Measurements & Frameworks for Growth Optimization

Speaking at the Product-Led Festival, Michael Berliner, Masterclass, explained how to create a growth model that helps you understand how your metrics span across different growth channels.

He covers:

- How to zero-in and focus on your goal.
- Creating a growth model that helps you understand how your metrics span across different growth channels.
- The do/don't do/continue framework.
- Maximising efficiency and effectiveness towards goals.

Transcript

1. Measurements & frameworks for growth optimization
2. Agenda 1. Focusing on the goal. 2. Creating a growth model. 3. A “do | don’t do | continue” framework. 4. Optimizing team throughput.
3. What’s the antidote to these 3 failure reasons? Requires Focus *Data from CB Insights Study
4. The goal = $$$
5. Creating a growth model
6. How to prioritize across growth levers? Partnerships Viral Monetization New Markets Paid 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)
7. 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
8. 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
9. Applying a “don’t do” framework
10. The growth optimization process Ideation Prioritization Execution Learnings
11. Confidence Impact Effort
12. Confidence Impact Effort = Estimated effect on target metric = Estimated person-weeks of time
13. Comparable Products Prior Experiments Data & Analytics User Research Brainstorming Confidence = Data + Relevancy Subject Matter Experts
15. How conversion works ( Perceived Value ) x Excitement ( Perceived Costs ) x Context >
16. Questions we ask 1. How would you describe the product to a friend or family member? 2. What was the most exciting part of your experience? 3. What do you like about the page? Dislike? Want? 4. At what point did you get the information you needed to make a decision? 5. Which of these is most important for deciding whether to buy? 6. Which of these, if any, would be your hesitation with buying? 7. If it cost $X, would you buy it? Why or why not?
17. We want to maximize the perceived value
18. And get them excited
19. While reducing their perceived costs
20. And helping them understand it’s feasible right now
21. Process cheat-sheet Objective Tactics Hypothesis Ideation Comparables User Surveys On-Site Polls Prioritization I.C.E. Scoring Hypothesis “Themes” Execution Self-Contained Pod “1 Review” Standards Experimentation Architecture Streamlined Processes Learnings Standardized Segmentation Secondary Metrics Winning/Losing “Themes” Learning from Losers
22. Confidence Impact Effort ( ) Confidence x = Value Score
23. Double Down 80/20 Don’t Do
24. Optimizing team throughput
25. Throughput funnel Velocity Win-rate Success Rate Avg. Impact
26. Throughput metric curves Test Design, Testing Medium, Pod Structure, Processes & Expectations Backlog Size & Quality, Winning Themes Advanced Data Analysis, Big Swings 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
27. 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
28. Thank You www.MikeCrunch.com www.linkedin/in/berlinermichael
29. Appendix / Philosophies
30. Confidence Impact Effort
31. Impact Effort ( ) Confidence x = Value Score
32. Double Down 80/20 Don’t Do
33. Breaking growth levers down into initiatives Monetization Content Paid Viral Retention
34. There’s no “silver bullet” Safe Moderate Risky
35. Paid (FB Ads, Adwords, Retargeting) Partnerships New Markets Retention (First Experience, Renewal, Engagement) (International, Domestic, New Audiences) (Revenue Share, Distribution) Viral (Referrals, Incentives, Sharing Mechanisms) Monetization Content (SEO, Blog, Community) (Conversion, Pricing, Packaging) Ideation
36. Ideation Prioritization Execution Learnings Comparable Products Subject Matter Experts User Research Data Analysis Prior Experiments Brainstorming
37. Size opportunity using quantitative user polls Evaluate solution execution complexity Comparable Products Subject Matter Experts User Research Data Analysis Prior Experiments Brainstorming RESEARCH SOURCES User Problems Solution Hypotheses more confidence less confidence
38. 1) User-Centric Ideation 4) Focused Learnings 3) High-Velocity Execution 2) Disciplined Prioritization The Growth Experimentation Process
39. 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
40. Each $1 more earned per acquired = X% CAC LTV Revenue Each $1 less spent per acquired = X% Each additional… ...Visitor ...Acquired ...Retained = +$X Healthy Growth
41. We don’t know what we don’t know
42. Acquisition Channel Mix Healthy Unhealthy
43. Speed over completeness 1 Learning @70% 1 Learning @70% 1 Learning @100% > 1 Learning @70%
44. Don’t reinvent the wheel
45. Practice ruthless prioritization Double Down 80/20 Don’t Do