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    fotos fotos Presentation Transcript

    • MindCanvas: Reimagining online research Rashmi Sinha Uzanto www.uzanto.com www.themindcanvas.com
    • Duct-tape research! (in the trenches - Information Architecture Redesign of eBay.com)
    • Background to IA redesign
      • eBay.com has grown in organic fashion – inconsistent, fractured user experience
        • Separate design / usability efforts for parts of eBay
          • first effort to focus on user experience for entire site
      • Basic eBay facts
        • World’s largest online marketplace (79 million in US)
        • Types of users
          • Buyers & sellers
          • New & experienced
          • Individuals & corporations
          • Different countries & cultures
    • Challenges
      • New IA would need to
        • Serve diverse user group
          • varying goals / mental models
        • Be future-oriented, allow for change & growth
        • Changes needed to be evolutionary not revolutionary
          • accommodate users familiar with current site
      • Senior management at eBay needed proof
        • Is there need for such drastic restructuring?
      • Research to be completed in 6 weeks!
    • Goals of research
      • Research has multiple goals
        • Need successful design, not just good design
          • Serves user
          • Satisfies business goals
          • Is accepted by management
      • 3-stage research method
          • Stages: Exploration  Understanding  Verification
          • Stages complement & build upon each other
      • Mix of qualitative & quantitative methods
          • Qualitative: rich, open-ended understanding of users / domain
          • Quantitative: recommendations grounded in data (help make case to management)
    • 3-stage user research Stage 1: Explore Interviews, free-listing Stage 3: Verify / Refine Large-sample closed card-sorting 3 stages Stakeholders User thinking / categorization Preliminary IA Stage 2: Understand Open card-sorting Verify categorization Top-level categories Scope of content & functionality ebay.com Community Buy Sell Sub cat1 SubCat2 SubCat3 xx SubCat1 Subcat4 Subcat3 Subcat2 xx xx xxx SubCat3 SubCat5 SubCat4 SubCat6 SubCat4 xx xxx xx xxx xxx xxx SubCat4 SubCat5 SubCat1 SubCat2 xxx xx xx
    • Stage 1: Explore domain with Freelisting
      • Goals
        • Explore domain in open-ended fashion, map scope.
        • Generate list of current & “Horizon Tasks” (planned for future)
      • Method
        • Interviews & Freelisting
        • With eBay users, stakeholders & designers
      • Freelisting tasks (eBay is about tasks!)
        • What are all the tasks users can do on eBay.com
          • List an item, Pay for it
        • What else will users be able to do on eBay.com 2-5 years that they can’t do today?
      • Results: List of 100 representative tasks (25 Horizon)
    • Stage 2: Explore user categorizations
      • Goals:
        • Gain insight into user thinking about eBay
        • Identify top-level categories for ALL site content and functionality
      • Method: Interviews & Open card sorting
        • List of 100 tasks (including 20 Horizon Tasks).
        • 35 participants (including sellers & buyers; new and advanced users).
    • Identify top levels of hierarchy
      • Hierarchical Cluster analysis to generate aggregate user categorizations.
      • Separate analysis for 4 user groups
        • Identify inconsistencies in categorizations
        • Reconcile to create one scheme.
      • Result: Preliminary IA
        • 5 top-level categories accounting for all site content and functionality.
      Dendogram
    • Stage 3: Verify & refine scheme
      • Goals:
        • Verify 5-category scheme covers all of eBay.
          • What tasks/concepts don’t fit? Where do users expect this info?
        • Input from larger, more diverse set of users.
        • Establish method for future verification of IA.
          • and to generalize scheme to international eBays.
      • Method: closed card sorting
        • Large sample (~ 1,000) representing all eBay user types.
        • Study conducted using online survey.
          • Participants categorized tasks into one of categories (or selected Other if it didn’t belong)
      • Result
        • Site-map showing the structure for all main parts of the eBay.com
    • Sell - Before
    • Sell Hub - After
    • eBay redesigned successfully!
      • Three-stage methodology
        • Understand business context
        • Delineate user categorizations
        • Create IA blueprint
      • Deliverable: site-map with structure for main parts of eBay.com.
        • map used as blueprint of IA redesign (took 2 years).
        • Generalized to international eBays.
        • Positive business implications (ROI)!
