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Startup analytics
This document discusses metrics and analytics for startups. It provides examples of metrics to measure at different stages of growth, including empathy, stickiness, virality, revenue, and scale. It emphasizes the importance of choosing one metric that matters for a given business stage and focusing on actionable metrics. Cohort analysis and funnels are presented as useful tools for understanding user behavior over time. Growth hacking techniques from successful startups like Airbnb, Dropbox, and LinkedIn are highlighted. Throughout, the document stresses testing hypotheses and using data and experimentation to optimize business performance.
Startup analytics
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- 3. Looks great! 0 1000 2000 3000 1 23 4 5 Active users 0 2000 4000 6000 8000 1 2 3 4 5 Sign-ups (cum)
- 4. Or not? 0% 20% 40% 60% 80% 100% 2 34 5 Active users (existing) 0% 20% 40% 60% 80% 100% 1 2 3 4 5 Active users by cohort months after they registered
- 5. Disaster or goodbusiness? 500 1000 1500 2000 1 2 3 4 5 New monthly sign-ups • In this fictional case, good flow of new sign-ups keeps the general metrics looking good • These numbers could mean a disaster for some businesses (for ex. monthly subscription) • They can also be OK for certain revenue models (for ex. one-time fee + upsell), but in that case you’d need to look at the acquisition cost
- 6. Vanity Metrics They makeyou feel good, but they don’t offer clear guidance for what to do. -Eric Ries
- 7. The right wayto use analytics: case Twitter Analytics: Twitter learned that users that follow 5-10 others, are more likely to come back. Solution: re-engineered the whole site to get users to follow when they sign up Confidential7
- 8. What does your successlook like?
- 9. Where’s the value? Measureit and the preceeding steps
- 10. Use spreadsheet models tounderstand the logic Useful for finding what to validate, not for proving the success
- 11. Quick’n’Dirty guide tochoosing metrics Not very useful by itself Are we creating value for our customers? Are our users willing to pay for it 1. Anything happening? 2. What works, what doesn’t 3. Is it a business? Sign-ups, downloads, visitors etc. Conversions, active users, cart size, viral co-efficient etc. Revenue, Customer lifetime value etc. Forexample
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- 13. Good metrics are actionableand give focus
- 14. A good metricis: Comparative Understandable Ratio or a rate Changes behavior Helps you to understand how different areas are progressing (time, groups of competitors or users etc.) If your team doesn’t understand the metric, they won’t be able to act on it. Ratios and rates are comparative and usually easier act on. Metric are for learning what is working and how to do better.
- 15. Pick One Metric ThatMatters relevant for your business and stage you’re at Lean Analytics
- 16. One Metric ThatMatters It answers the most important question you have It forces you to draw a line in the sand It focuses the entire company It inspires a culture of experimentation
- 17. Where to focus? Thinkabout your company stage
- 18. Lean Analytics byCroll & Yoskovitz Empathy Stickiness Virality Revenue Scale
- 19. Focus on thingsimportant to the company stage Empathy Problem and solution validation: discover real needs you can solve. Stickiness Engage with customers in a meaningful, valuable way. Virality Grow adoption through virality (inherent, artificial word-of-mouth). Revenue Convince users to pay with optimal pricing Scale Growing through customer acquisition, channel relationships, finding efficiencies, and participating in a market ecosystem.
