http://leananalyticsbook.comAn Introductionto Lean AnalyticsBen Yoskovitz@byosko
A bit about me...http://instigatorblog.com1996 - 20062007 - 20102010 - 20112011 - ....
Why did I write it?h"p://loreindustries.com/wp-­‐content/uploads/2012/05/Monkeys-­‐typing.jpg
We’re all liars.
The basics of Lean StartupEveryone’s idea isthe best right?People lovethis part!(but that’s not always agood thing)This is...
Analytics is the measurement ofmovement towards yourbusiness goals.What is analytics?
In a startup, the purpose of analyticsis to iterate to product/market fitbefore the money runs out.And for startups?
Good Metrics are:1 Understandable4 Behavior Changing2 ComparativeActive Users vs.Active Users/month3 Ratio / Rate% Monthly...
If it won’t changehow you behave,it’s abadmetric.If a metric won’t change howyou behave, it’s ah"p://www.flickr.com/photos/...
h"p://www.flickr.com/photos/maCmaCla/3822631755/Types of Metrics
Warm and fuzzy. Cold and hard.Unstructured,anecdotal,revealing, hard toaggregate.Numbers and stats;hard facts but lessinsi...
Discover qualitatively.Prove quantitatively.Quantitative vs. qualitative data
Speculative, tries tofind unexpected orinteresting insights.Predictable, keepsyou abreast ofnormal, day-to-dayoperations.Th...
Finding the answer in the data•Started as Circle of Friends•Leveraged Facebook early•Grew to 10M usersBut engagement sucked!
Moms are crazy!(in a good way)Engagement solved!• Messages to one another were on average 50% longer.• 115% more likely to...
Historical metricthat shows youhow you’re doing:reports the news.Number today thatshows a metrictomorrow: makesthe news.Tr...
h"p://www.flickr.com/photos/bloke_with_camera/401812833/sizes/o/in/photostream/Analytical Superpowers(or what the heck is g...
110100100010000Ice cream consumption DrowningsJan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
SummerIce creamconsumptionDrowningCorrelatedCausalCausalTwo variables thatchange in similar ways,perhaps becausethey’re li...
Correlation lets youpredict the futureCausality lets youchange the future“I will have 420 engaged usersand 75 paying custo...
Lean Analytics Frameworkh"p://www.flickr.com/photos/ikhlasulamal/2331176652/
Your Business + StageWhat businessare you in?What stageare you at?•E-Commerce•SaaS•Free Mobile App•2-Sided Marketplace•Med...
business models
The 2-Sided Market Customer LifecycleVisitsSELLERSSellervisitsAccount createdListings createdListing countNew listings/day...
2-Sided Marketplaces1 Do things that don’t scale2 Focus on the money5 The scale has to be enormous3 Seller quality matters...
lean analytics stages
EMPATHYSTICKINESSGROWTHRATEVIRALITYREVENUESCALELean AnalyticsStagesI’ve found a real, poorly-met need thata reachable mark...
•Stage: Empathy•Model: UCG/Mobile•Real-time Q&A platform tied to locations•Needed to find out if a core behavior--answering...
Localmind hacks Twitter•Before writing a line of code, they wanted to answer this question•This was their biggest risk: if...
•Stage: Empathy / Stickiness•Model: E-Commerce•Eco-friendly prints of your photos•Originally tied exclusively to Instagram...
★ 2x transactions★ lower bounce rate★ sign-in goals increasedwith InstaOrderClick checkoutSign into PayPalConfirmation page...
skip steps at yourown risk
One MetricThat Matters.How It All Comes TogetherThe business you’re inE-Com SaaS Mobile 2-Sided Media UCGEmpathyStickiness...
•Stage: Scale•Model: SaaS•SEO toolkit (product suite)•Reduced KPIs to focus on Net AddsSEOMoz reduces the KPIs ittracks
If Net Adds: Why & Next Steps:Net Adds = “business health”indicator•Was a marketing campaign successful?•Were customer com...
Choose only one metric anddraw a line in the sand.Choosing your OMTM isn’t enough...
•Stage: Virality•Model: Mobile app•Social network around the past•Focused on virality (but not theviral coefficient)Timehop...
• Focused on % of daily active users thatshare content• Aiming for 20-30% of daily active usersto share content“All that m...
