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Best Practices for Defining,
Evaluating & Communicating Key
Performance Indicators (KPIs) of
User Experience
       Meng Yang
       User Experience Researcher
       IBM Software Group
       @IBMSocialBizUX


   © Copyright IBM Corporation 2012
Agenda

   Why measuring user experience?

   What user experience KPIs or metrics?

   Future work




                     © Copyright IBM Corporation 2012
If you cannot measure it, you cannot improve it.
                                    -Lord Kelvin




                © Copyright IBM Corporation 2012
Design: Intuition-driven or data-driven?




Reference: Metrics-driven design by Johua porter:r
 http://www.slideshare.net/andrew_null/metrics-driven-design-by-joshua-porter
                                  © Copyright IBM Corporation 2012
5 Reasons why metrics are a designer’s best friend

     Metrics reduce arguments based on opinion.
     Metrics give you answers about what really works.
     Metrics show you where you’re strong as a designer.
     Metrics allow you to test anything you want.
     Clients love metrics.




   Reference: Metrics-driven design by Joshua porter
   http://www.slideshare.net/andrew_null/metrics-driven-design-by-joshua-porter

                                     © Copyright IBM Corporation 2012
Stakeholders (executives/developers) love numbers!




                 © Copyright IBM Corporation 2012
Lean start-up/Lean UX movement




    Reference: Lean Startup by Eric Ries http://theleanstartup.com/principles
                               © Copyright IBM Corporation 2012
What make good metrics?
  Actionable                                       Business alignment
  Accessible                                       Honest assessment
  Auditable                                        Consistency
                                                    Repeatability and
  Powerful                                        reproducibility
  Low-cost                                         Actionability

  Easy-to-use                                      Time-series tracking
                                                    Predictability
                                                    Peer comparability



 Reference:                                        2). Forrest Breyfogle’s book “Integrated
 1). Eric Ries: Lean Start up:                     Enterprise Excellence Volume II: Business
  http://theleanstartup.com/                       Deployment”
                                 © Copyright IBM Corporation 2012
User experience metrics used

              Task-level                                        Product-level
Task success rate                             System Usability Scale (SUS) score
Task easiness rating (SEQ)                    Net Promoter Score (NPS)
Task error rate
Task time

First click analysis
Heat map
Number of clicks
                  
Predicative human modeling
(CogTool) task time and clicks for
optimal path



                             © Copyright IBM Corporation 2012
System Usability Scale (SUS) Positive Version

   Why chosen?
     Free, short, valid, and reliable. [1]
     A single SUS score can be calculated
      and a grade can be assigned. [1]
     Over 500 user studies to be compared
      with. [1]
     The most sensitive post-study
      questionnaire. [2]
   References
     [1] Jeff Sauro's blog entry: Measuring
      Usability with the System Usability Scale
      (SUS)
      http://www.measuringusability.com/sus.p
      hp
     [2] Book by Jeff Sauro & James Lewis:
      Quantifying the User Experience:
      Practical Statistics for User Research .
      http://www.amazon.com/Quantifying-
      User-Experience-Practical-
      Statistics/dp/0123849683/ref=sr_1_1?
      s=books&ie=UTF8&qid=1327605730&sr
      =1-1                      © Copyright IBM Corporation 2012
SUS score calculation
   Calculation [1]
     For odd items: subtract one from the user
      response.
     For even-numbered items: subtract the user
      responses from 5
     This scales all values from 0 to 4 (with four being
      the most positive response).
     Add up the converted responses for each user
      and multiply that total by 2.5. This converts the
      range of possible values from 0 to 100 instead
      of from 0 to 40.
   Calculation package
       Jeff Sauro provides a SUS guide & calculator
        package ($299.99 for a site liscense)
        http://www.measuringusability.com/products/SUS
        pack
   Reference                                                      Example SUS score: 66.7, level C
       [1] Jeff Sauro's blog entry: Measuring Usability
        with the System Usability Scale (SUS)
        http://www.measuringusability.com/sus.php
                                © Copyright IBM Corporation 2012
Net Promoter Score (NPS)




              © Copyright IBM Corporation 2012
Task success rate
   Large-scale usability testing
       Self-reported success in UserZoom
   Small-scale moderated usability testing
       Through observation




                                                            Example task-based
                                                               unmoderated usability
                                                               testing through UserZoom




