harder to visualize, and harder to understand than simply flipping pages. DESIGN Don’t replicate Mechanical-Age artifacts in user interfaces without principle Information-Age enhancements. Real-world mechanical systems have the strengths and weaknesses of their medium, such as pen and paper. Software has a completely different set of strengths and weaknesses, yet when mechanical representations are replicated without change, they combine the weaknesses of the old with the weaknesses of the new. In our address book example, the computer could easily search for an entry by first name, but, by storing the names in exactly the same way as the mechanical artifact, we deprive ourselves of new ways of searching. We limit ourselves in terms of capa- bilities possible in an information medium, without reaping any of the benefits of the original mechanical medium. When designers rely on Mechanical-Age representations to guide them, they are blinded to the far greater potential of the computer to provide sophisticated infor- mation management in a better, albeit different, way. The use of a Mechanical-Age representation in a user interface can operate as a metaphor that artificially con- strains the design. For further discussion of the pitfalls surrounding reliance on metaphors in user interfaces, see Chapter 13. Improving on Mechanical-Age representations: An example Although new technologies can bring about entirely new concepts, they can also extend and build upon old concepts, allowing designers to take advantage of the power of the new technology on behalf of users through updated representations of their interface. For example, take the calendar. In the nondigital world, calendars are made of paper and are usually divided up into a one-month-per-page format. This is a rea- sonable compromise based on the size of paper, file folders, briefcases, and desk drawers.
  • 69. 38 Part I: Understanding Goal-Directed Design Programs with visual representations of calendars are quite common, and they almost always display one month at a time. Even if they can show more than one month, as Outlook does, they almost always display days in discrete one-month chunks. Why? Paper calendars show a single month because they are limited by the size of the paper, and a month is a convenient breaking point. Computer screens are not so constrained, but most designers copy the Mechanical-Age artifact faithfully (see Figure 2-3). On a computer, the calendar could easily be a continuously scrolling sequence of days, weeks, or months as shown in Figure 2-4. Scheduling something from August 28 to September 4 would be simple if weeks were contiguous instead of broken up by the arbitrary monthly division. Similarly, the grid pattern in digital calendars is almost always of a fixed size. Why couldn’t the width of columns of days or the height of rows of weeks be adjustable like a spreadsheet? Certainly you’d want to adjust the sizes of your weekends to reflect their relative importance in relation to your weekdays. If you’re a busi- nessperson, your working-week calendar would demand more space than a vacation week. The idioms are as well known as spreadsheets — that is to say, universal — but the Mechanical-Age representations are so firmly entrenched that we rarely see software publishers deviate from it. Figure 2-3 The ubiquitous calendar is so familiar that we rarely stop to apply Information-Age sensibilities to its design on the screen. Calendars were originally designed to fit on stacked sheets of paper, not interactive digital displays. How would you redesign it? What aspects of the calendar are artifacts of its old, Mechanical-Age platform?
  • 70. Chapter 2: Implementation Models and Mental Models 39 Figure 2-4 Scrolling is a very familiar idiom to computer users. Why not replace the page-oriented representation of a calendar with a scrolling representation to make it better? This perpetual calendar can do everything the old one can, and it also solves the mechanical-representation problem of scheduling across monthly boundaries. Don’t drag old limitations onto new platforms out of habit. What other improvements can you think of? The designer of the software in Figure 2-3 probably thought of calendars as canon- ical objects that couldn’t be altered from the familiar. Surprisingly, most time- management software handles time internally — in its implementation model — as a continuum, and only renders it as discrete months in its user interface — its represented model! Some might counter that the one-month-per-page calendar is better because it is easily recognizable and familiar to users. However, the new model is not that dif- ferent from the old model, except that it permits the users to easily do something they couldn’t do easily before — schedule across monthly boundaries. People don’t find it difficult to adapt to newer, more useful representations of familiar systems. DESIGN Significant change must be significantly better. principle
  • 71. 40 Part I: Understanding Goal-Directed Design Paper-style calendars in personal information managers (PIMs) and schedulers are mute testimony to how our language influences our designs. If we depend on words from the Mechanical Age, we will build software from the Mechanical Age. Better software is based on Information-Age thinking.
  • 72. 3 Beginners, Experts, and Intermediates Most computer users know all too well that buying a new cell phone or opening the shrink-wrap on a new software product augurs several days of frustration and dis- appointment spent learning the new interface. On the other hand, many experi- enced users of a digital product may find themselves continually frustrated because that product always treats them like rank beginners. It seems impossible to find the right balance between catering to the needs of the first-timer and the needs of the expert. One of the eternal conundrums of interaction and interface design is how to address the needs of both beginning users and expert users with a single, coherent interface. Some programmers and designers choose to abandon this idea com- pletely, choosing instead to segregate the user experiences by creating wizards for beginners and burying critical functionality for experts deep in menus. Of course, no one wants to deal with the extra labor associated with moving through a wizard, but the leap from there to knowing what esoteric command to select from a series of long menus is usually a jump off a rather tall cliff into a shark-infested moat of implementation-model design. What, then, is the answer? The solution to this predicament lies in a different understanding of the way users master new concepts and tasks.
  • 73. 42 Part I: Understanding Goal-Directed Design Perpetual Intermediates Most users are neither beginners nor experts; instead, they are intermediates. The experience level of people performing an activity tends, like most population distributions, to follow the classic statistical bell curve (see Figure 3-1). For almost any activity requiring knowledge or skill, if we graph number of people against skill level, a relatively small number of beginners are on the left side, a few experts are on the right, and the majority — intermediate users — are in the center. Beginners Intermediates Experts What does the I forgot how to import. How do I automate this? program do? How do I find facility X? What are the shortcuts How do I print? for this command? Remind me what this does. What is the program’s Can this be changed? What was the command for X? scope? How can I customize Opps! Can I undo? Where do I start? this? What is this control for? What is dangerous? What new features are in Is there a keyboard this upgrade? equivalent? Figure 3-1 The demands that users place on digital products vary considerably with their experience. Statistics don’t tell the whole story, however. The bell curve is a snapshot in time, and although most intermediates tend to stay in that category, the beginners do not remain beginners for very long. The difficulty of maintaining a high level of expertise also means that experts come and go rapidly, but beginners change even more rapidly. Both beginners and experts tend over time to gravitate towards intermediacy. Although everybody spends some minimum time as a beginner, nobody remains in that state for long. People don’t like to be incompetent, and beginners, by defini- tion, are incompetent. Conversely, learning and improving is rewarding, so begin- ners become intermediates very quickly — or they drop out altogether. All skiers, for example, spend time as beginners, but those who find they don’t rapidly progress beyond more-falling-than-skiing quickly abandon the sport. The rest soon move off of the bunny slopes onto the regular runs. Only a few ever make it onto the double-black diamond runs for experts.
