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Gibson Biddle "Netflilx's Customer Obsession" Productized19
The document discusses Gibson Biddle's insights on customer obsession at Netflix, emphasizing the importance of delighting customers and using data to drive product strategies. Key elements include personalization, consumer insights, and the balance between margin enhancement and customer delight. The work highlights the effectiveness of A/B testing and experimental approaches to improve customer retention and satisfaction.
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Gibson Biddle "Netflilx's Customer Obsession" Productized19
- 1. Productized: November 22,2019 N E T F L I X ’ S CUSTOMER OBSESSION Gibson Biddle // @gibsonbiddle @gibsonbiddle
- 2. @gibsonbiddle Are you a Netflix member?
- 3. Net Promoter Score ? Detractors(0-6)Passives (7-8)Promoters (9-10) Net Promoter Score @gibsonbiddle
- 4. Net Promoter Score 10%10%80%70% 70 Detractors (0-6)Passives (7-8)Promoters (9-10) Net Promoter Score @gibsonbiddle
- 5. Jeff Bezos CEO, Amazon @gibsonbiddle Customersare always beautifully, wonderfully dissatisfied, even when they report being happy and business is great. Even when they don’t yet know it, customers want something better, and your desire to delight customers will drive you to invent on their behalf.”
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- 11. Speaker, Adviser, Teacher(2015) CPO, Chegg (2010) VP Product, Netflix (2005) SVP, Creative Wonders,The Learning Company, Mattel (1995) Director, Product, Electronic Arts (1991) Gibson Biddle @gibsonbiddle
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- 14. Customer Obsession The DHM Model ConsumerScience Free Trial Reminder Agenda @gibsonbiddle
- 15. @gibsonbiddle DHM Delight customers in Hardto copy Margin-enhancing ways.
- 16. Balancing act Delight v.margin New Release DVD test. @gibsonbiddle
- 17. NEW on DVD Consumerinsight Surveys, focus groups & CS dispositioning data The A/B test Perfect New Release Delivery The result Cancels: from 4.50% to 4.45% “Save” 5,000 customers “Worth” $1M= 5,000 x $100 x 2 But, additional inventory = $5M “Launch to all” or “No launch”? @gibsonbiddle Perfect New Release test
- 18. @gibsonbiddle “Movie enjoyment madeeasy” Personalization Device ecosystem Original content / ExamplesHard to copy Brand Unique technology Network effect Economies of scale
- 19. @gibsonbiddle Personalized Instant (DVD,streaming) Easy Exclusives Open APIs Entertainment Friends (social) Movie-finding tools
- 20. Entertainment Instant (DVD, streaming) EasyExclusives Open APIs Friends (social) Movie-finding tools @gibsonbiddle Personalized
- 21. Entertainment Instant (DVD, streaming) EasyExclusives Open APIs Friends (social) Movie-finding tools Originals TV devices @gibsonbiddle Personalized
- 22. Product strategy Personalization Instant Easy Device ecosystem Margin-enhancing /Tactics Ratings Wizard, new algorithms From 20 to 100 hubs; streaming Day One experience API launch; Xbox, Playstation Price & plan testing @gibsonbiddle
- 23. / Metrics % members:50 + ratings at M2 % members watch > 15 min./mo. % with > 3 titles in queue, day 1 % of demand weighted TVs Lifetime value, gross margin @gibsonbiddle Product strategy Personalization Instant Easy Device ecosystem Margin-enhancing
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- 25. Consumer Science Consumer insight through: Qualitative Survey Existingdata A/B tests Hypotheses Procedures (Experiments) Data (Results) SCIENTIFIC METHOD Findings (Conclusions) @gibsonbiddle
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- 27. Ratings Wizard Queue-add data Collaborativefiltering Acquire better movies / Tactic @gibsonbiddle Personalization Explicit data Implicit data Matching algorithms High-quality movies
- 28. @gibsonbiddle P2 > 50ratings % members add > 6 dvds/mo. RMSE Average rating / MetricPersonalization Explicit data Implicit data Matching algorithms High-quality movies
- 29. Pop Quiz #1 @gibsonbiddle What% of members rate > 50 movies in first 6 weeks?
- 30. % of memberswho rate > 50 movies @gibsonbiddle 0 0.075 0.15 0.225 0.3 2004 2005 2006 2007 2008 2009 2010 2011 30% 15% 0%
- 31. Ratings Wizard @gibsonbiddle The moreyou rate, the better we’ll do at finding movies you’ll love.
- 32. @gibsonbiddle Pop Quiz #2 Willdemographics help predict movie taste?
- 33. Movie predictions improveover time @gibsonbiddle 0.6 0.7 0.8 0.9 1 2004 2005 2006 2007 2008 2009 2010 2011
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- 35. Improve RMSE by10%, win $1M! @gibsonbiddle
- 36. @gibsonbiddle Pop Quiz #3 Willthe new algorithm improve retention?
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- 38. @gibsonbiddle 0 0.95 1.9 2.85 3.8 2004 2005 20062007 2008 2009 2010 2011 Average rating improves over time
- 39. @gibsonbiddle Movie rating =movie enjoyment?
- 40. @gibsonbiddle Movie rating =movie enjoyment.
- 41. From Stars toThumbs @gibsonbiddle
- 42. Mall Cop =93% match @gibsonbiddle 93% Match
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- 47. (2018: All dataare guesstimates) @gibsonbiddle 2% 90% $10M 85% Consumer insight Fence sitters <> “cancel anytime” Customer service: Trials/visits conversion: Month one retention: A/B test results Month one retention: DHM? High or low stakes? Who makes the decision? Free trial reminder Launch or no launch? The A/B test: Day 27 reminder
- 48. DHM: Double downon delight Low stakes (magnitude, reversible) Cost of ethics & brand Debate, decide, do. Free trial learnings @gibsonbiddle
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- 51. @gibsonbiddle Existing data Data focus Customer& Bus. Qualitative 1-1, usability, focus groups Survey data Demo, cancel, quality, NPS A/B testing Measure change Delight v. margin Strategy Hypotheses DHM model Are You Obsessed?
- 52. Customer Obsession Putting the customerat the center of everything you do, to delight customers in hard-to-copy, margin-enhancing ways, to invent the future.” @gibsonbiddle
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- 57. www.gibsonbiddle.com Complete Net PromoterScore survey Download PDF of presentation “Customer Obsession” article on Medium @gibsonbiddle
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