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Analytics for startups

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Analytics for startups

  1. 1. Analytics for Startups Lars Lofgren - April 2014
  2. 2. Hit me up @larslofgren
  3. 3. 1 The data problems that startups face We’ll cover… 2 Gateway metrics 3 4 gateways and the metrics for each #KISSwebinar
  4. 4. I’m not going to spend any time on Google Analytics.
  5. 5. How healthy is this business?
  6. 6. 1 MRR, Churn, LTV, acquisition cost It’d be great to track metrics like these: 2 Virality, DAU, MAU 3 Average order value, repurchase rate #KISSwebinar 4 Funnels and conversions
  7. 7. But you don’t have any data yet
  8. 8. Your data is in a constant rate of decay
  9. 9. You data is messy
  10. 10. Use metrics that measure your biggest problem. Ignore the rest.
  11. 11. Gateway Metrics
  12. 12. When picking metrics, always ask yourself: What’s my biggest constraint right now and which metric will tell me if I’m making progress?
  13. 13. You need to do the right things in the right order.
  14. 14. Gateway #1: Is your idea any good?
  15. 15. Your main constraint: Getting anyone to care about your idea.
  16. 16. Your main metric: Get someone to pay or use your product regularly.
  17. 17. Bad metrics for this gateway: 1 Asking people if they’ll pay 2 AdWords clicks 3 Beta or waiting list signups 4 Traffic
  18. 18. Gateway #2: Is your product good enough?
  19. 19. Your main constraint: Having a product that’s good enough to build a business on.
  20. 20. Your main metric: Ask 500 users the Product/Market Fit Question
  21. 21. What is the P/M Fit Question? 1 Very disappointed 2 Somewhat disappointed 3 Not disappointed (it isn’t really that useful) How would you feel if you could no longer use [your product]?
  22. 22. Your goal for the P/M Fit Question: At least 40% of users should say “Very disappointed.” *Sean Ellis and Hiten Shah get credit for this one.
  23. 23. How do you get to the first 500 users/customers? Hustle.
  24. 24. The P/M Fit Question isn’t perfect, verify with a retention metric.
  25. 25. Gateway #3: Can you grow?
  26. 26. Your main constraint: Acquiring customers consistently from at least one channel.
  27. 27. You have plenty of options to choose from: 1 Inbound (Google, Content, Social) 2 Paid (PPC, Affiliates) 3 Virality (Invites, Referrals)
  28. 28. Pick just one to start Work on your channel for at least 3 months. Assume it’ll work and get the resources needed to execute.
  29. 29. Your main metrics: Your main business metric and acquisition funnel.
  30. 30. Main business metrics: 1 SaaS: Monthly Recurring Revenue 2 Ecommerce: Monthly Revenue 3 Consumer Tech: Monthly Active Users
  31. 31. SaaS Funnel
  32. 32. Ecommerce Funnel
  33. 33. Consumer Tech Funnel
  34. 34. Why not cost per acquisition or lifetime value? You have no idea how much it costs to acquire customers or how much they’ll spend (yet).
  35. 35. Gateway #4: Do you have a stable model?
  36. 36. Your main constraint: In order to keep scaling, you need a stable model for your business.
  37. 37. Your main metrics: Depends entirely on what business model you have.
  38. 38. The SaaS Model 1 LTV is at least 3x acquisition cost 2 Recover acquisition cost within 12 months 3 Get monthly churn below 2%
  39. 39. The Ecommerce Model 1 2 3 It’s all about profit margin.
  40. 40. The Consumer Tech Model 1 Virality > 1 2 Usage 3 out of 7 days 3 30% of users active day after signup 4 Organic growth of 100s signups/day. 5 Clear path to 100,000+ users *Andrew Chen’s “Zero to Product/Market Fit”
  41. 41. Find someone in your industry that knows the key benchmarks.
  42. 42. Finally, get serious with data.
  43. 43. If you have a sales team, pile data into your CRM.
  44. 44. If consumer tech, do everything in-house.
  45. 45. Google Analytics plus an internal database will take you far.
  46. 46. Start with constraints, hack together what you need to measure them.
  47. 47. How to get data you really need: 1 One team owns data quality. 2 Hire a data engineer. 3 Clean up and integrate your data. 4 Use customer analytics. 5 Build a Growth Team.
  48. 48. Q&A Time! Lars Lofgren @larslofgren llofgren@kissmetrics.com