- 20. Questions for differentstages and business types Business type E-commerce Two-sided marketplace Software as a Service Free mobile app Media User- generated content The really big question Empathy Will they buy enough for enough money from you? Will it solve a pain they’ll pay for? Will they engage with content in a repeatable manner Interviews, qualitative results, quantitative scoring, surveys StageMetrics
- 21. Questions for differentstages and business types Will it grow? Stickiness Will they find you and tell others? Will they sign up, stick around, and tell others? Can you grow traffic to a level that can be profitably monetized?Virality Business type Stickiness Loyalty, conversion Inventory, listings Engagement, churn Downloads, churn, virality Content, spam Traffic, visits, returns Virality CAC, shares, reactivation SEM, sharing Inherent virality, CAC WoM, app ratings, CAC Invites, sharing Content virality, SEM Stage E-commerce Two-sided marketplace Software as a Service Free mobile app Media User- generated content Metrics
- 22. Questions for differentstages and business types Primary source of money Revenue Transactions Active users Ad revenue Scale Business type Revenue Transaction, CLV Transactions, commission Upselling, CAC, CLV CLV, ARPDAU Ads, donations CPE, affiliate %, eyeballs Scale Affiliates, white-label Other verticals API, magic #, mktplace Spinoffs, publishers Analytics, user data Syndication, licenses Stage E-commerce Two-sided marketplace Software as a Service Free mobile app Media User- generated content Metrics
- 23. Know your baseline ie.don’t make stupid decisions based on data
- 24. Some interesting benchmarks •Growth: 5-7% per week (Y Combinator) • User engagement/day: 10% (see Fred Wilson’s 30/10/10 rule) • Monthly churn: 2% (=22% annual churn) • Mailing list effectiveness: 20-30% open rate, 5% click-through rate • Freemium: 2% of your users will actually sign up for the full offering • ARPDAU: $0.01-$0.05 for puzzle, caretaking and simulation games. • Lots of benchmarks, for example, in Lean Analytics book • Find yours!
- 25. Use funnels to understandand drive your customers’ actions
- 26. Startup Metrics forPirates by Dave McClure A Acquisition (how do users find you?) A Activation (do they have a great first experience?) R Retention (do they return?) R Revenue (how do you make money?) R Referral (do users tell others?)
- 27. Use cohorts to findout what’s really happening
- 28. Cohort group of peoplewho share something in common For example, • Conversion rate of people that signed up in week 3 • Retention rate of users after five months • Cart size of people that came via an email campaign • Retention rate of men • Cancelation rate for customer after one week vs. one month • Users based on engagement level (for ex. how many time they use the service, how many service features they use etc.)
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- 30. Mindset of data,creativity, and curiosity allows a growth hacker to accomplish the feat of growing a user base into the millions -Aaron Ginn
- 31. Growth hackers asks“How do I get customers for my product?” and answers with A/B tests, landing pages, viral factor, email deliverability, and Open Graph. Growth hackers make sure virality is embedded at the core of a product. - Andrew Chen
- 32. Airbnb made itreally easy to post the listing on craigslist.com Accessed instantly millions of potential customers Note. Craigslist had no public API Confidential34
- 33. Mailbox application download waitlist showed users how many others were in front of them In six weeks, million users signed up Confidential35
- 34. Dropbox made areferral program with incentives 100k to 4M users in under two years Confidential36
- 35. Hotmail put atagline in each message sent through the service. After five weeks they had 2M users Confidential37 -------- Get your free email at Hotmail.com
- 36. Linkedin gave usersan option to create public profiles. Went from 2M users to 200M Confidential38
- 37. Facebook, for example, enabledusers to put FB widgets on other sites Comments, activity, recommendations, feed, etc. Confidential39
- 38. Twitter learned thatusers that follow 5-10 others, are more likely to come back. They re-engineered the whole site to get users to follow when they sign up Confidential40
- 39. Youtube has madeit really easy to share Youtube videos and embed them on other sites Confidential41
- 40. Growth hacking This iswhat you do Pick a metric to change Find correlation Test causality Optimize the causal factor Does either of the correlated variables really have an impact on the other? Two variables that seem to be associated with each other Metric that is relevant for your company’s stage and model Use the causality to make improvements.
- 41. And always remember correlationdoesn’t necessarily mean causality! Source: www.tylervigen.com
- 42. Contact Topi Järvinen +358 40754 3131 topi.jarvinen@nestholma.com http://www.nestholma.com