                         © Copyright IBM Corporation 2012
SEQ (Single Ease Question)
   Why chosen?
     Reliable, sensitive & valid. [1]
     Short, easy to respond to, easy to administer & easy to score [1]
     The secondly most sensitive after-task questions, next to SMEQ, but
      much simpler. [2]
   References
     [1] Jeff Sauro's blog entry: If you could only ask one question, use this
      one http://www.measuringusability.com/blog/single-question.php
     [2] Book by Jeff Sauro & James Lewis: Quantifying the User
      Experience: Practical Statistics for User Research .
      http://www.amazon.com/Quantifying-User-Experience-Practical-
      Statistics/dp/0123849683/ref=sr_1_1?
      s=books&ie=UTF8&qid=1327605730&sr=1-1




                            © Copyright IBM Corporation 2012
Example task performance table
                                                                                      Fake data for illustration purposes
           Task performance data summary
           (% means percentage of all participants for each task)
                     Successful with the Considered task
                                                                  Highlights of the problem                    Recommendation
                            task                   easy
              Task 1               90%                     95%            Easy task                           None
              Task 2               61%                     42%            Hard to find the action button      xx
              Task 3               55%                     30%            Too many clicks                     xx
              Task 4               85%                     90%            Relatively easy task                xx
Task performance data summary
(% means percentage of all participants for each task)                    Task performance data summary
             Successful with the task              Considered task easy   (% means percentage of all participants for each task)
                                                                                       Successful with the task              Considered task easy
           Study 1 Study 2 Change Study 1 Study 2 Change                             Study 1 Study 2 Change Study 1 Study 2 Change
  Task 1    89%         84%          -5.1%       60%      63%        3.0%   Task 1    89%         84%          -5.1%       60%      63%        3.0%
  Task 2    89%         70%         -19.0%       65%      60%       -5.2%   Task 2    89%         70%         -19.0%       65%      60%       -5.2%
  Task 3    62%         55%          -6.8%       75%      87%       12.0%   Task 3    62%         55%          -6.8%       75%      87%       12.0%
  Task 4    71%         90%         19.0%        56%      80%       24.0%   Task 4    71%         90%         19.0%        56%      85%       29.0%

                                              Benchmark comparison between two
                                                studies on the same tasks
                                                     © Copyright IBM Corporation 2012
Use cases and tasks dashboard

                                       Fake data for illustration purposes




              © Copyright IBM Corporation 2012
Clickstream data in large-scale user testings
   Good to have
       Yet another way to visually
        illustrate the problems which
        are shown in other metrics
        such as task success rate and
        easiness ratings.
   But hard to implement &
    analyze
     Approach 1: asking participants
      to install a plugin, which
      reduces the participation rate.
     Approach 2: inserting a line of
      javascript code on every page
      of the website, which is hard to
      achieve.




                           © Copyright IBM Corporation 2012
Task time and storyboard in CogTool
   What is CogTool
     Produce a valid cognitive model
      predicting how long it will take a
      skilled user to complete a task.
     Developed by Bonnie John from CMU
      (now at IBM Research).
   Pros
     Free and easy to install.
     Good way to get competitive data
      (task time).
     Task visualization shows the most
      time-consuming task steps.
   Cons
     Hard to learn at first.
     Don’t address issues for novice users
     Inter-rater validity and consistency

   Reference:
        CogTool website
        http://cogtool.hcii.cs.cmu.edu/
                                © Copyright IBM Corporation 2012
Best-practices

   Focus on core use cases and top tasks.
   Use standardized questions/metrics for peer
    comparability.
   Don’t always need large-scale (unmoderated) usability
    studies to gather metrics.
   Visualization is the key to effective communication.
       visual.ly is a good site to create infographics and visualization
   KPIs/metrics catch people’s attention, but qualitative
    information provides the insights.



                           © Copyright IBM Corporation 2012
Future work

   Align UX metrics with business goals.
   Communicate UX metrics to Influence product strategy.
   Incorporate UX metrics in the agile development
    process.
   Collaborate with analytics team to gather metrics such
    as Engagement/Adoption/Retention.
   How do we measure usefulness (vs. ease of use)?




                      © Copyright IBM Corporation 2012
© Copyright IBM Corporation 2012

IBM Lotus Software

550 King St.

Littleton, MA 01460

U.S.A.



