Measurements & Frameworks for Growth Optimization

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Measurements & frameworks for growth optimization

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

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

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The goal = $$$

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Creating a growth model

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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)

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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

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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

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Applying a “don’t do” framework

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The growth optimization process Ideation Prioritization Execution Learnings

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Conﬁdence Impact Effort

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

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

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No content

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How conversion works ( Perceived Value ) x Excitement ( Perceived Costs ) x Context >

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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?

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We want to maximize the perceived value

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And get them excited

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While reducing their perceived costs

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And helping them understand it’s feasible right now

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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

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Conﬁdence Impact Effort ( ) Conﬁdence x = Value Score

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Double Down 80/20 Don’t Do

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Optimizing team throughput

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Throughput funnel Velocity Win-rate Success Rate Avg. Impact

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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

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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

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

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Appendix / Philosophies

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Conﬁdence Impact Effort

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Impact Effort ( ) Conﬁdence x = Value Score

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Double Down 80/20 Don’t Do

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Breaking growth levers down into initiatives Monetization Content Paid Viral Retention

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There’s no “silver bullet” Safe Moderate Risky

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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

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Ideation Prioritization Execution Learnings Comparable Products Subject Matter Experts User Research Data Analysis Prior Experiments Brainstorming

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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

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1) User-Centric Ideation 4) Focused Learnings 3) High-Velocity Execution 2) Disciplined Prioritization The Growth Experimentation Process

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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

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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

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We don’t know what we don’t know

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Acquisition Channel Mix Healthy Unhealthy

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