  • 74. Chapter 3: Beginners, Experts, and Intermediates 43 DESIGN Nobody wants to remain a beginner. principle Most occupants of the beginner end of the curve will either migrate into the center bulge of intermediates, or they will drop off of the graph altogether and find some product or activity in which they can migrate into intermediacy. Most users thus remain in a perpetual state of adequacy striving for fluency, with their skills ebbing and flowing like the tides depending on how frequently they use the product. Larry Constantine first identified the importance of designing for intermediates, and in his book Software for Use, he refers to such users as improving intermediates. We prefer the term perpetual intermediates, because although beginners quickly improve to become intermediates, they seldom go on to become experts. Many popular ski resorts have a gentle slope for learning and a few expert runs to really challenge the serious skier. But if the resort wants to stay in business, it will cater to the perpetual intermediate skier, without scaring off the beginner or insult- ing the expert. The beginner must find it easy to matriculate into the world of inter- mediacy, and the expert must not find his vertical runs obstructed by aids for trepidatious or conservative intermediates. In many cases, a well-balanced user interface takes the same approach. It doesn’t cater to the beginner or to the expert, but rather devotes the bulk of its efforts to satisfying the perpetual intermediate. At the same time, it provides mechanisms so that both of its smaller constituencies can be effective. Most users in this middle state would like to learn more about the product but usu- ally don’t have the time. Occasionally, the opportunity to do so will surface. Some- times these intermediates use the product extensively for weeks at a time to complete a big project. During this time, they learn new things about the product. Their knowledge grows beyond its previous boundaries. Sometimes, however, they do not use the product for months at a time and forget sig- nificant portions of what they knew. When they return to the product, they are not beginners, but they will need reminders to jog their memory back to its former state. In some specialized products, it is appropriate to optimize the user experience for experts. In particular, tools that technically minded people rely on for a significant portion of their professional responsibilities should be inflected towards a high degree of proficiency. Development tools often fall into this category, as do scien- tific instrumentation and medical devices. We expect the users of those products to come to the table with the necessary technical knowledge, and to be willing to invest significant time and effort to mastering the application.
  • 75. 44 Part I: Understanding Goal-Directed Design Similarly, there are other products, especially those used in a transient manner, or those used by people with certain disabilities, that must be optimized for beginners. Examples we have worked on include informational kiosks designed for public spaces like museums, or a device that helps elderly patients with diminished abili- ties take their blood pressure. We are often asked whether consumer Web sites should be optimized for beginners or intermediates. Ultimately, we believe that the same considerations that we apply to other digital products should be used here. A well-designed Web site interface should help its user become quickly familiar and comfortable with navigation and functionality. Something worth considering here is that even a customer who has visited your site several times before and may be familiar with what you offer and with Web interaction idioms in general, may not visit your site frequently enough to memorize organizational constructs. This increases the importance of making interactions on your site as transparent and discoverable as possible. Also, as it has become increasingly popular to provide an adaptive experience by tracking user actions on a Web site, it is often useful to rely on cookies to identify a new visitor and to provide unobtrusive orientation assistance for the first few visits to the site. Designing for Different Experience Levels Now let’s contrast our bell curve of intermediates with the way that software is developed. Programmers qualify as experts in the software they code because they have to explore every possible use case, no matter how obscure and unlikely, to cre- ate program code to handle it. Their natural tendency is to design implementation- model software with every possible option given equal emphasis in the interaction, which they, as experts, have no problem understanding. At the same time, sales, marketing, and management often demonstrate the prod- uct to customers, reporters, partners, and investors who are themselves unfamiliar with the product. Because of their constant exposure to beginners, these profes- sionals have a strongly biased view of the user community. Therefore, it comes as no surprise that sales and marketing folks lobby for bending the interface to serve beginners. They demand that training wheels be attached to the product to help out the struggling beginner. Programmers create interactions suitable only for experts, while the marketers demand interactions suitable only for beginners, but — as we have seen — the largest, most stable, and most important group of users is the intermediate group.
  • 76. Chapter 3: Beginners, Experts, and Intermediates 45 It’s amazing to think that the majority of real users are typically ignored, but more often than not that is the case. You can see it in many enterprise and commercial software-based products. The overall design biases them towards expert users, while at the same time, cumbersome tools like wizards and Clippy are grafted on to meet the marketing department’s perception of new users. Experts rarely use them, and beginners soon desire to discard these embarrassing reminders of their igno- rance. But the perpetual intermediate majority is perpetually stuck with them. DESIGN Optimize for intermediates. principle Our goal should be neither to pander to beginners nor to rush intermediates into expertise. Our goal is threefold: to rapidly and painlessly get beginners into inter- mediacy, to avoid putting obstacles in the way of those intermediates who want to become experts, and most of all, to keep perpetual intermediates happy as they stay firmly in the middle of the skill spectrum. We need to spend more time making our products powerful and easy to use for perpetual intermediate users. We must accommodate beginners and experts, too, but not to the discomfort of the largest segment of users. The remainder of this chapter describes some basic strategies for accomplishing this. What beginners need Beginners are undeniably sensitive, and it is easy to demoralize a first-timer, but we must keep in mind that the state of beginnerhood is never an objective. Nobody wants to remain a beginner. It is merely a rite of passage everyone must experience. Good software shortens that passage without bringing attention to it. As an interaction designer, it’s best to imagine that users — especially beginners — are simultaneously very intelligent and very busy. They need some instruction, but not very much, and the process has to be rapid and targeted. If a ski instructor begins lecturing on snowpack composition and meteorology, he will lose his stu- dents regardless of their aptitude for skiing. Just because a user needs to learn how to operate a product doesn’t mean that he needs or wants to learn how it works inside. DESIGN Imagine users as very intelligent but very busy. principle
  • 77. 46 Part I: Understanding Goal-Directed Design On the other hand, intelligent people always learn better when they understand cause and effect, so you must give them an understanding of why things work as they do. We use mental models to bridge the contradiction. If the represented model of the interface closely follows the user’s mental model (as discussed in Chapter 2), it will provide the understanding the user needs without forcing him to figure out the implementation model. Getting beginners on board A new user must grasp the concepts and scope of the product quickly or he will abandon it. Thus, the first order of business of the designer is to ensure that the product adequately reflects the user’s mental model of his tasks. He may not recall from use to use exactly which command is needed to act on a particular object, but he will definitely remember the relationships between objects and actions — the important concepts — if the interface’s conceptual structure is consistent with his mental model. To get beginners to a state of intermediacy requires extra help from the program, but this extra help will get in their way as soon as they become intermediates. This means that whatever extra help you provide, it must not be fixed into the interface. It must know how to go away when its services are no longer required. Standard online help is a poor tool for providing such beginner assistance. We’ll talk more about help in Chapter 25, but its primary utility is as a reference, and beginners don’t need reference information; they need overview information, such as a guided tour. A separate guide facility — displayed within a dialog box — is a fine means for communicating overview, scope, and purpose. As the user begins to use the prod- uct, a dialog box can appear that states the basic goals and tools of the product, naming the main features. As long as the guide stays focused on beginner issues, like scope and goals, and avoids perpetual intermediate and expert issues (dis- cussed below), it should be adequate for assisting beginners. Beginners also rely heavily upon menus to learn and execute commands (see Chap- ter 22 for a detailed discussion about why this is true). Menus may be slow and clunky, but they are also thorough and verbose, so they offer reassurances. The dia- log boxes that the menu items launch (if they do so at all) should also be (tersely) explanatory, and come with convenient Cancel buttons.