        • Users did not protest!
      site.com Top Category 3 Top Category1 Top Category 2 Top Category 4 SubCat1 Sub cat1 SubCat2 xx SubCat3 xx xx SubCat2 SubCat3 SubCat5 xx xx xx xx SubCat1 Subcat4 Subcat3 Subcat2 xx xx xxx SubCat3 SubCat5 SubCat4 SubCat6 SubCat4 xxx xx xx xxx xx xxx xxx xxx SubCat7 SubCat4 SubCat5 SubCat6 SubCat1 SubCat2 xx xx xxx xx xxx xx xx SubCat4 xx Preliminary IA
    • Duct-tape research! There has to be a better way - fast, cheap (relatively) & online…
    • Why we built MindCanvas
      • Qualitative research is great, takes a lot of time
      • Online tools suck, get used anyway (users not engaged)
      • Business stakeholders respond to quantitative analysis & large sample sizes
      • Deliverables do not cater to designers
      • Research findings remain locked up with analyst
    • Inspiration
      • Luis Von Ahn’s ESP Game
        • Rely on games to label the web
      • PopCap Games
        • Quick, short, engaging games
      • Visualization research
        • bringing statistics to designers
    •  
    • back to the future! MindCanvas interpretation
    • What is MindCanvas? Remote research methods Statistical Analysis & Data Mining Interactive Visualizations loosely coupled, use as qualitative or quantitative
    • Game-like elicitation methods
      • Surveys do not engage people. Games are fun!
        • People engage in complex tasks willingly
          • Do game-like methods work better?
        • MindCanvas has game-like elements (its not a game)
          • Interactive, visual, screen build up, fun
      • For both qualitative & quantitative
        • Remote moderated for qualitative
        • Remote unmoderated for quantitative
    • Rich interactive visualizations
      • Large datasets need statistical analysis & data mining
      • Visualizations-to-go
          • Self-contained files - embedded into PowerPoint, emailed, shared
          • Interactive visualizations with slides & knobs!
          • Easy to share with team
      • Visualization posters
        • Designers want printouts to hang on walls, and scribble on
    • MindCanvas research focuses on the mind
      • Inspiration from cognitive anthropology, psychology, market research
      • Semi-structured methods
      • Quantitative aggregation & visualization
      Categorizations Preferences Language
    • Who we built for: designer persona Needs convenient methods to do research Does not want to spend time learning statistics The busy designer / researcher who wants to look at patterns visually Want to directly interact with users, does not have time
    • Who we built for: participant persona “ This was the most fun I have had in a while!” “ It is very easy to complete the task. In fact, I had fun doing this.” The not-tech savvy person who occasionally takes surveys “ I think there are too many cards. But it was kind of fun.”
    • Where MindCanvas could help
      • Product Development: Finding the right feature-set for the right users (or personas)
      • Information Architecture: Understanding how people think for information design.
      • Early visual design validation: Understanding what people think & feel about a design when its just an image.
    • MindCanvas in product development
      • Initial understanding of domain
        • What’s important to people? What words do they use?
          • Method: Freelisting
          • Deliverable: ListMap
      • Prioritizing features / outcomes users care about
        • Method: Divide-the-dollar
        • Deliverable:
          • WeightMap
          • ClusterBrowser
    • MindCanvas in Information Architecture
      • How do people think about a domain?
        • Method: OpenSort
        • Deliverable
          • Dendogram
          • SimilarityBrowser
          • VocabularyBrowser 1, 2
      • Is your information architecture effective? Is one scheme more effective than another?
        • Method: TreeSort
        • Deliverable:
          • ClusterBrowser
    •  
    • Questions?
      • MindCanvas team is…
      • Delhi
      • Kapil Mohan
      • Kamalmeet Singh
      • Debasish Biswas
      • Sunil Gupta
      • Amit Ranjan
      • Mountain View
      • Jon Boutelle
      • Rashmi Sinha
      [email_address]
    • Methods & Deliverables
      • Current Methods
        • OpenSort: Dendogram, VocabBrowser, SimilarityBrowser
        • TreeSort: ClusterBrowser, SimilarityBrowser
        • Divide-the-Dollar: WeightMap, ClusterBrowser
        • Free Listing: ListMap
        • Utility Questions: MultipleChoice, EssayType
      • Upcoming Methods: MenuTrace, MindMontage, Likert Sort
      • Upcoming Designables: OnionMap
    • Collaborative Research Process
      • High quality research needs expertise
        • research design + statistics
      • Service should enable high quality research
        • Structured research process
          • Templates for study design
          • Help with data collection
    • What is MindCanvas
      • An innovative research platform for high quality research
        • Game-like elicitation methods
        • Interactive visualizations (designables-to-go)
        • Research expertise