building a minimum viable product / learning from data
DESCRIPTION
Slides from my talk last week @ Berkeley, Haas School of Business.TRANSCRIPT
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Building a Minimum
Viable Product a data driven approach
Igal Perelman
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MVP
The minimum set of features you have to
build in order to learn from early adopters
(*) Lean Startup - Eric Ries, Steve Blank
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Decisions (assumptions) • Culture
• Core Use Case
• Differentiation
• Platform(s)
• UX
• Data
• Go To Market
• And many others…
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Goals
• Product Market Fit
• Scale
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MVP
The minimum set of features you have to build
in order to learn from early adopters
![Page 6: Building a Minimum Viable Product / Learning from data](https://reader034.vdocuments.mx/reader034/viewer/2022051311/5453d892af795908308b58aa/html5/thumbnails/6.jpg)
Learning from early adopters
• Qualitative (from day 0)
• Feedback channels
• Reach out to users
• Quantitative (from day 1)
• What should I measure?
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Quantitative
• New user acquisition
• New user activation
• Engagement
• Retention
• Revenue
(*) User resurrection
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New User Acquisition
• Invites
• SEO
• ASO
• PPC
• Social platforms
• And many other channels...
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ROI
• Investment / Acquisition channel
• UI
• Time
• $$$
• Return / AC == # of new users
• Activated users
• Paying users
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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?
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Voxer
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Voxer
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Funnel Analysis
(*) mixpanel, dummy data.
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Engagement
• Core use case => engagement ‘unit’
• # of these units
• Uniques
• Total
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(*) Internet Marketing Inc, Based on ComScore report.
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Retention
• % of engaged users after X time
• Cohort analysis
• Core use case
• Viability, reliability, speed and usability
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Retention
(*) mixpanel, dummy data.
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Iterate
• Tweak / Remove / Build
• Measure
• Iterate based on learnings
• Metrics
• User feedback
• Research
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Create a product that users ♥
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Q&A
more questions?
@iperelman