  • 78. Chapter 3: Beginners, Experts, and Intermediates 47 What experts need Experts are also a vital group because they have a disproportionate influence on less experienced users. When a prospective buyer considers your product, he will trust the expert’s opinion more than an intermediate’s. If the expert says, “It’s not very good,” she may mean “It’s not very good for experts.” The beginner doesn’t know that, however, and will take the expert’s advice, even though it may not apply. Experts might occasionally look for esoteric features, and they might make heavy use of a few of them. However, they will definitely demand faster access to their reg- ular working set of tools, which may be quite large. In other words, experts want shortcuts to everything. Anyone who uses a digital product for hours a day will very quickly internalize the nuances of its interface. It isn’t so much that they want to cram frequently used commands into their heads, as much as it is unavoidable. Their frequency of use both justifies and requires the memorization. Expert users constantly, aggressively seek to learn more and to see more connec- tions between their actions and the product’s behavior and representation. Experts appreciate new, powerful features. Their mastery of the product insulates them from becoming disturbed by the added complexity. What perpetual intermediates need Perpetual intermediates need access to tools. They don’t need scope and purpose explained to them because they already know these things. ToolTips (see Chapter 23) are the perfect perpetual intermediate idiom. ToolTips say nothing about scope and purpose and meaning; they only state function in the briefest of idioms, con- suming the least amount of video space in the process. Perpetual intermediates know how to use reference materials. They are motivated to dig deeper and learn, as long as they don’t have to tackle too much at once. This means that online help is a perpetual intermediate tool. They use it by way of the index, so that part of help must be very comprehensive. Perpetual intermediates establish the functions that they use with regularity and those that they only use rarely. The user may experiment with obscure features, but he will soon identify — probably subconsciously — his frequently used working set. The user will demand that the tools in his working set be placed front and cen- ter in the user interface, easy to find and to remember.
  • 79. 48 Part I: Understanding Goal-Directed Design Perpetual intermediates usually know that advanced features exist, even though they may not need them or know how to use them. But the knowledge that they are there is reassuring to the perpetual intermediate, convincing him that he made the right choice investing in this product. The average skier may find it inspirational to know that there is a really scary, black-diamond, expert run just beyond those trees, even if she never intends to use it. It gives her something to aspire to and dream about, and it gives her the sense that she’s at a good ski resort. Your product’s code must provide for both rank amateurs and all the possible cases an expert might encounter. Don’t let this technical requirement influence your design thinking. Yes, you must provide those features for expert users. Yes, you must provide support for beginners. But in most cases, you must apply the bulk of your talents, time, and resources to designing the best interaction possible for your most representative users: the perpetual intermediates.
  • 80. 4 Understanding Users: Qualitative Research The outcome of any design effort must ultimately be judged by how successfully it meets the needs of both the product user and the organization that commissioned it. No matter how skillful and creative the designer, if she does not have clear and detailed knowledge of the users she is designing for, the constraints of the problem, and the business or organizational goals that are driving design activities, she will have little chance of success. Real insight into these topics can’t be achieved by digging through the piles of num- bers that come from a quantitative study like a market survey (though these can be critical for answering other kinds of questions). Rather, this kind of deep knowl- edge can only be achieved by qualitative research techniques. There are many types of qualitative research, each of which can play an important role in understanding the design landscape of a product. In this chapter, we focus on specific qualitative research techniques that support the design methods described in subsequent chapters. At the end of the chapter, we briefly discuss how quantitative research can, and cannot, be used to help support this effort.
  • 81. 50 Part I: Understanding Goal-Directed Design Qualitative versus Quantitative Research Research is a word that most people associate with science and objectivity. This association isn’t incorrect, but it biases many people towards the notion that the only valid sort of research is the kind that yields the supposed ultimate in objectiv- ity: quantitative data. It is a common perspective in business and engineering that numbers represent truth, even though we all know that numbers — especially sta- tistics describing human activities — are subject to interpretation and can be manipulated at least as dramatically as words. Data gathered by the hard sciences like physics are simply different from that gath- ered on human activities: Electrons don’t have moods that vary from minute to minute, and the tight controls physicists place on their experiments to isolate observed behaviors are impossible in the social sciences. Any attempt to reduce human behavior to statistics is likely to overlook important nuances, which can make an enormous difference to the design of products. Quantitative research can only answer questions about “how much” or “how many” along a few reductive axes. Qualitative research can tell you about what, how, and why in rich detail that is reflective of the actual complexities of real human situations. Social scientists have long realized that human behaviors are too complex and sub- ject to too many variables to rely solely on quantitative data to understand them. Design and usability practitioners, borrowing techniques from anthropology and other social sciences, have developed many qualitative methods for gathering use- ful data on user behaviors to a more pragmatic end: to help create products that better serve user needs. The value of qualitative research Qualitative research helps us understand the domain, context, and constraints of a product in different, more useful ways than quantitative research does. It also helps us identify patterns of behavior among users and potential users of a product much more quickly and easily than would be possible with quantitative approaches. In particular, qualitative research helps us understand: Behaviors, attitudes, and aptitudes of potential product users Technical, business, and environmental contexts — the domain — of the product to be designed
  • 82. Chapter 4: Understanding Users: Qualitative Research 51 Vocabulary and other social aspects of the domain in question How existing products are used Qualitative research can also help the progress of design projects by: Providing credibility and authority to the design team, because design decisions can be traced to research results Uniting the team with a common understanding of domain issues and user con- cerns Empowering management to make more informed decisions about product design issues that would otherwise be based on guesswork or personal preference It’s our experience that in comparison, qualitative methods tend to be faster, less expensive, and more likely to provide useful answers to important questions that lead to superior design: How does the product fit into the broader context of people’s lives? What goals motivate people to use the product, and what basic tasks help peo- ple accomplish these goals? What experiences do people find compelling? How do these relate to the prod- uct being designed? What problems do people encounter with their current ways of doing things? The value of qualitative studies is not limited to helping support the design process. In our experience, spending the time to understand the user population as human beings can provide valuable business insights that are not revealed through tradi- tional market research. In one particularly illustrative example, we were asked by a client to perform a user study for an entry-level consumer video-editing product for Windows users. An established developer of video-editing and -authoring software, the client had used traditional market research techniques to identify a significant business opportu- nity in developing a product for people who owned a digital video camera and a computer but hadn’t connected the two yet. In the field, we conducted interviews with a dozen users in the target market. Our first discovery was not surprising — that the people who did the most taping and had the strongest desire to share edited versions of their videos were parents. The second discovery, however, was quite startling. Of the 12 people whose homes we visited, only one person had successfully connected his video camera to his computer, and he had relied on the IT guy at work to set it up for him. One of the
  • 83. 52 Part I: Understanding Goal-Directed Design necessary preconditions of the success of the product was that people could actu- ally get video onto their computers to edit, but at the time it was extremely difficult to get a FireWire or video capture card functioning properly on an Intel-based PC. As a result of four days of research, we were able to help our client make a decision to put a hold on the product, which likely ended up saving them a considerable investment. Types of qualitative research Social science and usability texts are full of methods and techniques for conducting qualitative research, and readers are encouraged to explore this literature. In this chapter, we will focus specifically on techniques that have been proven effective in our practice over the last decade, occasionally drawing attention to similar tech- niques practiced in the design and usability fields at large. We will also try to avoid getting bogged down in theory, and instead will present these techniques from a pragmatic perspective. The qualitative research activities we have found to be most useful in our practice are: Stakeholder interviews Subject matter expert (SME) interviews User and customer interviews User observation/ethnographic field studies Literature review Product/prototype and competitive audits Stakeholder interviews Research for any new product design should start by understanding the business and technical context surrounding the product. In almost all cases, the reason a product is being designed (or redesigned) is to achieve one or several specific busi- ness outcomes (most commonly, to make money). It is the designers’ obligation to develop solutions without ever losing sight of these business goals, and it is there- fore critical that the design team begin its work by understanding the opportunities and constraints that are behind the design brief. As Donald Schön so aptly puts it, “design is a conversation with materials”1 This means that for a designer to craft an appropriate solution, he must understand the capabilities and limitations of the “materials” that will be used to construct the product, whether they be lines of code or extruded plastic.
