The webinar discusses frameworks and metrics for growth optimization. It covers creating a growth model that prioritizes different growth levers like content, retention, partnerships, and monetization. Common growth metrics like cost per acquisition, lifetime value, and revenue are examined. The webinar also presents a "don't do, double down, 80/20" framework for prioritizing experiments and optimizing a team's throughput. The goal is to develop a hypothesis-driven growth strategy that maximizes revenue by optimizing resources towards the highest ROI growth levers.

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Webinar: Growth Optimization:
Metrics & Frameworks
by MasterClass Sr PM

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6. Measurements & frameworks for
growth optimization

7. Agenda
1. Focusing on the goal.
2. Creating a growth model.
3. A “do | don’t do | continue” framework.
4. Optimizing team throughput.

8. What’s the antidote to these 3 failure reasons?
Requires
Focus
*Data from CB Insights Study

9. The goal = $$$

10. Creating a growth model

11. How to prioritize across growth levers?
PartnershipsViral
Monetization New MarketsPaid
Content
Retention
(SEO, Blog, Community) (Referrals, Incentives,
Sharing Mechanisms)
(FB Ads, Adwords,
Retargeting)
(First Experience,
Renewal, Engagement)
(International, Domestic,
New Audiences)
(Conversion, Pricing,
Packaging)
(Revenue Share,
Distribution)

12. Common growth metrics
Paid
Spend
Cost / Click
Viral
Referred Visitors / Acquired
Spend / User Referral
Content
SEO Visitors
Partnerships
Partner Referred Visitors
Spend / Partner Referral
Visitors
Spend / Visitor
Conversion
Purchases / Visitor
Average Order Value
Acquired
Revenue / Visitor
Retention
Retention Rate
Purchases / Month
Retained
Revenue / Acquired
CAC
LTV
Revenue

13. Common growth metrics
CAC
LTV
Revenue
Each $1 less spent per acquired = X%
Each $1 more earned per acquired = X%
Each additional…
...Visitor
...Acquired
...Retained
= +$X
Healthy
Growth

14. Applying a “don’t do” framework

15. Confidence
Impact
Effort

16. Confidence
Impact
Effort
= Estimated effect on target metric
= Estimated person-weeks of time

17. Comparable
Products
Prior Experiments
Data & Analytics
User Research
Brainstorming
Confidence
=
Data
+
Relevancy
Subject Matter
Experts

19. Confidence
Impact
Effort
( ) Confidencex =
Value
Score

20. Double Down
80/20
Don’t Do

21. Optimizing team throughput

22. Throughput funnel
Velocity
Win-rate
Success Rate
Avg. Impact

23. Throughput metric curves
Experiment Design, Testing Medium,
Pod Structure
Backlog Size & Quality,
Winning Themes
Advanced Data Analysis
Testing Velocity
Test Win-Rate
Avg. Lift / Win
Improve With:
Eventually you calibrate these metrics by lever to more easily estimate a lever’s revenue potential
Metric
Time

24. Voilà!
A Hypothesis Driven Growth
Strategy to Maximize Revenue
Optimize
backlog for
maximum
revenue ROI
per time
invested.
Optimize
resources towards
highest revenue
ROI levers

25. Thank You
www.MikeCrunch.com
www.linkedin/in/berlinermichael

26. Appendix / Philosophies

27. Confidence
Impact
Effort

28. Impact
Effort
( ) Confidencex =
Value
Score

29. Double Down
80/20
Don’t Do

30. Comparable
Products
Prior Experiments
Data & Analytics
User Research
Brainstorming
Subject Matter
Experts
Confidence
=
Data
+
Relevancy

31. No-Purchase Reasons

32. Breaking growth levers down into initiatives
Monetization
ContentPaid
Viral Retention

33. There’s no “silver bullet”
Safe
Moderate
Risky

34. We don’t know what we don’t know

35. Acquisition Channel Mix
Healthy Unhealthy

36. Speed over completeness
1 Learning @70%
1 Learning @70% 1 Learning @100%
>1 Learning @70%

37. Don’t reinvent the wheel

38. Practice ruthless prioritization
Double Down
80/20
Don’t Do

39. 39