Some interesting benchmarksGrowth5% / week (revenue or activeusers)Churn2% / monthEngaged visitors30% monthly users10% dai...
Lean Analytics cycleh"p://www.flickr.com/photos/jrodmanjr/4728457415/
Identify a key business problem,pick the OMTM, draw a line in thesand, and get started.Time to experiment
Draw a new linePivot orgive upTry againSuccess!Did we move theneedle?Measure theresultsMake changes inproductionDesign a t...
Thank you.byosko@gmail.com@byoskoORDER!follow me.instigatorblog.comleananalyticsbook.comsubscribe.email me.
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Introduction to Lean Analytics for Lean Startup Circle SF

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An introduction to Lean Analytics for the Lean Startup Circle SF event. Covers the basic topics of analytics, Lean Analytics framework, and a number of case studies from companies such as Circle of Friends, Localmind, Static Pixels and more.

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Transcript of "Introduction to Lean Analytics for Lean Startup Circle SF"

  1. 1. http://leananalyticsbook.comAn Introductionto Lean AnalyticsBen Yoskovitz@byosko
  2. 2. A bit about me...http://instigatorblog.com1996 - 20062007 - 20102010 - 20112011 - ....
  3. 3. Why did I write it?h"p://loreindustries.com/wp-­‐content/uploads/2012/05/Monkeys-­‐typing.jpg
  4. 4. We’re all liars.
  5. 5. The basics of Lean StartupEveryone’s idea isthe best right?People lovethis part!(but that’s not always agood thing)This is where thingsfall apart.No data, nolearning.
  6. 6. Analytics is the measurement ofmovement towards yourbusiness goals.What is analytics?
  7. 7. In a startup, the purpose of analyticsis to iterate to product/market fitbefore the money runs out.And for startups?
  8. 8. Good Metrics are:1 Understandable4 Behavior Changing2 ComparativeActive Users vs.Active Users/month3 Ratio / Rate% MonthlyActive Users
  9. 9. If it won’t changehow you behave,it’s abadmetric.If a metric won’t change howyou behave, it’s ah"p://www.flickr.com/photos/circasassy/7858155676/
  10. 10. h"p://www.flickr.com/photos/maCmaCla/3822631755/Types of Metrics
  11. 11. Warm and fuzzy. Cold and hard.Unstructured,anecdotal,revealing, hard toaggregate.Numbers and stats;hard facts but lessinsight.Qualitativevs.Quantitative
  12. 12. Discover qualitatively.Prove quantitatively.Quantitative vs. qualitative data
  13. 13. Speculative, tries tofind unexpected orinteresting insights.Predictable, keepsyou abreast ofnormal, day-to-dayoperations.The cool stuff. The necessary stuff.Exploratory Reportingvs.
  14. 14. Finding the answer in the data•Started as Circle of Friends•Leveraged Facebook early•Grew to 10M usersBut engagement sucked!
  15. 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. 16. Historical metricthat shows youhow you’re doing:reports the news.Number today thatshows a metrictomorrow: makesthe news.Try and get here.Start here.Lagging Leadingvs.
  17. 17. h"p://www.flickr.com/photos/bloke_with_camera/401812833/sizes/o/in/photostream/Analytical Superpowers(or what the heck is growth hacking?)
  18. 18. 110100100010000Ice cream consumption DrowningsJan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
  19. 19. SummerIce creamconsumptionDrowningCorrelatedCausalCausalTwo variables thatchange in similar ways,perhaps becausethey’re linked tosomething else.CorrelatedAn independent factorthat directly impacts adependent one.Causalvs.
  20. 20. Correlation lets youpredict the futureCausality lets youchange the future“I will have 420 engaged usersand 75 paying customers nextmonth.”“If I can make more first-timevisitors stay on for 17 minutes Iwill increase sales in 90 days.”Find correlation Test causalityOptimize thecausal factorCausality is a superpower, because it letsyou change the future.
