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Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
Building a Minimum Viable Product / Learning from data
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Building a Minimum Viable Product / Learning from data

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Slides from my talk last week @ Berkeley, Haas School of Business.

Slides from my talk last week @ Berkeley, Haas School of Business.

Published in: Technology, Business
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Transcript

  • 1. Building a Minimum Viable Product a data driven approach Igal Perelman
  • 2. MVP The minimum set of features you have to build in order to learn from early adopters (*) Lean Startup - Eric Ries, Steve Blank
  • 3. Decisions (assumptions) • • • • • • • • Culture Core Use Case Differentiation Platform(s) UX Data Go To Market And many others…
  • 4. Goals • Product Market Fit • Scale
  • 5. MVP The minimum set of features you have to build in order to learn from early adopters
  • 6. Learning from early adopters • Qualitative (from day 0) • • Feedback channels Reach out to users • Quantitative (from day 1) • What should I measure?
  • 7. Quantitative • New user acquisition • New user activation • Engagement • Retention • Revenue (*) User resurrection
  • 8. New User Acquisition • Invites • SEO • ASO • PPC • Social platforms • And many other channels...
  • 9. ROI • Investment / Acquisition channel • • • UI Time $$$ • Return / AC == # of new users • • Activated users Paying users
  • 10. New User Activation • Signup flow >> Signup page • Questions • • • Signup funnel conversion % of new users that complete the core use case What is the core metric?
  • 11. Voxer
  • 12. Voxer
  • 13. Funnel Analysis (*) mixpanel, dummy data.
  • 14. Engagement • Core use case => engagement ‘unit’ • # of these units • • Uniques Total
  • 15. Pinterest (*) Internet Marketing Inc, Based on ComScore report.
  • 16. Retention • % of engaged users after X time • Cohort analysis • Core use case • Viability, reliability, speed and usability
  • 17. Retention (*) mixpanel, dummy data.
  • 18. Iterate • Tweak / Remove / Build • Measure • Iterate based on learnings • • • Metrics User feedback Research
  • 19. Create a product that users ♥
  • 20. Q&A more questions? @iperelman

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