  • 84. Chapter 4: Understanding Users: Qualitative Research 53 Generally speaking, a stakeholder is anyone with authority and/or responsibility for the product being designed. More specifically, stakeholders are key members of the organization commissioning the design work, and typically include executives, managers, and representative contributors from development, sales, product man- agement, marketing, customer support, design, and usability. They may also include similar people from other organizations in business partnership with the commissioning organization. Interviews with stakeholders should occur before any user research begins because these discussions often inform how user research is conducted. Also, it is usually most effective to interview each stakeholder in isolation, rather than in a larger, cross-departmental group. A one-on-one setting promotes candor on the part of the stakeholder, and ensures that individual views are not lost in a crowd. (One of the most interesting things that can be discovered in such interviews is the extent to which everyone in a product team shares — or doesn’t share — a common vision.) Interviews need not last longer than about an hour, though follow-up meetings may be called for if a particular stakeholder is identified as an exceptionally valu- able source of information. The type of information that is important to gather from stakeholders includes: Preliminary product vision — As in the fable of the blind men and the elephant, you may find that each business department has a slightly different and slightly incomplete perspective on the product to be designed. Part of the design approach must therefore involve harmonizing these perspectives with those of users and customers. Budget and schedule — Discussions on this topic often provide a reality check on the scope of the design effort and provide a decision point for management if user research indicates a greater (or lesser) scope is required. Technical constraints and opportunities — Another important determinant of design scope is a firm understanding of what is technically feasible given bud- get, time, and technology constraints. It is also often the case that a product is being developed to capitalize on a new technology. Understanding the opportu- nities underlying this technology can help shape the product’s direction. Business drivers — It is important for the design team to understand what the business is trying to accomplish. This again leads to a decision point, should user research indicate a conflict between business and user needs. The design must, as much as possible, create a win-win situation for users, customers, and providers of the product.
  • 85. 54 Part I: Understanding Goal-Directed Design Stakeholders’ perceptions of the user — Stakeholders who have relationships with users (such as customer support representatives) may have important insights on users that will help you to formulate your user research plan. You may also find that there are significant disconnects between some stakeholders’ per- ceptions of their users and what you discover in your research. This information can become an important discussion point with management later in the process. Understanding these issues and their impact on design solutions helps you as a designer to better develop a successful product. Regardless of how desirable your designs are to customers and users, without considering the viability and feasibility of the proposed solution there is no chance that the product will thrive. Discussing these topics is also important to developing a common language and understanding among the design team, management, and engineering teams. As a designer, your job is to develop a vision that the entire team believes in. Without taking the time to understand everyone’s perspective, it is unlikely that they will feel that proposed solutions reflect their priorities. Because these people have the responsibility and authority to deliver the product to the real world, they are guar- anteed to have important knowledge and opinions. If you don’t ask for it upfront, it is likely to be forced upon you later, often in the form of a critique of your pro- posed solutions. Subject matter expert (SME) interviews Early in a design project, it is often invaluable to identify and meet with several sub- ject matter experts (SMEs) — experts on the domain within which the product will operate. Many SMEs were users of the product or its predecessors at one time and may now be trainers, managers, or consultants. Often they are experts hired by stakeholders, rather than stakeholders themselves. Similar to stakeholders, SMEs can provide valuable perspectives on a product and its users, but designers should be careful to recognize that SMEs represent a somewhat skewed perspective. Some points to consider about using SMEs are: SMEs are often expert users. Their long experience with a product or its domain means that they may have grown accustomed to current interactions. They may also lean towards expert controls rather than interactions designed for perpetual intermediates. SMEs are often not current users of the product and may have more of a management perspective. SMEs are knowledgeable, but they aren’t designers. They may have many ideas on how to improve a product. Some of these may be valid and valuable, but the most useful pieces of information to glean from these suggestions are the causative problems that lead to their proposed solutions. As with users, when you encounter a proposed solution, ask “how would that help you or the user?”
  • 86. Chapter 4: Understanding Users: Qualitative Research 55 SMEs are necessary in complex or specialized domains. If you are designing for a technical domain such as medical, scientific, or financial services, you will likely need some guidance from SMEs, unless you are one yourself. Use SMEs to get information on industry best practices and complex regulations. SME knowledge of user roles and characteristics is critical for planning user research in complex domains. You will want access to SMEs throughout the design process. If your product domain requires use of SMEs, you should be able to bring them in at different stages of the design to help perform reality checks on design details. Make sure that you secure this access in your early interviews. Customer interviews It is easy to confuse users with customers. For consumer products, customers are often the same as users, but in corporate or technical domains, users and customers rarely describe the same sets of people. Although both groups should be inter- viewed, each has its own perspective on the product that needs to be factored quite differently into an eventual design. Customers of a product are those people who make the decision to purchase it. For consumer products, customers are frequently users of the product; although for prod- ucts aimed at children or teens, the customers are parents or other adult supervisors of children. In the case of most enterprise, medical, or technical products, the customer is someone very different from the user — often an executive or IT manager — with distinct goals and needs. It’s important to understand customers and satisfy their goals in order to make a product viable. It is also important to realize that customers seldom actually use the product themselves, and when they do, they use it quite differently from the way their users do. When interviewing customers, you will want to understand: Their goals in purchasing the product Their frustrations with current solutions Their decision process for purchasing a product of the type you’re designing Their role in installation, maintenance, and management of the product Domain-related issues and vocabulary Like SMEs, customers may have many opinions about how to improve the design of the product. It is important to analyze these suggestions, as in the case of SMEs, to determine what issues or problems underlie the ideas offered, because better, more integrated solutions may become evident later in the design process.