  21. 21. Lean Analytics Frameworkh"p://www.flickr.com/photos/ikhlasulamal/2331176652/
  22. 22. Your Business + StageWhat businessare you in?What stageare you at?•E-Commerce•SaaS•Free Mobile App•2-Sided Marketplace•Media•User-Generated Content•Empathy•Stickiness•Virality•Revenue•Scale
  23. 23. business models
  24. 24. The 2-Sided Market Customer LifecycleVisitsSELLERSSellervisitsAccount createdListings createdListing countNew listings/dayFraud rateFraudulent / FlaggedResults% blank searchesAdditional ServicesOther revenueConversion ratesDeliveryTransactionClick-throughsGood resultsConversionsShortlistBuyer rates SellerRatings, rateRepeat SellerAccount Cancelled Listing Expired DisengagementChurn RateSeller churnSeller lifetime valueVisitsBUYERSSignup rateAccount createdNotificationsDisengagement /opt-outRepeat BuyerBuyer lifetime valueEmail bounceOpenClicksBuyerchurnClick-through rateSearchesSearches / visitSeller ratesBuyerRatings, rateOne-timepurchaseGross revenueNet revenue
  25. 25. 2-Sided Marketplaces1 Do things that don’t scale2 Focus on the money5 The scale has to be enormous3 Seller quality matters4 Find extra revenue sources
  26. 26. lean analytics stages
  27. 27. EMPATHYSTICKINESSGROWTHRATEVIRALITYREVENUESCALELean AnalyticsStagesI’ve found a real, poorly-met need thata reachable market faces.I’ve figured out how to solve theproblem in a way they will adopt andpay for.I’ve built the right product/features/functionality that keeps users around.The users and features fuel growthorganically and artificially.I’ve found a sustainable, scalablebusiness with the right margins in ahealthy ecosystem.“Gates” needed tomove forward
  28. 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--happenedenough to make the business realLocalmind hacks Twitter
  29. 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 suckWould 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 continueRan 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. 30. •Stage: Empathy / Stickiness•Model: E-Commerce•Eco-friendly prints of your photos•Originally tied exclusively to Instagram andbuilt a custom InstaOrder featureStatic Pixels simplifies to focus onimmediate success
  31. 31. ★ 2x transactions★ lower bounce rate★ sign-in goals increasedwith InstaOrderClick checkoutSign into PayPalConfirmation pageConfirm orderBack to PayPalAuthorize pre-approved paymentsSuccess pagewithout InstaOrderClick checkoutSign into PayPalConfirmation pageConfirm orderSuccess pageOptimize for 1st time purchases orrepeat orders?
  32. 32. skip steps at yourown risk
  33. 33. One MetricThat Matters.How It All Comes TogetherThe business you’re inE-Com SaaS Mobile 2-Sided Media UCGEmpathyStickinessViralityRevenueScaleThestageyou’reat
  34. 34. •Stage: Scale•Model: SaaS•SEO toolkit (product suite)•Reduced KPIs to focus on Net AddsSEOMoz reduces the KPIs ittracks
  35. 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. 36. Choose only one metric anddraw a line in the sand.Choosing your OMTM isn’t enough...
  37. 37. •Stage: Virality•Model: Mobile app•Social network around the past•Focused on virality (but not theviral coefficient)Timehop aims for virality throughcontent sharing
  38. 38. • Focused on % of daily active users thatshare content• Aiming for 20-30% of daily active usersto share content“All that matters now is virality. Everything else—be itpress, publicity stunts or something else—is likepushing a rock up a mountain: it will never scale. Butbeing viral will.” - Jonathan Wegener, co-founderThe One Metric That Matters:Content sharing
  39. 39. Some interesting benchmarksGrowth5% / week (revenue or activeusers)Churn2% / monthEngaged visitors30% monthly users10% daily usersTime on site17 minutesPage load time< 5 secondsCLV:CAC3:1Mobile file size< 50MBFree to paid2% of free users
  40. 40. Lean Analytics cycleh"p://www.flickr.com/photos/jrodmanjr/4728457415/
  41. 41. Identify a key business problem,pick the OMTM, draw a line in thesand, and get started.Time to experiment
  42. 42. Draw a new linePivot orgive upTry againSuccess!Did we move theneedle?Measure theresultsMake changes inproductionDesign a testHypothesisWith data:find acommonalityWithout data:make a goodguessFind a potentialimprovementDraw a linePick a KPIThe Lean Analytics Cycle
  43. 43. Thank you.byosko@gmail.com@byoskoORDER!follow me.instigatorblog.comleananalyticsbook.comsubscribe.email me.

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