UX STRAT Europe 2021 Workshop: Jules Skopp, Expedia
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Jules Skopp gave this workshop at UX STRAT Europe 2021 on the topic: "Design with Data: Objectives and Metrics, the Drivers of UX Strategy"
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UX STRAT Europe 2021 Workshop: Jules Skopp, Expedia
- 1. Design with data Objectives and metrics, the drivers of experience strategy
- 2. About
- 3. Hello! Data matters, d’oh! Confidence (new products) Sustainable outcomes (existing products) Good metric Metrics tree Demo 9:00 :40 10:00 :40 :50 11:10 :40 :50 12:20
- 4. About digital products, transferable elsewhere too
- 5. Slides and handouts will be provided
- 6. Whatever you share here stays here
- 7. Add your name to Post Its I won’t call you out otherwise
- 8. Hello!
- 9. Jules’ day
- 11. 1. Note challenges 2. Group them 3. Talk about the top one
- 12. Write down your challenges 5 mins
- 14. Group them in common themes
- 15. Describe your top challenge 2 mins each
- 16. Sketch out your product Include objectives
- 18. Data matters
- 19. Designers themselves have been partly to blame in the past: they have not always embraced design metrics or actively shown management how their designs tie to business goals. mckinsey.com/business-functions/mckinsey-design/our-insights/the-business-value-of-design, October 2018
- 20. Quant Analytics Eye tracking Tree tests A/B/n tests Surveys* Qual Interviews Usability tests Recordings Surveys*
- 22. What are your challenges with metrics/data?
- 23. Purpose of data
- 26. Does your data challenge fall into “Convince” bucket?
- 28. Antitheses Seeking data for other solutions that solve the same problem, or data that rejects your hypotheses I don’t care about the result I do care about specific result I do care about global results only
- 31. Does your data challenge fall into “Validate” bucket?
- 33. By doing action I expect outcome Hypotheses By doing _________, I expect ____________ Available Results
- 38. Does your data challenge fall into “Monitor” bucket?
- 41. Predict What happened/will happen if a metric changes? Repeat rate Conversion
- 42. Purpose of data: Convince, validate, monitor
- 43. Confidence
- 45. Kano model Must-haves, performance, and delighter features Jared Spool’s Medium article
- 46. Mo-st have Should have Could have Won’t have productplan.com/glossary/moscow-prioritization
- 49. 3+1 questions:
- 50. Are you defining what to build next?
- 51. Sketch how does your org innovate
- 52. What is the next thing you’d like to pursue?
- 53. Big decision: Merge products with similar goals?
- 55. How confident are you about your strategy?
- 57. Confidence 0 10 My idea is the best Deploy
- 61. Confidence 10 3 I dig it Me too!
- 62. Confidence 10 5 A/B tests MVP light launch
- 64. Are you familiar with the local maxima problem?
- 68. Good enough
- 75. The approach that matters Ideas you explored
- 76. Confidence
- 77. Stay two steps ahead with Confidence tracking Multiple strategies
- 79. 1. Conversion rate 2. % of users reached 3. Revenue potential 4. Page views 5. Trust
- 82. 1. Users’ revenue 2. Travelers’ conversion 3. Traveler page views 4. Trust
- 83. What are the measurable outcomes of your product?
- 84. Why not? Net promoter score
- 85. Promoters >35% retently.com/blog/good-net-promoter-score NPS survey interpretation, measure of success Promoters NPS = % promoters - % detractors Detractors 8 6
- 88. How would you feel if you could no longer use the product? Very disappointed Not disappointed
- 89. Promoters >40% review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit Product/market fit survey interpretation, measure of success Very disappointed
- 91. Promoters
- 92. Source: Internal report—please don’t share publicly
- 93. You are accountable for these metrics NOT
- 95. Organizational priorities: Objectives and key results
- 97. Vanity metrics Bounce rate Time Team velocity Page views Users Revenue productplan.com/glossary/vanity-metrics
- 98. Principle: Make it about the user success
- 99. Good metric
- 100. Return to your previous exercise and check for these factors...