  • 87. 56 Part I: Understanding Goal-Directed Design User Interviews Users of a product should be the main focus of the design effort. They are the peo- ple who are personally utilizing the product to accomplish a goal (not their man- agers or support team). If you are redesigning or refining an existing product, it is important to speak to both current and potential users, that is, people who do not currently use the product but who are good candidates for using it in the future because they have needs that can be met with the product and are in the target mar- ket for the product. Interviewing both current and potential users illuminates the effect that experience with the current version of a product may have on how the user behaves and thinks about things. Information we are interested in learning from users includes: The context of how the product (or analogous system, if no current product exists) fits into their lives or workflow: when, why, and how the product is or will be used Domain knowledge from a user perspective: What do users need to know to do their jobs? Current tasks and activities: both those the current product is required to accom- plish and those it doesn’t support Goals and motivations for using their product Mental model: how users think about their jobs and activities, as well as what expectations users have about the product Problems and frustrations with current products (or an analogous system if no current product exists) User observation Most people are incapable of accurately assessing their own behaviors,2 especially when they are removed from the context of their activities. It is also true that out of fear of seeming dumb, incompetent, or impolite, many people may avoid talking about software behaviors that they find problematic or incomprehensible. It then follows that interviews performed outside the context of the situations the designer hopes to understand will yield less-complete and less-accurate data. You can talk to users about how they think they behave, or you can observe their behav- ior first-hand. The latter route provides superior results.
  • 88. Chapter 4: Understanding Users: Qualitative Research 57 Perhaps the most effective technique for gathering qualitative user data combines interviewing and observation, allowing the designers to ask clarifying questions and direct inquiries about situations and behaviors they observe in real time. Many usability professionals make use of technological aides such as audio or video recorders to capture what users say and do. Interviewers must take care not to make these technologies too obtrusive; otherwise, the users will be distracted and behave differently than they would off-tape. In our practice, we’ve found that a notebook and a camera allow us to capture everything we need without compromising the honest exchange of information. Typically, we won’t bring out the camera until we feel that we’ve established a good rapport with the interview subject, and then we use it to capture things about the environment that are difficult to jot in our notes. However, video, when used with care, can sometimes provide a powerful rhetorical tool for achieving stakeholder buy-in to contentious or surprising research results. Video may also prove useful in situations where note taking is dif- ficult, such as in a moving car. Literature review In parallel with stakeholder interviews, the design team should review any litera- ture pertaining to the product or its domain. This can and should include product marketing plans, brand strategy, market research, user surveys, technology specifi- cations and white papers, business and technical journal articles, competitive stud- ies, Web searches for related and competing products and news, usability study results and metrics, and customer support data such as call center statistics. The design team should collect this literature, use it as a basis for developing ques- tions to ask stakeholders and SMEs, and later use it to supply additional domain knowledge and vocabulary, and to check against compiled user data. Product and competitive audits Also in parallel to stakeholder and SME interviews, it is often quite helpful for the design team to examine any existing version or prototype of the product, as well as its chief competitors. Doing so gives the design team a sense of the state of the art, and provides fuel for questions during the interviews. The design team, ideally, should engage in an informal heuristic or expert review of both the current and competitive interfaces, comparing each against interaction and visual design prin- ciples (such as those found later in this book). This procedure both familiarizes the team with the strengths and limitations of what is currently available to users, and provides a general idea of the current functional scope of the product.
  • 89. 58 Part I: Understanding Goal-Directed Design Ethnographic Interviews: Interviewing and Observing Users Drawing on years of design research in practice, we believe that a combination of observation and one-on-one interviews is the most effective and efficient tool in a designer’s arsenal for gathering qualitative data about users and their goals. The technique of ethnographic interviews is a combination of immersive observation and directed interview techniques. Hugh Beyer and Karen Holtzblatt have pioneered an ethnographic interviewing technique that they call contextual inquiry. Their method has, for good reason, rapidly gained traction in the industry, and provides a sound basis for qualitative user research. It is described in detail in the first four chapters of their book, Con- textual Design. Contextual inquiry methods closely parallel the methods described here, but with some subtle and important differences. Contextual inquiry Contextual inquiry, according to Beyer and Holtzblatt, is based on a master- apprentice model of learning: observing and asking questions of the user as if she is the master craftsman, and the interviewer the new apprentice. Beyer and Holtzblatt also enumerate four basic principles for engaging in ethnographic interviews: Context — Rather than interviewing the user in a clean white room, it is impor- tant to interact with and observe the user in her normal work environment, or whatever physical context is appropriate for the product. Observing users as they perform activities and questioning them in their own environments, filled with the artifacts they use each day, can bring the all-important details of their behaviors to light. Partnership — The interview and observation should take the tone of a collabo- rative exploration with the user, alternating between observation of work and discussion of its structure and details. Interpretation — Much of the work of the designer is reading between the lines of facts gathered about users’ behaviors, their environment, and what they say. These facts must be taken together as a whole and analyzed by the designer to uncover the design implications. Interviewers must be careful, however, to avoid assumptions based on their own interpretation of the facts without verifying these assumptions with users.
