Design to Refine: Developing a tunable information architecture

Design to ReﬁneDeveloping a tunable information architectureLou Rosenfeld • Rosenfeld Media • rosenfeldmedia.com London • 14 April 2011

Hello, my name is Lou

Agenda1. The quick intro2. Prioritizing and tuning top-down navigation3. Demo: content modeling4. Prioritizing and tuning contextual navigation5. Group exercise: site search analytics6. Prioritizing and tuning search7. Changing your work and your organization

I’ve already dissed redesignSee the slides here:http://www.slideshare.net/lrosenfeld/

The alternatives to redesign1. Prioritize: Identify the important problems regularly2. Tune: Address those problems regularly3. Be opportunistic: Look for low-hanging fruit

Prioritize becausea little goes a long way

A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most

A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most LOVE IT

A handful of your queries/ways to navigate/documents meet A little data goes a long waythe needs of the few audiences that use your site most LOVE IT LEAVE IT

Zipf in text

Report card for essential wants and needs

Be an incrementalist:tune because things change

From projects to processes:a regular regimen of design Example: the rolling content inventory

Impact of change on design(queries)

Be an opportunist:look for the low-hanging fruit1. Top-down navigation: Anticipates interests/questions at arrival2. Bottom-up (contextual) navigation: Enables answers to emerge3. Search: Handles speciﬁc information needs

Life by a thousand cuts 50% of users are search dominantx 5% of all queries are typos, fixed by spell checking. 2.5% improvement to the UX 50% of all users are search dominantx 30% (best bet results for top 100 queries) 15% improvement to the UXDitto for improving content, search results design,navigation design…

Summary You can reﬁne 1. Prioritize the problems that are most important to your users 2. Regularly address these problems 3. Identify opportunities to make small improvements that go a long way

Prioritizing and TuningTop-Down Navigation

The data-driven main page:Who wants what and when?

Who wants what?US English speakers

Who wants what?German speakers

When do they want it?

Commerce sites get it

The IRS gets it

But really, who caresabout the main page?

The risk of main page ﬁxationFrom Tony Dunn’s Tales from Redesignland(http://redesignland.blogspot.com/)

Focusing on main page =taking Zipf too far...plus lots of competition (Google, ads/landing pages)

The tail that wags the dog:site map drivesimproved site hierarchy

Site map by tool, unit, and format

User-centered site mapUser-centered site map...

Asking the possiblefrom your site index

Specialized site indices

Specialized site indices Cisco’s site indices are specialized by content type (products, services)

Best bet-based site indices MSU’s site index is built on popular information needs (based on best bet search results)

Going broad and deep withguides (AKA microsites)

Vanguard’s main page lovesguides

The Tax Center is a guide

One more example: IRS

...e-ﬁling is presented assequential steps

Summary: Top-down navigation Prioritize main page content and layout 1. Confuse as necessary by diverting attention 2. Counter politics with data; e.g., use seasonality to drive design Tune and prioritize site-wide navigation 3. Use the site map as a skunkworks for site-wide hierarchy 4. Base site indices on specialized content or popular information needs (e.g., best bets) 5. Use guides (micro-sites) as narrow/deep complement to broad/shallow navigation schemes

concert calendar album pages artist descriptions TV listings Demonstration: Content Modelingalbum reviews discography artist bios

What are the common content objects in your site? album pages artist bios artist descriptions album reviews 53

How do they ﬁt together? concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios

What content objects are missing? concert calendar And how do they ﬁt? album pages artist descriptions TV listingsalbum reviews discography artist bios

Where do you start? concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios

How will you connect those objects?

Use content modelsfor content that’s... Homogeneous High-volume High importance What’s the most important deep content in your site?

Use content modelswhen you need to... Incorporate user research into your deep content Improve contextual navigation Identify missing content Prioritize metadata choices Really beneﬁt from your CMS

Steps for developingcontent models1. Determine key audiences (who’s using it?)2. Select important tasks to test (what are they using it for?)3. Determine important content areas (what do they want?)4. Determine content types (what are they using?)5. Determine metadata attributes (how will we connect the objects?)6. Determine contextual linking rules (where should the objects lead us to next?)