Produced in the United States of America

May 2012

All Rights Reserved



IBM, the IBM logo and ibm.com are trademarks or registered trademarks

of International Business Machines Corporation in the United States, other

countries, or both. If these and other IBM trademarked terms are marked

on their first occurrence in this information with a trademark symbol (® or

™), these symbols indicate U.S. registered or common law trademarks

owned by IBM at the time this information was published. Such trademarks

may also be registered or common law trademarks in other countries. A

current list of IBM trademarks is available on the Web at “Copyright and

trademark information” at ibm.com/legal/copytrade.shtml

Other company, product and service names may be trademarks or service

marks of others.



References in this publication to IBM products and services do not

imply that IBM intends to make them available in all countries in which

IBM operates.




                                                        © Copyright IBM Corporation 2012

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Best practices for defining, evaluating, & communicating Key Performance Indicators (KPIs) of user experience

  • 1. Best Practices for Defining, Evaluating & Communicating Key Performance Indicators (KPIs) of User Experience Meng Yang User Experience Researcher IBM Software Group @IBMSocialBizUX © Copyright IBM Corporation 2012
  • 2. Agenda  Why measuring user experience?  What user experience KPIs or metrics?  Future work © Copyright IBM Corporation 2012
  • 3. If you cannot measure it, you cannot improve it. -Lord Kelvin © Copyright IBM Corporation 2012
  • 4. Design: Intuition-driven or data-driven? Reference: Metrics-driven design by Johua porter:r http://www.slideshare.net/andrew_null/metrics-driven-design-by-joshua-porter © Copyright IBM Corporation 2012
  • 5. 5 Reasons why metrics are a designer’s best friend  Metrics reduce arguments based on opinion.  Metrics give you answers about what really works.  Metrics show you where you’re strong as a designer.  Metrics allow you to test anything you want.  Clients love metrics. Reference: Metrics-driven design by Joshua porter http://www.slideshare.net/andrew_null/metrics-driven-design-by-joshua-porter © Copyright IBM Corporation 2012
  • 6. Stakeholders (executives/developers) love numbers! © Copyright IBM Corporation 2012
  • 7. Lean start-up/Lean UX movement Reference: Lean Startup by Eric Ries http://theleanstartup.com/principles © Copyright IBM Corporation 2012
  • 8. What make good metrics?  Actionable  Business alignment  Accessible  Honest assessment  Auditable  Consistency  Repeatability and  Powerful reproducibility  Low-cost  Actionability  Easy-to-use  Time-series tracking  Predictability  Peer comparability Reference: 2). Forrest Breyfogle’s book “Integrated 1). Eric Ries: Lean Start up: Enterprise Excellence Volume II: Business http://theleanstartup.com/ Deployment” © Copyright IBM Corporation 2012
  • 9. User experience metrics used Task-level Product-level Task success rate System Usability Scale (SUS) score Task easiness rating (SEQ) Net Promoter Score (NPS) Task error rate Task time First click analysis Heat map Number of clicks                    Predicative human modeling (CogTool) task time and clicks for optimal path © Copyright IBM Corporation 2012
  • 10. System Usability Scale (SUS) Positive Version  Why chosen?  Free, short, valid, and reliable. [1]  A single SUS score can be calculated and a grade can be assigned. [1]  Over 500 user studies to be compared with. [1]  The most sensitive post-study questionnaire. [2]  References  [1] Jeff Sauro's blog entry: Measuring Usability with the System Usability Scale (SUS) http://www.measuringusability.com/sus.p hp  [2] Book by Jeff Sauro & James Lewis: Quantifying the User Experience: Practical Statistics for User Research . http://www.amazon.com/Quantifying- User-Experience-Practical- Statistics/dp/0123849683/ref=sr_1_1? s=books&ie=UTF8&qid=1327605730&sr =1-1 © Copyright IBM Corporation 2012
  • 11. SUS score calculation  Calculation [1]  For odd items: subtract one from the user response.  For even-numbered items: subtract the user responses from 5  This scales all values from 0 to 4 (with four being the most positive response).  Add up the converted responses for each user and multiply that total by 2.5. This converts the range of possible values from 0 to 100 instead of from 0 to 40.  Calculation package  Jeff Sauro provides a SUS guide & calculator package ($299.99 for a site liscense) http://www.measuringusability.com/products/SUS pack  Reference Example SUS score: 66.7, level C  [1] Jeff Sauro's blog entry: Measuring Usability with the System Usability Scale (SUS) http://www.measuringusability.com/sus.php © Copyright IBM Corporation 2012