  • 90. Chapter 4: Understanding Users: Qualitative Research 59 Focus — Rather than coming to interviews with a set questionnaire or letting the interview wander aimlessly, the designer needs to subtly direct the interview so as to capture data relevant to design issues. Improving on contextual inquiry Contextual inquiry forms a solid theoretical foundation for qualitative research, but as a specific method it has some limitations and inefficiencies. The following process improvements, in our experience, result in a more highly leveraged research phase that better sets the stage for successful design: Shorten the interview process — Contextual inquiry assumes full-day interviews with users. The authors have found that interviews as short as one hour can be sufficient to gather the necessary user data, provided that a sufficient number of interviews (about six well-selected users for each hypothesized role or type) are scheduled. It is much easier and more effective to find a diverse set of users who will consent to an hour with a designer than it is to find users who will agree to spend an entire day. Use smaller design teams — Contextual inquiry assumes a large design team that conducts multiple interviews in parallel, followed by debriefing sessions in which the full team participates. We’ve found that it is more effective to conduct interviews sequentially with the same designers in each interview. This allows the design team to remain small (two or three designers), but even more important, it means that the entire team interacts with all interviewed users directly, allowing the members to most effectively analyze and synthesize the user data. Identify goals first — Contextual inquiry, as described by Beyer and Holtzblatt, feeds a design process that is fundamentally task focused. We propose that ethnographic interviews first identify and prioritize user goals before determining the tasks that relate to these goals. Looking beyond business contexts — The vocabulary of contextual inquiry assumes a business product and a corporate environment. Ethnographic inter- views are also possible in consumer domains, though the focus of questioning is somewhat different, as we describe later in this chapter. The remainder of this chapter provides general methods and tips for preparing for and conducting ethnographic interviews. Preparing for ethnographic interviews Ethnography is a term borrowed from anthropology, meaning the systematic and immersive study of human cultures. In anthropology, ethnographic researchers
  • 91. 60 Part I: Understanding Goal-Directed Design spend years living immersed in the cultures they study and record. Ethnographic interviews take the spirit of this type of research and apply it on a micro level. Rather than trying to understand behaviors and social rituals of an entire culture, the goal is to understand the behaviors and rituals of people interacting with indi- vidual products. Identifying candidates Because the designers must capture an entire range of user behaviors regarding a product, it is critical that the designers identify an appropriately diverse sample of users and user types when planning a series of interviews. Based on information gleaned from stakeholders, SMEs, and literature reviews, designers need to create a hypothesis that serves as a starting point in determining what sorts of users and potential users to interview. The persona hypothesis We label this starting point the persona hypothesis, because it is the first step towards identifying and synthesizing personas, the user archetypes we will discuss in detail in the next chapter. The persona hypothesis should be based on likely behavior patterns and the factors that differentiate these patterns, not purely on demographics. It is often the case with consumer products that demographics are used as screening criteria to select interview subjects, but even in this case, they should be serving as a proxy for a hypothesized behavior pattern. The nature of a product’s domain makes a significant difference in how a persona hypothesis is constructed. Business users are often quite different from consumer users in their behavior patterns and motivations, and different techniques are used to build the persona hypothesis in each case. The persona hypothesis is a first cut at defining the different kinds of users (and sometimes customers) for a product. The hypothesis serves as the basis for initial interview planning; as interviews proceed, new interviews may be required if the data indicates the existence of user types not originally identified. The persona hypothesis attempts to address, at a high level, these three questions: What different sorts of people might use this product? How might their needs and behaviors vary? What ranges of behavior and types of environments need to be explored?
  • 92. Chapter 4: Understanding Users: Qualitative Research 61 Roles in business and consumer domains For business products, roles — common sets of tasks and information needs related to distinct classes of users — provide an important initial organizing prin- ciple. For example, for an office phone system, we might find these rough roles: People who make and receive calls from their desks People who travel a lot and need to access the phone system remotely Receptionists who answer the phone for many people People who technically administer the phone system In business and technical contexts, roles often map roughly to job descriptions, so it is relatively easy to get a reasonable first cut of user types to interview by under- standing the kind of jobs held by users (or potential users) of the system. Unlike business users, consumers don’t have concrete job descriptions, and their use of products may cross multiple contexts. Therefore, it often isn’t meaningful to use roles as an organizing principle for the persona hypothesis for a consumer product. Rather, it is often the case that you will see the most significant patterns emerge from users’ attitudes and aptitudes, as manifest in their behaviors. Behavioral and demographic variables In addition to roles, a persona hypothesis should be based on variables that help differentiate between different kinds of users based on their needs and behaviors. This is often the most useful way to distinguish between different types of users (and forms the basis for the persona-creation process described in the next chap- ter). Despite the fact that these variables can be difficult to fully anticipate without research, they often become the basis of the persona hypothesis for consumer prod- ucts. For example, for an online store, there are several ranges of behavior concern- ing shopping that we might identify: Frequency of shopping (from frequent to infrequent) Desire to shop (from loves to shop to hates to shop) Motivation to shop (from bargain hunting to searching for just the right item) Although consumer user types can often be roughly defined by the combination of behavioral variables they map to, behavioral variables are also important for iden- tifying types of business and technical users. People within a single business-role definition may have different needs and motivations. Behavioral variables can cap- ture this, although often not until user data has been gathered.
  • 93. 62 Part I: Understanding Goal-Directed Design Given the difficulty in accurately anticipating behavioral variables before user data is gathered, another helpful approach in building a persona hypothesis is making use of demographic variables. When planning your interviews, you can use market research to identify ages, locations, gender, and incomes of the target markets for the product. Interviewees should be distributed across these demographic ranges in the hope of interviewing a sufficiently diverse group of people to identify the sig- nificant behavior patterns. Domain expertise versus technical expertise One important type of behavioral distinction is the difference between technical expertise (knowledge of digital technology) and domain expertise (knowledge of a specialized subject area pertaining to a product). Different users will have varying amounts of technical expertise; similarly, some users of a product may be less expert in their knowledge of the product’s domain (for example, accounting knowledge in the case of a general ledger application). Thus, depending on who the design target of the product is, domain support may be a necessary part of the product’s design, as well as technical ease of use. A relatively naive user will likely never be able to use more than a small subset of a domain-specific product’s func- tions without domain support provided in the interface. If naive users are part of the target market for a domain-specific product, care must be taken to support domain-naive behaviors. Environmental considerations A final consideration, especially in the case of business products, is the cultural dif- ferences between organizations in which the users are employed. At small compa- nies, for example, workers tend to have a broader set of responsibilities and more interpersonal contact; at huge companies, workers tend to be highly specialized and there are often multiple layers of bureaucracy. Examples of these environmental variables include: Company size (from small to multinational) Company location (North America, Europe, Asia, and so on) Industry/sector (electronics manufacturing, consumer packaged goods, and so on) IT presence (from ad hoc to draconian) Security level (from lax to tight) Like behavioral variables, these may be difficult to identify without some domain research, because patterns do vary significantly by industry and geographic region.
  • 94. Chapter 4: Understanding Users: Qualitative Research 63 Putting a plan together After you have created a persona hypothesis, complete with potential roles and behavioral, demographic, and environmental variables, you then need to create an interview plan that can be communicated to the person in charge of coordinating and scheduling the interviews. In our practice, we’ve observed that each presumed behavioral pattern requires about a half-dozen interviews to verify or refute (sometimes more if a domain is particularly complex). What this means in practice is that each identified role, behavioral variable, demographic variable, and environmental variable identified in the persona hypothesis should be explored in four to six interviews (sometimes more if a domain is particularly complex). However, these interviews can overlap. If we believe that use of an enterprise prod- uct may differ, for example, by geographic location, industry, and company size, then research at a single small electronics manufacturer in Taiwan would allow us to cover several variables at once. By being clever about mapping variables to inter- viewee-screening profiles, you can keep the number of interviews to a manageable number. Conducting ethnographic interviews After the persona hypothesis has been formulated and an interview plan has been derived from it, you are ready to interview — assuming you get access to inter- viewees! While formulating the interview plan, designers should work closely with project stakeholders who have access to users. Stakeholder involvement is gen- erally the best way to make interviews happen, especially for business and technical products. If stakeholders can’t help you get in touch with users, you can contact a market or usability research firm that specializes in finding people for surveys and focus groups. These firms are useful for reaching consumers with diverse demographics. The difficulty with this approach is that it can sometimes be challenging to get interviewees who will permit you to interview them in their homes or places of work. As a last alternative for consumer products, designers can recruit friends and rela- tives. This makes it easier to observe the interviewees in a natural environment but also is quite limiting as far as diversity of demographic and behavioral variables are concerned.