- 101. Log in Dashboard To detail Take action Behavior-based Conversion funnel 1. 2. 3. 4.
- 103. Log in : take action Ratio or percentage
- 104. Product view Sat on it per
- 105. Pulse
- 107. Per week Per time frame
- 108. Plot on the timeline
- 109. Not enough traffic Leading indicators
- 110. 47 minutes
- 111. More than one metric
- 113. Visits Product view
- 114. Login : calendar Always more than one metric Login : create Login : invite Login : duplicate Login : view item
- 116. Why… yes! Conversion
- 117. Conversion Affecting behavior, removing Friction towards objective, is our job 60 838 12 40 15 190
- 118. ...the system automatically adds 30 business metrics to each test, just to make sure you don’t mess up anything The well-known rumor about Booking.com
- 122. Satisfaction “CSat” monitors quality of service qualtrics.com/uk/experience-management/customer/ measure-customer-satisfaction/ Overall, how satisfied are you with “La Jolla Grove restaurant”?
- 125. YES! Attitudes
- 126. For example Google’s HaTS or relevant qual. research Challenge: feature creep Solution: attitudinal research
- 127. Attitudes The highest goal of experience is to be able to change the opinion of users Google’s HaTS
- 128. Alright, yes! Competitive UX comparison
- 130. Principle: Make it about the user success
- 131. Users’ money made Users’ phys. betterment Users’ goals reached ...
- 133. Good metrics: Documenting user success Behaviors Attitudes/satisfaction People-centric framework, not yet copyrighted, by Jules
- 134. Metric tree
- 135. Increase revenue Decrease costs Increase new business Increase existing business Increase shareholder value Jared Spool: UX strategy means business
- 136. North star
- 137. Increase revenue Decrease costs Increase new business Increase existing business Increase shareholder value The north star metric can be… well... not exciting
- 138. Chair
- 139. Pick one Discover store Sit on it Compare Walk in Sell chairs
- 140. Product view Impression Sat on it Comparisons Visits Chairs sold
- 141. Think about the North-Star metric for your company
- 142. North star
- 143. Pick one Discover store Sit on it Compare Walk in Sell chairs
- 144. Pick one Discover store Sit on it Walk in Sell chairs
- 145. Fill in each next lane with the behavioral metrics leading into previous row’s metrics
- 147. Discussions matter
- 148. Appendix: Demo
- 152. Install Event tracking tracker extension View on Chrome Store
- 153. Install GA debugger extension View on Chrome Store
- 154. Event category This is a product space, like “ShoppingCart” Disclaimer: This might differ from Partner Central Shopping cart Next
- 155. Event action All the taps/clicks captured User.Click.Cart.Next 1. Shopping cart 2x 3x Next
- 156. Event label Distinguish between same events User.Click.Cart.Next label = step1 1. Shopping cart 2x 3x Next
- 157. 50$ Event value Attach value to events User.Click.Cart.Next step 1 value = 50 1. Shopping cart 2x 3x Next
- 158. Event Action: User.Click.Cart.Next Label: User.Click.Cart.Next=step2 Value: User.Click.Cart.Next step 2 = 50 2. Checkout Next Insurance +$10
- 159. Event action Ticking the box action User.Click.Cart.Insurance 2. Checkout Next Insurance +$10
- 160. Event action Ticking the box action User.Click.Cart.Insurance 2. Checkout Next Insurance +$10
- 161. Custom dimension Logs states as users do stuff IsInsured = True 2. Checkout Next Insurance +$10
- 162. 3. Summary 2x 3x Order $60 All together Event category: Shopping.Cart Event action: User.Click.Cart.Next Event label: Step3 Event value: 60 Custom dimension: IsInsured=True
- 164. Remove all of these
- 166. Add user segment
- 168. A/B/n testing
- 169. Original Var A Var B Var C
- 170. Multivariate testing
- 171. Original Var A Var B Var C
- 173. Original Var A Var B Var B
- 175. Original Var A.1 Var A.2 Var B.1 Va
- 177. Other metric