  • 12. Net Promoter Score (NPS) © Copyright IBM Corporation 2012
  • 13. Task success rate  Large-scale usability testing  Self-reported success in UserZoom  Small-scale moderated usability testing  Through observation Example task-based unmoderated usability testing through UserZoom © Copyright IBM Corporation 2012
  • 14. SEQ (Single Ease Question)  Why chosen?  Reliable, sensitive & valid. [1]  Short, easy to respond to, easy to administer & easy to score [1]  The secondly most sensitive after-task questions, next to SMEQ, but much simpler. [2]  References  [1] Jeff Sauro's blog entry: If you could only ask one question, use this one http://www.measuringusability.com/blog/single-question.php  [2] Book by Jeff Sauro & James Lewis: Quantifying the User Experience: Practical Statistics for User Research . http://www.amazon.com/Quantifying-User-Experience-Practical- Statistics/dp/0123849683/ref=sr_1_1? s=books&ie=UTF8&qid=1327605730&sr=1-1 © Copyright IBM Corporation 2012
  • 15. Example task performance table Fake data for illustration purposes Task performance data summary (% means percentage of all participants for each task) Successful with the Considered task Highlights of the problem Recommendation task easy Task 1 90% 95% Easy task None Task 2 61% 42% Hard to find the action button xx Task 3 55% 30% Too many clicks xx Task 4 85% 90% Relatively easy task xx Task performance data summary (% means percentage of all participants for each task) Task performance data summary Successful with the task Considered task easy (% means percentage of all participants for each task) Successful with the task Considered task easy Study 1 Study 2 Change Study 1 Study 2 Change Study 1 Study 2 Change Study 1 Study 2 Change Task 1 89% 84% -5.1% 60% 63% 3.0% Task 1 89% 84% -5.1% 60% 63% 3.0% Task 2 89% 70% -19.0% 65% 60% -5.2% Task 2 89% 70% -19.0% 65% 60% -5.2% Task 3 62% 55% -6.8% 75% 87% 12.0% Task 3 62% 55% -6.8% 75% 87% 12.0% Task 4 71% 90% 19.0% 56% 80% 24.0% Task 4 71% 90% 19.0% 56% 85% 29.0% Benchmark comparison between two studies on the same tasks © Copyright IBM Corporation 2012
  • 16. Use cases and tasks dashboard Fake data for illustration purposes © Copyright IBM Corporation 2012
  • 17. Clickstream data in large-scale user testings  Good to have  Yet another way to visually illustrate the problems which are shown in other metrics such as task success rate and easiness ratings.  But hard to implement & analyze  Approach 1: asking participants to install a plugin, which reduces the participation rate.  Approach 2: inserting a line of javascript code on every page of the website, which is hard to achieve. © Copyright IBM Corporation 2012
  • 18. Task time and storyboard in CogTool  What is CogTool  Produce a valid cognitive model predicting how long it will take a skilled user to complete a task.  Developed by Bonnie John from CMU (now at IBM Research).  Pros  Free and easy to install.  Good way to get competitive data (task time).  Task visualization shows the most time-consuming task steps.  Cons  Hard to learn at first.  Don’t address issues for novice users  Inter-rater validity and consistency  Reference:  CogTool website http://cogtool.hcii.cs.cmu.edu/ © Copyright IBM Corporation 2012
  • 19. Best-practices  Focus on core use cases and top tasks.  Use standardized questions/metrics for peer comparability.  Don’t always need large-scale (unmoderated) usability studies to gather metrics.  Visualization is the key to effective communication.  visual.ly is a good site to create infographics and visualization  KPIs/metrics catch people’s attention, but qualitative information provides the insights. © Copyright IBM Corporation 2012
  • 20. Future work  Align UX metrics with business goals.  Communicate UX metrics to Influence product strategy.  Incorporate UX metrics in the agile development process.  Collaborate with analytics team to gather metrics such as Engagement/Adoption/Retention.  How do we measure usefulness (vs. ease of use)? © Copyright IBM Corporation 2012
  • 21. © Copyright IBM Corporation 2012 IBM Lotus Software 550 King St. Littleton, MA 01460 U.S.A. Produced in the United States of America May 2012 All Rights Reserved IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked on their first occurrence in this information with a trademark symbol (® or ™), these symbols indicate U.S. registered or common law trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in other countries. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at ibm.com/legal/copytrade.shtml Other company, product and service names may be trademarks or service marks of others. References in this publication to IBM products and services do not imply that IBM intends to make them available in all countries in which IBM operates. © Copyright IBM Corporation 2012