  • 95. 64 Part I: Understanding Goal-Directed Design Interview teams and timing The authors favor a team of two designers per interview, one to drive the interview and take light notes, and the other to take detailed notes (these roles can switch halfway through the interview). One hour per user interviewed is often sufficient, except in the case of highly complex domains such as medical, scientific, and finan- cial services that may require more time to fully understand what the user is trying to accomplish. Be sure to budget travel time between interview sites, especially for consumer interviews in residential neighborhoods, or interviews that involve “shadowing” users as they interact with a (usually mobile) product while moving from place to place. Teams should try to limit interviews to six per day, so that there is adequate time for debriefing and strategizing between interviews, and so that the interviewers do not get fatigued. Phases of ethnographic interviews A complete set of ethnographic interviews for a project can be grouped into three distinct, chronological phases. The approach of the interviews in each successive phase is subtly different from the previous one, reflecting the growing knowledge of user behaviors that results from each additional interview. Focus tends to be broad at the start, aimed at gross structural and goal-oriented issues, and more narrow for interviews at the end of the cycle, zooming in on specific functions and task- oriented issues. Early interviews are exploratory in nature, and focused on gathering domain knowledge from the point of view of the user. Broad, open-ended questions are common, with a lesser degree of drill-down into details. Middle interviews are where designers begin to see patterns of use and ask open-ended and clarifying questions to help connect the dots. Questions in general are more focused on domain specifics, now that the designers have absorbed the basic rules, structures, and vocabularies of the domain. Later interviews confirm previously observed patterns, further clarifying user roles and behaviors and making fine adjustments to assumptions about task and information needs. Closed-ended questions are used in greater number, tying up loose ends in the data. After you have an idea who your actual interviewees will be, it can be useful to work with stakeholders to schedule individuals most appropriate for each phase in the interview cycle. For example, in a complex, technical domain it is often a good idea to perform early interviews with the more patient and articulate interview subjects. In some cases, you may also want to loop back and interview this particularly knowledgeable and articulate subject again at the end of the interview cycle to address any topics that you weren’t aware of during your initial interview.
  • 96. Chapter 4: Understanding Users: Qualitative Research 65 Basic methods The basic methods of ethnographic interviewing are simple, straightforward, and very low tech. Although the nuances of interviewing subjects takes some time to master, any practitioner should, if they follow the suggestions below, be rewarded with a wealth of useful qualitative data: Interview where the interaction happens Avoid a fixed set of questions Focus on goals first, tasks second Avoid making the user a designer Avoid discussions of technology Encourage storytelling Ask for a show and tell Avoid leading questions We describe each of these methods in more detail in the following sections. Interview where the interaction happens Following the first principle of contextual inquiry, it is of critical importance that subjects be interviewed in the places where they actually use the products. Not only does this give the interviewers the opportunity to witness the product being used, but it also gives the interview team access to the environment in which the interac- tion occurs. This can give tremendous insight into product constraints and user needs and goals. Observe the environment closely: It is likely to be crawling with clues about tasks the interviewee might not have mentioned. Notice, for example, the kind of infor- mation they need (papers on desks or adhesive notes on screen borders), inade- quate systems (cheat sheets and user manuals), the frequency and priority of tasks (inbox and outbox); and the kind of workflows they follow (memos, charts, calen- dars). Don’t snoop without permission, but if you see something that looks inter- esting, ask your interviewee to discuss it. Avoid a fixed set of questions If you approach ethnographic interviews with a fixed questionnaire, you not only run the risk of alienating the interview subject but can also cause the interviewers to miss out on a wealth of valuable user data. The entire premise of ethnographic interviews (and contextual inquiry) is that we as interviewers don’t know enough about the domain to presuppose the questions that need asking: We must learn what is important from the people we talk to. This said, it’s certainly useful to have
  • 97. 66 Part I: Understanding Goal-Directed Design types of questions in mind. Depending on the domain, it may also be useful to have a standardized set of topics that you want to make sure you cover in the course of your interview. This list of topics may evolve over the course of your interviews, but this will help you make sure that you get enough detail from each interview so that you are able to recognize the significant behavior patterns. Here are some goal-oriented questions to consider: Goals — What makes a good day? A bad day? Opportunity — What activities currently waste your time? Priorities — What is most important to you? Information — What helps you make decisions? Another useful type of question is the system-oriented question: Function — What are the most common things you do with the product? Frequency — What parts of the product do you use most? Preference — What are your favorite aspects of the product? What drives you crazy? Failure — How do you work around problems? Expertise — What shortcuts do you employ? For business products, workflow-oriented questions can be helpful: Process — What did you do when you first came in today? And after that? Occurrence and recurrence — How often do you do this? What things do you do weekly or monthly, but not every day? Exception — What constitutes a typical day? What would be an unusual event? To better understand user motivations, you can employ attitude-oriented questions: Aspiration — What do you see yourself doing five years from now? Avoidance — What would you prefer not to do? What do you procrastinate on? Motivation — What do you enjoy most about your job (or lifestyle)? What do you always tackle first? Focus on goals first, tasks second Unlike contextual inquiry and the majority of other qualitative research methods, the first priority of ethnographic interviewing is understanding the why of users — what
  • 98. Chapter 4: Understanding Users: Qualitative Research 67 motivates the behaviors of individuals in different roles, and how they hope to ulti- mately accomplish this goal — not the what of the tasks they perform. Understand- ing the tasks is important, and the tasks must be diligently recorded. But these tasks will ultimately be restructured to better match user goals in the final design. Avoid making the user a designer Guide the interviewee towards examining problems and away from expressing solutions. Most of the time, those solutions reflect the interview subject’s personal priorities, and while they sound good to him, they tend to be shortsighted, idiosyn- cratic, and lack the balance and refinement that an interaction designer can bring to a solution based upon adequate research and years of experience. That said, a proposed design solution can be a useful jumping off point to discuss a user’s goals and the problems they encounter with current systems. If a user blurts out an inter- esting idea, ask “What problem would that solve for you?” or “Why would that be a good solution?” Avoid discussions of technology Just as you don’t want to treat the user as a designer, you also don’t want to treat him as a programmer or engineer. Discussion of technology is meaningless without first understanding the purpose underlying any technical decisions. In the case of technical or scientific products, where technology is always an issue, distinguish between domain-related technology and product-related technology, and steer away from the latter. If an interview subject is particularly insistent on talking about how the product should be implemented, bring the subject back to his goals and motivations by asking “How would that help you?” Encourage storytelling Far more useful than asking users for design advice is encouraging them to tell spe- cific stories about their experiences with a product (whether an old version of the one you’re redesigning, or an analogous product or process): how they use it, what they think of it, who else they interact with when using it, where they go with it, and so forth. Detailed stories of this kind are usually the best way to understand how users relate to and interact with products. Encourage stories that deal with typical cases and also more exceptional ones. Ask for a show and tell After you have a good idea of the flow and structure of a user’s activities and inter- actions and you have exhausted other questions, it is often useful to ask the inter- viewee for a show and tell or grand tour of artifacts related to the design problem. These can be domain-related artifacts, software interfaces, paper systems, tours of the work environment, or ideally all the above. Be careful to not only record the
