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Data and Design: BFFs or Frenemies?
- 1. Data and Design: BFFs or Frenemies? Steve Mulder @muldermedia
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- 5. 5 Trap #1 We design by blindly following data
- 6. 6
- 7. 7 Trap #2 We measure the wrong thing
- 8. 8
- 9. 9
- 10. 10 What we measure becomes what we reward
- 11. 11 What we reward becomes what we do and what we are
- 12. 12 Trap #3 We become optimizers instead of designers
- 13. 13 Optimization via A/B or usability testing The danger of optimizing to a local maximum Local maximum
- 14. 14
- 15. 15 1. Data is the platform from which we leap
- 16. 16 For NPR, Arbitron ratings data tells us that audience is up but listening time is down
- 17. 17 Third-party research validates trends in media fragmentation and digital adoption
- 18. 18 Channels proliferate, presenting both opportunity and challenge “Radio isn’t going away, it’s going everywhere.”
- 19. 19 Our own research and personas reveal changing consumer behaviors & opportunities
- 20. 20 It’s not about building things that users know to ask for
- 21. 21 New digital interfaces in familiar locations (connected car)
- 22. 22 Experiments with new listening experiences Exploring experiences that meet needs users can’t yet articulate
- 23. 23 2. Data helps us know how high we’ve jumped and whether to keep going
- 24. 24 The Facebook experiment: Local station stories geo-targeted on NPR’s Facebook stream
- 25. 25 Local stories saw consistently higher engagement and grew local audience
- 26. 26 Pivot and double-down: We created a workflow tool so we can scale this offering
- 27. 27 and more about continuous learning 3. It’s less about achieving goals
- 28. 28 Yes, this sounds like Lean Startup thinking Assumption/hypoth esis Minimum Viable Product Analytics, researc h, testing
- 29. 29 Designing choice in the new NPR app Original design: Give users more control/choices Hypothesis to test: Fewer immediate choices + simplicity = longer listening Results: Listening time up 8%
- 30. 30 Usability testing (and third-party research) on the infamous hamburger nav
- 31. 31 Walking the narrow path
- 32. 32
Editor's Notes
- Qualitative and quantitativeUser interviews, surveys, third-party researchUsability testing, A/B testing, concept testinghttp://www.flickr.com/photos/chicagobart/4650478963/
- UX and design community: fundamental fear and skepticism of research & metricsCan feel like data’s purpose is to mug design and steal creativity from us, restrict what we dohttp://www.flickr.com/photos/spencerbbclark/6483073463/
- http://www.flickr.com/photos/kerryburnout/3826128002/
- False:Research = doing what users tell you to doDriving directions, prescriptive, restrictiveLycos marketing survey on colors
- Sony boombox colorWhat users say isn’t always what they do
- Or measuring only one thingEverything hinges on what you decide to measurehttp://www.adprint.ro/files/executions/8/356_topinterior_mag_sofa_low.jpg_900.jpg
- Wisconsin grocery chain decided to use IPM (items per minute) as key metric for cashier productivity. Faster checkout should mean shorter lines, happier customers, more profit.But IPM is only tracked when a lane is open and a cashier’s terminal is ready. So cashiers learned to put their terminals in secure state to stop the clock – between customers, while bagging, etc. IPM score goes up, but terminal on and off slows down actual checkout times.*Unintended consequences*http://innovationedge.com/2010/05/10/dangerous-metrics-for-innovation/
- Former Soviet Union: managers of glass plants rewarded by tons of sheet glass produced. Most plants produced glass so thick it was nearly opaque. Changed to square meters of glass. Led to glass so thin that it was easily broken.For us: Session conversion vs longer-term loyalty effectsUpsellsLeads to false optimization, taking us in the wrong directionhttp://compliance.saiglobal.com/community/know/blogs/item/4392-unintended-consequences-and-perverse-incentives
- Ifsomethingcanbe counted, it’smorelikely to be used tomeasuresuccessWe choosewhat we measure – and whatmetrics we lookat and use the mosthttp://www.flickr.com/photos/60852569@N00/2204909532/
- Incentives drive behavior change and cultureThey affect what we work on and who we becomeWhat gets counted in your organization?What numbers do you praise people for or chastise them for?How does that change behavior and impact what you do and who you are?http://www.flickr.com/photos/jon_tucker/2446567442/
- Instead of using our creative skills, it’s just about optimization and making very small adjustmentsBecoming machinists, tending to the robots that make decisionsCult of A/B testingDoug at Google on testing blueshttp://www.flickr.com/photos/seattlemunicipalarchives/4089729743/
- What is it about A/B testing that makes it so easy to fall into this trap?
- It’s the baseline we start from, not the endIt provides context and constraints that focus us before freeing ushttp://www.flickr.com/photos/bfishadow/4407857237/
- Opportunity: reaching new audience where they liveChallenge: More competitors for “earshare” than ever before
- Channel usage by segmentLikelihood to consider public radioBrand perception and affinity:NPRvs station vsprogramBUT all this data doesn’t tell us exactly what to do
- Smartphone app works with Ford Sync, voice control
- App in private betaMobile version of NPR Infinite PlayerRemixing public radio content, algorithms and editorial curation for a lean-back or lean-forward experience
- Measure how high we've jumped (and whether it's worth continuing investment) It should inspire us to reach higherWithout overly limiting our design choiceshttp://www.flickr.com/photos/10710442@N08/8265087493/in/photolist-dAmJyv-aoYjU9-aoYk3q-LJAUR
- Initially: manual process – concierge MVP
- Mindset: the goal is learningThere is no “finished”http://www.deviantart.com/morelikethis/artists/198956566?view_mode=2
- Flips the product development model on its head (build first, then figure out what to measure)
- Findability and discoverabilityTesting alone didn’t answer the questionBut it gave us insights so WE could answer it
- Falling into the cult of datavsFalling into the cult of egoWithout data, design is just guessingWhy is it so hard for teams to walk the narrow path?
- Data doesn’t give us the answers, it helps us ask better questions