Prioritizing and TuningContextual Navigation

Establishing Desire LinesUse Content modeling • Site search analytics

Where do searches begin?Not just the mainpage, according to aUser InterfaceEngineering study(http://is.gd/j1NHeS)

Using site search analyticsto identify desire lines

Choose acommon contenttype (e.g., events) !Where should !users go from here? !

! ! ! ! ! !Analyze frequent queries generated from each content sample

! ! !Can you type these queries to improve yourcontent model?Link events to:• the site’s articles on the event’s topic• info on locales for each event

What content typesshould we be connecting?

Important content types emerge from content modeling concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios

Using SSA to prioritize contenttypes

Getting content types out ofsite search analytics Take an hour to... • Analyze top 50 queries (20% of all search activity) • Ask and iterate: “what kind of content would users be looking for when they searched these terms?” • Add cumulative percentages Result: prioritized list of potential content types #1) application: 11.77% #2) reference: 10.5% #3) instructions: 8.6% #4) main/navigation pages: 5.91% #5) contact info: 5.79% #6) news/announcements: 4.27%

What should we use toconnect content types?

Which metadata attributes will yourcontent model depend upon?

More on prioritizing metadata attributes

Prioritizing semantic relationships

How do weprioritize content?

Some content value variables I

Some content value variables I UsabilityPopularityCredibility

Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility

Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility Strategic value Addresses compliance issues (e.g., Sarbanes/Oxley) Content owners are good partners

Subjectively “grade” your content’s value1.Choose appropriatevalue criteria for eachcontent area2.Weight criteria (total= 100%)3.Subjectively grade foreach criterion4.weight x grade =score5.Add scores foroverall score

Subjectively “grade” your content’s value Subjective assessment1.Choose appropriatevalue criteria for eachcontent area2.Weight criteria (total= 100%)3.Subjectively grade foreach criterion4.weight x grade =score5.Add scores foroverall score

Put the grades together for a moreobjective “report card” Helps prioritize content migrations, refreshes, ...

Put the grades together for a moreobjective “report card” Objectiﬁes subjective assessments Helps prioritize content migrations, refreshes, ...

Summary:contextual navigation Use content modeling and site search analytics to 1. Identify and prioritize content types 2. Identify desire lines 3. Improve contextual navigation between content types 4. Identify and prioritize metadata attributes Prioritize content areas/subsites by establishing balanced value criteria

Group exercise:Site search analytics

Prioritizing and Tuning Search

Make “the Box” accommodatemost searchers’ queries

How long are our queries? Top 500 queries (37% of all trafﬁc)

Mean = 10.6 charactersMedian = 10 characters

Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longer

Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20s !

Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? !

Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? !Safe: @15-20 characters

We’ve seen this before:auto-completing queries

Auto-completing from aknown, common items (e.g.,

Auto-completing from aknown, common items (e.g., Uses known terms: e.g., movie titles and actor/director names

Auto-completing from queries

Uses common queriesAuto-completing from queries

Auto-completing from bestbets

Auto-completing from bestbets Uses best bets

Making change easy:supporting query reﬁnement

The absolutemeaninglessness ofadvanced search

The absolute meaninglessness of advanced search !At University of Alaska-Fairbanks,advanced = expanded search

The absolute meaninglessness of advanced search !At University of Alaska-Fairbanks,advanced = expanded search At the IRS, advanced = narrowed search !

Contextualizing “advanced” features

Look to session data forprogression and context

Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works

Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works search session patterns 1. solar energy 2. energy

Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns 1. solar energy 2. energy

Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy

Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy search session patterns 1. solar energy 2. solar energy news

Improving performance forspecialized queries

Recognizing proper nouns,dates, and unique ID#s

Surfacingspecialized content typesin search results

Tuning Search Results:Handling specialized answers

Tuning Search Results: Handling specialized answers“Product quick links” come directly from product content modelThese results are a strong counterbalance to raw results

When raw isn’t good enough:best bet search results

best bet #1

best bet #1best bet #2

best bet #1best bet #2even more best bets

best bet #1best bet #2even more best betsraw results

best bet #1 best bet #2 even more best betscompetition raw results

best bet #1 best bet #2 even more best betscompetition danger? raw results

best bet #1 best bet #2 even more best betscompetition danger? data raw results

The 0 search results page:search’s equivalent of the 404

Tuning Search Results: 0 results pagesNot helpful

Tuning Search Results: 0 results pagesNot helpfulMuch better: “Did youmean?” and Popular Searches

