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7 Practical Tips
on Lean Analytics
Janne Aukia — 17 Feb 2015
1. Lean Analytics
requires a Lean project
Illustration from commons.wikimedia.org/wiki/File:Kepler-solar-system-1.png
Challenging for a consultancy?
Lean Analytics works well with
Lean Startup, Lean UX and

Agile projects
Question designs, question
authorities, ask difficult questions,
be prepared to kill features.
Requires freedom to experiment
2. Write down a success
metric for every feature
Was this feature used more than
Google+ login?
If feature isn’t successful, 

just kill it.
Measure only actionable
metrics.
Is the feature for acquisition,
retention or revenue?
3. You need lots of
users for an A/B test
Typically at least 10k events,
such as visits or people using a
feature.
Doesn’t work for small
startups.
4. Make big changes
Illustration from http://quod.lib.umich.edu/m/moa/agb8710.0001.001/26
If you cannot see the changes
from 2 meters away, most likely
your AB test won’t either.
Google A/B tested 41 shades of
blue. Don’t do that — leads to
local optimum.
Illustration from http://www.doxsey.net/blog/too-practically-minded-to-be-of-any-theological-good/
5. Measure your tests
correctly
Never terminate early

a running test
Use a split test calculator, 

for example:
http://getdatadriven.com/ab-significance-test
6. Push through radical
changes with A/B
7. Use the right tools
Google Analytics can be used for
tracking events but it is
painful.
Mixpanel more suited for the
job. Consider Keen.io, Heap as
well.
1.Lean Analytics
requires a Lean
project
2.Specify success
metric for every
feature
3.You need lots of
users for an A/B
test
4.Make big changes
5.Measure your tests
correctly
6.Push through radical
changes with A/B
7.Use the right tools
Summary

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7 Practical Tips on Lean Analytics

  • 1. 7 Practical Tips on Lean Analytics Janne Aukia — 17 Feb 2015
  • 2. 1. Lean Analytics requires a Lean project Illustration from commons.wikimedia.org/wiki/File:Kepler-solar-system-1.png
  • 3. Challenging for a consultancy? Lean Analytics works well with Lean Startup, Lean UX and
 Agile projects Question designs, question authorities, ask difficult questions, be prepared to kill features. Requires freedom to experiment
  • 4. 2. Write down a success metric for every feature
  • 5. Was this feature used more than Google+ login? If feature isn’t successful, 
 just kill it. Measure only actionable metrics. Is the feature for acquisition, retention or revenue?
  • 6. 3. You need lots of users for an A/B test
  • 7. Typically at least 10k events, such as visits or people using a feature. Doesn’t work for small startups.
  • 8. 4. Make big changes Illustration from http://quod.lib.umich.edu/m/moa/agb8710.0001.001/26
  • 9. If you cannot see the changes from 2 meters away, most likely your AB test won’t either. Google A/B tested 41 shades of blue. Don’t do that — leads to local optimum. Illustration from http://www.doxsey.net/blog/too-practically-minded-to-be-of-any-theological-good/
  • 10. 5. Measure your tests correctly
  • 11. Never terminate early
 a running test Use a split test calculator, 
 for example: http://getdatadriven.com/ab-significance-test
  • 12. 6. Push through radical changes with A/B
  • 13.
  • 14. 7. Use the right tools
  • 15. Google Analytics can be used for tracking events but it is painful. Mixpanel more suited for the job. Consider Keen.io, Heap as well.
  • 16. 1.Lean Analytics requires a Lean project 2.Specify success metric for every feature 3.You need lots of users for an A/B test 4.Make big changes 5.Measure your tests correctly 6.Push through radical changes with A/B 7.Use the right tools Summary