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Introduction to Lean Analytics for Lean Startup Circle SF

  1. An Introduction to Lean Analytics Ben Yoskovitz @byosko
  2. A bit about me... 1996 - 2006 2007 - 2010 2010 - 2011 2011 - ....
  3. Why did I write it? h"p://­‐content/uploads/2012/05/Monkeys-­‐typing.jpg
  4. We’re all liars.
  5. The basics of Lean Startup Everyone’s idea is the best right? People love this part! (but that’s not always a good thing) This is where things fall apart. No data, no learning.
  6. Analytics is the measurement of movement towards your business goals. What is analytics?
  7. In a startup, the purpose of analytics is to iterate to product/market fit before the money runs out. And for startups?
  8. Good Metrics are: 1 Understandable 4 Behavior Changing 2 Comparative Active Users vs. Active Users/month 3 Ratio / Rate % Monthly Active Users
  9. If it won’t change how you behave, it’s a bad metric. If a metric won’t change how you behave, it’s a h"p://
  10. h"p:// Types of Metrics
  11. Warm and fuzzy. Cold and hard. Unstructured, anecdotal, revealing, hard to aggregate. Numbers and stats; hard facts but less insight. Qualitative vs. Quantitative
  12. Discover qualitatively. Prove quantitatively. Quantitative vs. qualitative data
  13. Speculative, tries to find unexpected or interesting insights. Predictable, keeps you abreast of normal, day-to-day operations. The cool stuff. The necessary stuff. Exploratory Reporting vs.
  14. Finding the answer in the data •Started as Circle of Friends •Leveraged Facebook early •Grew to 10M users But engagement sucked!
  15. Moms are crazy! (in a good way) Engagement solved! • Messages to one another were on average 50% longer. • 115% more likely to attach a picture to a post they wrote. • 110% more likely to engage in a threaded (i.e. deep) conversation. • Friends, once invited, were 50% more likely to become engaged users. • 180% more likely to click on Facebook news feed items. • 60% more likely to accept invitations to the app.
  16. Historical metric that shows you how you’re doing: reports the news. Number today that shows a metric tomorrow: makes the news. Try and get here.Start here. Lagging Leading vs.
  17. h"p:// Analytical Superpowers (or what the heck is growth hacking?)
  18. 1 10 100 1000 10000 Ice cream consumption Drownings Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
  19. Summer Ice cream consumption Drowning Correlated Causal Causal Two variables that change in similar ways, perhaps because they’re linked to something else. Correlated An independent factor that directly impacts a dependent one. Causal vs.
  20. Correlation lets you predict the future Causality lets you change the future “I will have 420 engaged users and 75 paying customers next month.” “If I can make more first-time visitors stay on for 17 minutes I will increase sales in 90 days.” Find correlation Test causality Optimize the causal factor Causality is a superpower, because it lets you change the future.