Summary: Search systems Tune query entry 1. Make “The Box” wide enough 2. Support query auto-completion to focus queries 3. Surface the right features to support query reﬁnement 4. Recognize and take advantage of specialized queries Tune search results design 5. Surface specialized content types as results for specialized queries 6. Complement raw results with best bets 7. Enable recovery from ﬁnding 0 search results

Changing your workand your organization

Doing your work differently1. Processes, not projects2. Rebalancing your research and design

From time-boxed projectsto ongoing processes Example: the rolling content inventory

What else can roll?Most everything Each week, for example... • Content scouting and sampling (rather than inventory) • Analyze analytics to identify spikes, new trends Each month... • Identify new tasks, run new task analysis studies • Develop new best bet search results Each quarter... • Field study • Review and tune personas

Build a practice that’sbalanced and data-driven

User Research Landscapefrom Christian Rohrer: http://is.gd/95HSQ2

User Research Landscape Ongoing coverage of each of these 4 quadrantsfrom Christian Rohrer: http://is.gd/95HSQ2

Lou’s TABLE OFOVERGENERALIZED Web Analytics User Experience DICHOTOMIES Users intentions and What they Users behaviors (whats motives (why those things analyze happening) happen) Qualitative methods for What methods Quantitative methods to explaining why things they employ determine whats happening happen Helps users achieve goals What theyre Helps the organization meet (expressed as tasks ortrying to achieve goals (expressed as KPI) topics of interest) Uncover patterns and How they use Measure performance (goal- surprises (emergent data driven analysis) analysis) Statistical data ("real" data Descriptive data (in smallWhat kind of data in large volumes, full of volumes, generated in lab they use errors) environment, full of errors)

Getting your organizationto support your work1. Making friends and allies2. Changing your leaders’ minds

Making friends and allies

Showing content ownershow their content performs

Helping marketingdevelop better messagingJargon vs. Plain Language at Washtenaw Community College • Online courses were marketed using terms “College on Demand” (“COD”) and “FlexEd”; signup rates were poor • Compare jargon with “online” (used in 213 other queries) • Content was retitled rather than re-marketed

Helping IT say “no” with authorityReduce pressure to solve problems with technologies by making what we have workMinimize radical changes to platforms • Enterprise search • Content management systems • Analytics applications • ...

Changing leaders’ minds

Talking pointsfor reﬁning, against redesigning 1. Solve the problem(s) 2. Save money 3. Reduce/end radical organizational changes

Solving the problem(s)• Forcing the issue: ban the term “redesign” from discussions• Data-driven deﬁnition / prioritization / tuning / opportunism• Creating anchors to keep project from spinning out of control: elevator pitch / mission / vision / goals / KPI

This can be very, very helpful Gamestorming by Dave Gray, Sunni Brown, and James Macanufo (O’Reilly, 2010)

Saving money• Life by a thousand cuts: small changes have huge impacts (see: Zipf)• Reuse and retain technology investments• Retain institutional knowledge• Get more from your (empowered) team and make it pay for itself• Spend less on external support and ﬁre your agency

Reduce/end radicalorganizational changes• End the pendulum swing from centralized to decentralized approaches• Reorganize information, not people• Build self-sustaining, steady in-house capabilities to prioritize and tune

Being prepared to fail

Sometimes your leadersare in a hurry

Sometimes your leadersare not very smart

Sometimes your organizationis immature

Nurit Peres’ Company UX Maturity Model(http://is.gd/x1dOuP)

Renato Feijó’s UX Maturity Model(http://is.gd/dul2t2)

Always be ready to gounder the radar

Summary: changing your workand your organization Do your work differently 1. Move from time-based projects to ongoing processes 2. Build a balanced, data-driven practice Get your organization to support your work 3. Make friends and allies 4. Change leaders’ minds by • Solving problems • Saving money • Reducing radical change Be prepared to fail

Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedia.com | @rosenfeldmedia

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Design to Refine: Developing a tunable information architecture

by Louis Rosenfeld

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