Metrics                   Lessons LearnedPhoto: Dstarg   @fmssnr + @andreasklinger > #leancamp
Florian Meissner,      CEO of EyeEm      @fmssnr      Andreas Klinger      Co-Founder a.D. of LOOKK      @andreasklinger  ...
Who here                - wants to run                - runs                - works in                - help              ...
Who here                       is before                       Product/Market Fit?Photo: kenjinakazawa
Startup phases…traction                                                               log(time)           Discovery       ...
Goal of this session:                    Talk about metrics                      in early stage                    because...
What does ittell me aboutmy product?
Vanity VS Actionable           Usually:        “We have 5000  (Total Registered) Users…”  But also numbers that relatestro...
problems in early stage:                1) external traffic messes up your insights                2) product is not ready f...
Metrics are applied differently in              early stages  Discovery       Validation      Efficiency           ScaleQuali...
Early stage metrics are useable for:                Validation of customer feedback                - saying vs doing      ...
Framework:                  AARRRPhoto: Pascal
Example PhotoappAquisition - User registeredActivation - User took a photoRetention - Opened the app again <= 2pmReferral ...
Example PhotoappAquisition - User registeredActivation - User took a photoRetention - Opened the app again <= 2pmReferral ...
Cohort - registration date  WK        acquisition    activation   retention   referral   revenue                          ...
In early stage focus on retention +activationAquisition - User registeredActivation - User took a photoRetention - Opened ...
Retention= people come again= people “do” again= people “buy” again       read: http://danhilltech.tumblr.com/post/       ...
Retention
You focus on retention                         because...               Retention = f(user_happiness)Photo: Marie
Find your Happiness metric!e.g. crashpadder (exit to airbnb)cohorts hosts-happiness by city&timeto create an health/happyn...
Dataschmutz                             A layer of dirt                           that obfoscutates                       ...
Dataschmutze.g. createdby trafficspikes
Dataschmutz - eg spike trafficWK       visitors   acquisition activation   retention   referral   revenue                 ...
Dataschmutz                                Exam              MySugr              is praised as              “beautiful app...
DataschmutzKPIs not drilled down enoughExampleGarmz/LOOKKhad90% activation (votes)but they only voted for friendsinstead o...
DataschmutzCompetitionsCompetitions createadditional ValueProposition.
The process               of user              activationPhoto: きなこ
The process of user activationYour users that are happy and retentive:What action differed them from your lost users?
Example: Twittersignup processHow many times do peopleneed to use Twitter to comeback next month?(7)What did they do?Magic...
KPIs           &       DashboardsPhoto: @fmssr
Good KPIs- Eliminates "Dataschmutz"- Is simple to explain- Focus on retention- To optimize retention focus on activtion- D...
TeamPhoto: fisheyedreams
“If we have data, let’s look at data.If all we have are opinions, let’s go with mine.” -Jim Barksdale, former CEO of Netsc...
TeamClear decision making hierarchyBroken code -> data not trustworthy -> trust lost -> datauselessImplement data thinking...
Read on!Startup metrics for Pirtates by Dace McClurehttp://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-...
Thanks                                 @andreasklinger                                    @fmssnr                       Sl...
Upcoming SlideShare
Loading in...5
×