  • 99. 68 Part I: Understanding Goal-Directed Design artifacts themselves (digital or video cameras are very handy at this stage) but also pay attention to how the interviewee describes them. Be sure to ask plenty of clari- fying questions as well. Avoid leading questions One important thing to avoid in interviews is the use of leading questions. Just as in a courtroom, where lawyers can, by virtue of their authority, bias witnesses by suggesting answers to them, designers can inadvertently bias interview subjects by implicitly (or explicitly) suggesting solutions or opinions about behaviors. Examples of leading questions include: Would feature X help you? You like X, don’t you? Do you think you’d use X if it were available? After the interviews After each interview, teams compare notes and discuss any particularly interesting trends observed or specific points brought up in the most recent interview. If they have the time, they should also look back at old notes to see whether unanswered questions from other interviews and research have been properly answered. This information should be used to strategize about the approach to take in subsequent interviews. After the interview process is finished, it is useful to once again make a pass through all the notes, marking or highlighting trends and patterns in the data. This is very useful for the next step of creating personas from the cumulative research. If it is helpful, the team can create a binder of the notes, review any videotapes, and print out artifact images to place in the binder or on a public surface, such as a wall, where they are all visible simultaneously. This will be useful in later design phases. Other Types of Research This chapter has focused on qualitative research aimed at gathering user data that will later be used to construct robust user and domain models that form the key tools in the Goal-Directed Design methodology described in the next chapter. A wide variety of other forms of research are used by design and usability profession- als, ranging from detailed task analysis activities to focus groups and usability tests. While many of these activities have the potential to contribute to the creation of useful and desirable products, we have found the qualitative approach described in this chapter to provide the most value to digital product design. Put simply, the
  • 100. Chapter 4: Understanding Users: Qualitative Research 69 qualitative approach helps answer questions about the product at both the big-pic- ture and functional-detail level with a relatively small amount of effort and expense. No other research technique can claim this. Mike Kuniavsky’s book Observing the User Experience is an excellent resource that describes a wide range of user research methods for use at many points in the design and development process. In the remainder of this chapter, we discuss just a few of the more prominent research methods and how they fit into the overall development effort. Focus groups Marketing organizations are particularly fond of gathering user data via focus groups, in which representative users, usually chosen to match previously identi- fied demographic segments of the target market, are gathered together in a room and asked a structured set of questions and provided a structured set of choices. Often, the meeting is recorded on audio or video media for later reference. Focus groups are a standard technique in traditional product marketing. They are useful for gauging initial reactions to the form of a product, its visual appearance, or industrial design. Focus groups can also gather reactions to a product that the respondents have been using for some time. Although focus groups may appear to provide the requisite user contact, the method is in many ways not appropriate as a design tool. Focus groups excel at elic- iting information about products that people own or are willing (or unwilling) to purchase but are weak at gathering data about what people actually do with those products, or how and why they do it. Also, because they are a group activity, focus groups tend to drive to consensus. The majority or loudest opinion often becomes the group opinion. This is anathema to the design process, where designers must understand all the different patterns of behavior a product must address. Focus groups tend to stifle exactly the diversity of behavior and opinion that designers must accommodate. Market demographics and market segments The marketing profession has taken much of the guesswork out of determining what motivates people to buy. One of the most powerful tools for doing so is mar- ket segmentation, which typically uses data from focus groups and market surveys to group potential customers by demographic criteria (such as age, gender, educa- tional level, and home zip code) to determine what types of consumers will be most receptive to a particular product or marketing message. More sophisticated
  • 101. 70 Part I: Understanding Goal-Directed Design consumer data also include psychographics and behavioral variables, including attitudes, lifestyle, values, ideology, risk aversion, and decision-making patterns. Classification systems such as SRI’s VALS segmentation and Jonathan Robbin’s geodemographic PRIZM clusters can add greater clarity to the data by predicting consumers’ purchasing power, motivation, self-orientation, and resources. These market-modeling techniques are able to accurately forecast marketplace acceptance of products and services. They are an invaluable tool in assessing the viability of a product. They can also be powerful tools for convincing executives to build a product. After all, if you know X people might buy a product or service for Y dollars, it is easy to evaluate the potential return on investment. However, understanding whether somebody wants to buy something is not the same thing as actually defining the product. Market segmentation is a great tool for identifying and quantifying a market opportunity, but an ineffective tool for defin- ing a product that will capitalize on that opportunity. It turns out, however, that data gathered via market research and that gathered via qualitative user research complement each other quite well. Because market research can help identify an opportunity, it is often the necessary starting point for a design initiative. Without assessing the opportunity, you will be hard pressed to convince a businessperson to fund the design. Also, as already discussed, ethno- graphic interviewers should use market research to help them select interview tar- gets, and finally, as the video-editing story earlier in this chapter illustrates, qualitative research can shed critical light on the results of quantitative studies. We will discuss the differences between segmentation models and user models in more detail in Chapter 5. Usability and user testing Usability testing (also known, somewhat unfortunately, as “user testing”) is a col- lection of techniques used to measure characteristics of a user’s interaction with a product, usually with the goal of assessing the usability of that product. Typically, usability testing is focused on measuring how well users can complete specific, standardized tasks, as well as what problems they encounter in doing so. Results often reveal areas where users have problems understanding and utilizing the prod- uct, as well as places where users are more likely to be successful. Usability testing requires a fairly complete and coherent design artifact to test against. Whether you are testing production software, a clickable prototype, or even a paper prototype, the point of the test is to validate a product design. This means that the appropriate place for usability testing is quite late in the design cycle, after
  • 102. Chapter 4: Understanding Users: Qualitative Research 71 there is a coherent concept and sufficient detail to generate such prototypes. We discuss evaluative usability testing as part of design refinement in Chapter 7. A case could certainly be made for the appropriateness of usability testing at the beginning of a redesign effort, and the technique is certainly capable of finding opportunities for improvement in such a project. However, we find that we are able to assess major inadequacies of a product through our qualitative studies, and if the budget is limited so as to allow usability testing only once in a product design ini- tiative, we find much more value in performing the tests after we have a candidate solution, as a means of testing the specific elements of the new design. Because the findings of user testing are generally measurable and quantitative, usability research is especially useful in comparing specific design variants to choose the most effective solution. Customer feedback gathered from usability test- ing is most useful when you need to validate or refine particular interaction mech- anisms or the form and expression of specific design elements. Usability testing is especially effective at determining: Naming — Do section/button labels make sense? Do certain words resonate better than others do? Organization — Is information grouped into meaningful categories? Are items located in the places customers might look for them? First-time use and discoverability — Are common items easy for new users to find? Are instructions clear?