  21. Lean Analytics Framework h"p://
  22. Your Business + Stage What business are you in? What stage are you at? •E-Commerce •SaaS •Free Mobile App •2-Sided Marketplace •Media •User-Generated Content •Empathy •Stickiness •Virality •Revenue •Scale
  23. business models
  24. The 2-Sided Market Customer Lifecycle Visits SELLERS Seller visits Account created Listings created Listing count New listings/day Fraud rate Fraudulent / Flagged Results % blank searches Additional Services Other revenue Conversion rates Delivery Transaction Click-throughs Good results Conversions Shortlist Buyer rates Seller Ratings, rate Repeat Seller Account Cancelled Listing Expired Disengagement Churn RateSeller churn Seller lifetime value Visits BUYERS Signup rate Account created Notifications Disengagement / opt-out Repeat Buyer Buyer lifetime value Email bounce Open Clicks Buyer churn Click-through rate Searches Searches / visit Seller rates Buyer Ratings, rate One-time purchase Gross revenue Net revenue
  25. 2-Sided Marketplaces 1 Do things that don’t scale 2 Focus on the money 5 The scale has to be enormous 3 Seller quality matters 4 Find extra revenue sources
  26. lean analytics stages
  27. EMPATHY STICKINESS GROWTHRATE VIRALITY REVENUE SCALE Lean Analytics Stages I’ve found a real, poorly-met need that a reachable market faces. I’ve figured out how to solve the problem in a way they will adopt and pay for. I’ve built the right product/features/ functionality that keeps users around. The users and features fuel growth organically and artificially. I’ve found a sustainable, scalable business with the right margins in a healthy ecosystem. “Gates” needed to move forward
  28. •Stage: Empathy •Model: UCG/Mobile •Real-time Q&A platform tied to locations •Needed to find out if a core behavior-- answering questions about a place--happened enough to make the business real Localmind hacks Twitter
  29. Localmind hacks Twitter •Before writing a line of code, they wanted to answer this question •This was their biggest risk: if questions went unanswered, the experience would suck Would people answer questions? Test results •The response rate to tweeted questions was very high •Good enough proxy to de-risk the solution and convince the team to continue Ran an experiment on Twitter •Tracked geolocated tweets in Time Square •Sent @ messages to people who had just tweeted, asking a question about the area
  30. •Stage: Empathy / Stickiness •Model: E-Commerce •Eco-friendly prints of your photos •Originally tied exclusively to Instagram and built a custom InstaOrder feature Static Pixels simplifies to focus on immediate success
  31. ★ 2x transactions ★ lower bounce rate ★ sign-in goals increased with InstaOrder Click checkout Sign into PayPal Confirmation page Confirm order Back to PayPal Authorize pre- approved payments Success page without InstaOrder Click checkout Sign into PayPal Confirmation page Confirm order Success page Optimize for 1st time purchases or repeat orders?
  32. skip steps at your own risk
  33. One Metric That Matters. How It All Comes Together The business you’re in E-Com SaaS Mobile 2-Sided Media UCG Empathy Stickiness Virality Revenue Scale Thestageyou’reat
  34. •Stage: Scale •Model: SaaS •SEO toolkit (product suite) •Reduced KPIs to focus on Net Adds SEOMoz reduces the KPIs it tracks
  35. If Net Adds: Why & Next Steps: Net Adds = “business health” indicator •Was a marketing campaign successful? •Were customer complaints lowered? •Was a product upgrade valuable? • Can we acquire more valuable customers? •What product features can increase engagement? • Can we improve customer support? •Are the new customers not the right segment? • Did a marketing campaign fail? • Did a product upgrade fail somehow? • Is customer support falling apart?
  36. Choose only one metric and draw a line in the sand. Choosing your OMTM isn’t enough...
  37. •Stage: Virality •Model: Mobile app •Social network around the past •Focused on virality (but not the viral coefficient) Timehop aims for virality through content sharing
  38. • Focused on % of daily active users that share content • Aiming for 20-30% of daily active users to share content “All that matters now is virality. Everything else—be it press, publicity stunts or something else—is like pushing a rock up a mountain: it will never scale. But being viral will.” - Jonathan Wegener, co-founder The One Metric That Matters: Content sharing
  39. Some interesting benchmarks Growth 5% / week (revenue or active users) Churn 2% / month Engaged visitors 30% monthly users 10% daily users Time on site 17 minutes Page load time < 5 seconds CLV:CAC 3:1 Mobile file size < 50MB Free to paid 2% of free users
  40. Lean Analytics cycle h"p://
  41. Identify a key business problem, pick the OMTM, draw a line in the sand, and get started. Time to experiment
  42. Draw a new line Pivot or give up Try again Success! Did we move the needle? Measure the results Make changes in production Design a test Hypothesis With data: find a commonality Without data: make a good guess Find a potential improvement Draw a linePick a KPI The Lean Analytics Cycle
  43. Thank you. @byosko ORDER! follow me. subscribe. email me.