Metrics in early stage startups - Leancamp Berlin

5,108

Published on

Metrics in early stage startups - Leancamp Berlin

Published in: Business, Economy & Finance

Metrics in early stage startups - Leancamp Berlin

  1. 1. Metrics Lessons LearnedPhoto: Dstarg @fmssnr + @andreasklinger > #leancamp
  2. 2. Florian Meissner, CEO of EyeEm @fmssnr Andreas Klinger Co-Founder a.D. of LOOKK @andreasklinger Hello Berlin. All slides are on www.slideshare.net/andreasklingerPhoto: TTL
  3. 3. Who here - wants to run - runs - works in - help startups?Photo: Dstarg
  4. 4. Who here is before Product/Market Fit?Photo: kenjinakazawa
  5. 5. Startup phases…traction log(time) Discovery Validation Efficiency Scale AcquisitionProblem/Solution Product/Market Company building Source: Steve Blank’s Customer Development
  6. 6. Goal of this session: Talk about metrics in early stage because feels kinda different…Photo: mecca dawn
  7. 7. What does ittell me aboutmy product?
  8. 8. Vanity VS Actionable Usually: “We have 5000 (Total Registered) Users…” But also numbers that relatestronger to your PR bumps than to your product core.“We have 5000 Visitors / Month” is in early stage usually not actionable.
  9. 9. problems in early stage: 1) external traffic messes up your insights 2) product is not ready for market communication, vp, market seg, channels, product - all is yet wrong. So how much does “10% improve really tell you” 3) small data pool of actually useable dataPhoto: Dstarg
  10. 10. Metrics are applied differently in early stages Discovery Validation Efficiency ScaleQualitative QuantitativeValidation Validation Source: Custdev.com
  11. 11. Early stage metrics are useable for: Validation of customer feedback - saying vs doing - did they really use the app? Validation of internal opinions - believing vs knowing - “Our users need/are/do/try…”Photo: dstarg
  12. 12. Framework: AARRRPhoto: Pascal
  13. 13. Example PhotoappAquisition - User registeredActivation - User took a photoRetention - Opened the app again <= 2pmReferral - Share a photo publiclyRevenue - haha
  14. 14. Example PhotoappAquisition - User registeredActivation - User took a photoRetention - Opened the app again <= 2pmReferral - Share a photo publiclyRevenue - hahaTo see progress over time we create groups of users(cohorts) and compare them.
  15. 15. Cohort - registration date WK acquisition activation retention referral revenue twice aPhotoapp registration first photo share … month 1 4000 62,5% 25% 10% 2 8750 65% 23% 9% 3 3500 64% 26% 4% … … … … …
  16. 16. In early stage focus on retention +activationAquisition - User registeredActivation - User took a photoRetention - Opened the app again <= 2pmReferral - Share a photo publiclyRevenue - haharead: http://www.ashmaurya.com/2010/07/3-rules-to-actionable-metrics/
  17. 17. Retention= people come again= people “do” again= people “buy” again read: http://danhilltech.tumblr.com/post/ 12509218078/startups-hacking-a-cohort- analysis-with-google
  18. 18. Retention
  19. 19. You focus on retention because... Retention = f(user_happiness)Photo: Marie
  20. 20. Find your Happiness metric!e.g. crashpadder (exit to airbnb)cohorts hosts-happiness by city&timeto create an health/happyness dashboard
  21. 21. Dataschmutz A layer of dirt that obfoscutates your insightful/useable/real data.Photo: Axel Hala!sz
  22. 22. Dataschmutze.g. createdby trafficspikes
  23. 23. Dataschmutz - eg spike trafficWK visitors acquisition activation retention referral revenue twice aEyeEm downloads registration first photo share … month 1 6000 66% / 4000 62,5% 25% 10% 2 25000 35% / 8750 65% 23% 9% 3 5000 70% / 3500 64% 26% 4%
  24. 24. Dataschmutz Exam MySugr is praised as “beautiful app” example.… => Downloads => Problem: Not all are diabetic They focus on people who activated.
  25. 25. DataschmutzKPIs not drilled down enoughExampleGarmz/LOOKKhad90% activation (votes)but they only voted for friendsinstead of actually using their platform.
  26. 26. DataschmutzCompetitionsCompetitions createadditional ValueProposition.
  27. 27. The process of user activationPhoto: きなこ
  28. 28. The process of user activationYour users that are happy and retentive:What action differed them from your lost users?
  29. 29. Example: Twittersignup processHow many times do peopleneed to use Twitter to comeback next month?(7)What did they do?Magic number 30(Follow 20 people, followedback by 10)How do we get people to 30?Make assumptions, createfeatures and run tests!Watch: http://www.youtube.com/watch?v=L2snRPbhsF0
  30. 30. KPIs & DashboardsPhoto: @fmssr
  31. 31. Good KPIs- Eliminates "Dataschmutz"- Is simple to explain- Focus on retention- To optimize retention focus on activtion- Drill down -> Metrics need to hurt.
  32. 32. TeamPhoto: fisheyedreams
  33. 33. “If we have data, let’s look at data.If all we have are opinions, let’s go with mine.” -Jim Barksdale, former CEO of Netscape
  34. 34. TeamClear decision making hierarchyBroken code -> data not trustworthy -> trust lost -> datauselessImplement data thinking (especially in core dev team)New features need to have a goal. And this goal needs tobe represented by a KPIFocus on a simple and small set of KPIs, dont go crazy(example google analytics)in early stage not data driven but data validation
  35. 35. Read on!Startup metrics for Pirtates by Dace McClurehttp://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-versionActionable Metrics by Ash Mauyrahttp://www.ashmaurya.com/2010/07/3-rules-to-actionable-metrics/Data Science Secrets by DJ Patil - LeWeb London 2012http://www.youtube.com/watch?v=L2snRPbhsF0Twitter sign up processhttp://www.lukew.com/ff/entry.asp?1128Lean startup metrics - @stueccleshttp://www.slideshare.net/stueccles/lean-startup-metricsCohorts in Google Analytics - @serenestudioshttp://danhilltech.tumblr.com/post/12509218078/startups-hacking-a-cohort-analysis-with-google
  36. 36. Thanks @andreasklinger @fmssnr Slides: http://www.slideshare.net/andreasklingerPhoto: Yayoi Yaguchi
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×