building a minimum viable product / learning from data

20
Building a Minimum Viable Product a data driven approach Igal Perelman

Upload: igal-perelman

Post on 30-Oct-2014

730 views

Category:

Technology


0 download

DESCRIPTION

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

TRANSCRIPT

Page 1: Building a Minimum Viable Product / Learning from data

Building a Minimum

Viable Product a data driven approach

Igal Perelman

Page 2: Building a Minimum Viable Product / Learning from data

MVP

The minimum set of features you have to

build in order to learn from early adopters

(*) Lean Startup - Eric Ries, Steve Blank

Page 3: Building a Minimum Viable Product / Learning from data

Decisions (assumptions) • Culture

• Core Use Case

• Differentiation

• Platform(s)

• UX

• Data

• Go To Market

• And many others…

Page 4: Building a Minimum Viable Product / Learning from data

Goals

• Product Market Fit

• Scale

Page 5: Building a Minimum Viable Product / Learning from data

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

Learning from early adopters

• Qualitative (from day 0)

• Feedback channels

• Reach out to users

• Quantitative (from day 1)

• What should I measure?

Page 7: Building a Minimum Viable Product / Learning from data

Quantitative

• New user acquisition

• New user activation

• Engagement

• Retention

• Revenue

(*) User resurrection

Page 8: Building a Minimum Viable Product / Learning from data

New User Acquisition

• Invites

• SEO

• ASO

• PPC

• Social platforms

• And many other channels...

Page 9: Building a Minimum Viable Product / Learning from data

ROI

• Investment / Acquisition channel

• UI

• Time

• $$$

• Return / AC == # of new users

• Activated users

• Paying users

Page 10: Building a Minimum Viable Product / Learning from data

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?

Page 11: Building a Minimum Viable Product / Learning from data

Voxer

Page 12: Building a Minimum Viable Product / Learning from data

Voxer

Page 13: Building a Minimum Viable Product / Learning from data

Funnel Analysis

(*) mixpanel, dummy data.

Page 14: Building a Minimum Viable Product / Learning from data

Engagement

• Core use case => engagement ‘unit’

• # of these units

• Uniques

• Total

Page 15: Building a Minimum Viable Product / Learning from data

Pinterest

(*) Internet Marketing Inc, Based on ComScore report.

Page 16: Building a Minimum Viable Product / Learning from data

Retention

• % of engaged users after X time

• Cohort analysis

• Core use case

• Viability, reliability, speed and usability

Page 17: Building a Minimum Viable Product / Learning from data

Retention

(*) mixpanel, dummy data.

Page 18: Building a Minimum Viable Product / Learning from data

Iterate

• Tweak / Remove / Build

• Measure

• Iterate based on learnings

• Metrics

• User feedback

• Research

Page 19: Building a Minimum Viable Product / Learning from data

Create a product that users ♥

Page 20: Building a Minimum Viable Product / Learning from data

Q&A

more questions?

@iperelman