Be Data Informed Without Being a Data Scientist
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Pamela Pavliscak discusses the importance of being data-informed without requiring extensive knowledge of data science. She emphasizes the overload of data in today's society, the need for curiosity and critical thinking when engaging with data, and the balance between quantitative and qualitative insights. The document promotes actionable strategies for utilizing data in user experience design and decision-making.
Be Data Informed Without Being a Data Scientist
- 1. BE DATA INFormeD without being a data scientist
- 2. Pamela Pavliscak (not meant to be spoken) @paminthelab Change Sciences
- 3. I <3 Data but I’m still learning
- 4. Today’s JOURNEY data overload the analyst the threshold poor signals the abyss return with elixir data thinking supertechnological aid trophy metrics
- 5. 3 million emails 2 million Google searches 684,000 Facebook shares $272,000 spent online shopping 100,000 tweets 3,600 photos to Instagram 2 million blog posts
- 6. 1 baby born 5 mobile phones activated @paminthelab
- 7. Each person carries an average of 3 devices
- 8. 375 megabytes consumed Per household each day
- 10. For now, data is focused on Selling and surveillance
- 12. BIG DATA is a little scary
- 13. Big data is like teenage sex - everybody talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it. -Dan Ariely “ @paminthelab
- 14. INSIGHT VACUUM
- 15. Think of data science like archeology traces left behind
- 16. They came <something, something> They left
- 17. It’s the every person story
- 18. There are really three ways to use DATA
- 19. PROVE something you know
- 20. Proving is about the bottom line
- 21. Numbers KPIs & scores @paminthelab
- 22. Strategic rather than tactical
- 23. TOO HIGH LEVEL for experience design
- 24. IMPROVE something you can change
- 26. A lot of consistency and a little experimentation
- 27. DISCOVER something you don’t know
- 29. Discovering is about relationships
- 30. How to Think like a data scientist
- 31. curiosity THINK WITH DATA 1
- 33. Expectations (before) Moments (during) Memories (after)
- 34. The Experience Continuum the long before just a memory weeks days hours minutes now now now minutes hours days almost now now the here after
- 35. remember it’s people first
- 36. Behaviors Interactions Feelings Attitudes
- 37. Start with buckets, and count the things
- 38. hamburger icon test case
- 40. Our gut says no
- 41. PROBABILiTy BE A BIT BAYESIAN 2
- 42. P (B | A) P (A) P (A | B) = P (B) TRANSLATION Belief + new evidence = updated belief
- 44. Analytics Piwik, Clicky Google Chartbeat, Crazy Egg, Mixpanel, KISS metrics
- 45. Social Media Data Shoutlet Reachli Trackur Topsy Social Mention Open Status Google Trends
- 46. Other data sources 1. A/B tests 2. Surveys 3. Heatmaps 4. Quantified qualitative studies 5. Biometrics & eyetracking 6. Sales data 7. CRM data 8. Call center logs 9. Billing systems 10. Business intelligence systems
- 47. It’s really all behaviors & words
- 48. USE degrees over absolutes
- 49. Pay attention to variation @paminthelab
- 51. It’s never 100% CERTAIN
- 53. Source: Exis Subtle changes make a difference
- 54. TRansparency DESCRIBE YOUR BIAS 3
- 55. There is always a filter HEISENBERG UNCERTAINTY PRINCIPLE (small data) SIGNAL BIAS (big data)
- 56. Even a big data source is not everyone
- 57. By studying something, we change it
- 58. Nice people skew studies HUMAN CONTACT NICE
- 59. There is a nice factor TV Network Site ONLINE Study 0 20 40 60 80 100 TV Network Site LAB Study 0 20 40 60 80 100 Source: Change Sciences
- 61. gut feel <bias> one site
- 63. COMbine forces Quantitative & Qualitative
- 64. Balance subjective & objective
- 66. Not Curious 74% tapped right past help of any kind
- 67. meaning TELL A STORY 5
- 68. SKIP TO MEANING 5 4 3 2 1 0
- 71. Audience put a human face on it
- 72. C-Suite Team
- 74. MENU IS CLEARER 20% more people clicked Menu than the the icon alone Source: Exis
- 75. I’ve been seeing that little doodad on the site, but I just thought it was part of the design. -M, Millennial “ Source: Change Sciences
- 77. Hamburger awareness Q1 2013 Q2 2013 Q3 2013 Q4 2013 Q1 2014 Q2 2014 Source: Change Sciences is on the rise
- 78. Data thinking 1. Get curious 2. Think Bayesian 3. Explain bias 4. Embrace context 5. Show & tell
- 79. UX + DATA SCIENCE
- 80. BE DATA INFormeD without being a data scientist Pamela Pavliscak @paminthelab ChangeSciences.com