The Science of Selling: How Data Shapes Unique Customer Journeys
summary
Shows concrete workflows: runs a 15-day A/B window with a 50/50 traffic split, flips hero images and tracks engagement, and reports an observable uplift in the second period rather than random noise. Describes building a recommendation engine using top‑10 catalogs, location and viewing habits, and linking household accounts in a unified CDP with multi‑profile linking to time suggestions (weekend family picks, new‑episode nudges). Covers experiment orchestration, conflict between design leadership and management, and which changes actually move engagement.
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chapters (20)
- 0:00Introduction to talk
- 1:51Customer journeys explained
- 3:20Netflix’s dynamic design evolution
- 6:37Leadership in customer journey design
- 8:52Team collaboration in design
- 10:22A/B testing paradigms
- 11:29Testing design decisions
- 12:51Key design decisions
- 14:20Experimenting with user segments
- 15:47Decoupage 10 case study
- 17:15Personalized movie recommendations
- 18:40Designing for user personas
- 20:17Episode completion challenges
- 21:08Location-based user preferences
- 22:38Predictive user behavior
- 23:43Customizing user experiences
- 24:46Building customer profiles
- 25:52Complexity of personalization
- 26:38Real-time movie suggestions
- 27:36Q&A session
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