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6 Guidelines for A/B Testing
Emily Robinson
@robinson_es
Experimentation Process
Prioritizing Creating Analyzing
Decision-
Making
Experimentation Process
Prioritizing Creating Analyzing
Decision-
Making
Three tests idea to increase registration
Test Idea 3: Revamp the course
pages
Test Idea 1: Preload sign-up
modal on our learning platform
Test Idea 2: Add recommended
courses to top of search page
One way to pick …
Prioritizing: Estimate number of new conversion per day
What’s the population of your test idea?
What’s the current conversion rate?
What’s your estimated increase?
Then: Multiply to get new daily conversions
Gathering numbers
Page Visitors per Day
Learning Platform 70,000
Search page 10,000
Course page 40,000
Gathering numbers
Page Visitors per Day Conversion Rate
Learning Platform 70,000 2%
Search page 10,000 21%
Course page 40,000 10%
Gathering numbers
Page Visitors per Day Conversion Rate Estimated Impact
Learning Platform 70,000 2% 5%
Search page 10,000 21% 2%
Course page 40,000 10% 3%
Gathering numbers
Page Visitors per Day Conversion Rate Estimated Impact
Learning Platform 70,000 2% 5%
Search page 10,000 21% 2%
Course page 40,000 10% 3%
VD x CR EIx = NCD
Calculating Impact
Page Visitors per Day Conversion Rate Estimated Impact New Conversions
per Day
Learning Platform 70,000 2% 5% 70
Search page 10,000 21% 2% 42
Course page 40,000 10% 3% 120
VD x CR EIx = NCD
Picking one test
Page Visitors per Day Conversion Rate Estimated Impact New Conversions
per Day
Homepage 70,000 2% 5% 70
Pricing page 10,000 21% 2% 42
Course page 40,000 10% 3% 120
VD x CR EIx = NCD
Experimentation Process
Prioritizing Creating Analyzing
Decision-
Making
Creating: Run a Power Analysis
• 80% Power: if there’s an effect of this size, there’s an 80% chance
you will detect it
• How long will you need to run your experiment for to get 80%
power?
Power Calculator
bookingcom.github.io/powercalculator
Deciding on changes to try
What could
improve
registration on
the course page?
Add registration form on page?
Add user testimonials?
Preload registration modal?
Add company logos?
Add video?
Why not all of them!
… Two Months Later
Oh no, we spent two
months working and
registrations didn’t go
up! Why didn’t it
work?
Data Scientist:
Creating: Work on Smaller, Incremental Tests
Creating: Work on Smaller, Incremental Tests
Creating: Work on Smaller, Incremental Tests
Picking one change
add registration form on page
Run it and dump the data on the data scientist?
We finished the
experiment! Can you
analyze it for us?
“To consult the statistician after
an experiment is finished is often
merely to ask [them] to conduct a
post mortem examination.
[They] can perhaps say what the
experiment died of.”
- Sir R.A. Fisher
Creating: Have a Data Scientist Involved
• Can make sure you’re tracking the right metrics
• Can help with the power calculation
• Can help iterate on ideas
Experimentation Process
Prioritizing Speccing Analyzing
Decision-
Making
Things that have happened
➔ People are put in both control and treatment
➔ People in the experiment have no page views
➔ People have multiple experiment starts in the same group
➔ Experiment starts didn’t have cookies (so we couldn’t track user)
➔ People weren’t split evenly between control and treatment
Analyzing: Have Health Checks
Analyzing: Have Health Checks
* These are fake numbers
Analyzing: Have Health Checks
Experimentation Process
Prioritizing Speccing Analyzing
Decision-
Making
Decision-Making: Be careful of launching on “neutral”
Decision-Making: Be careful of launching on “neutral”
• What is the technical complexity and debt you’re adding?
• Is it a foundational feature?
• Could be a negative impact too small to detect
• Decide beforehand whether you’ll launch it on “neutral”
Conclusion
Experimentation Process
Prioritizing
Creating
Analyzing
Decision-
Making
• Calculate potential increase
• Run a power calculation
• Work on smaller, incremental tests
• Have a Data Scientist involved
• Monitor health metrics
• Be careful of launching on “neutral”
Research papers
➔ Controlled experiments on the web: survey and practical guide (2008)
➔ Seven rules of thumb for web site experiments (2014)
➔ A dirty dozen: twelve common metric interpretation pitfalls in online
controlled experiments (2017)
➔ Democratizing online controlled experiments at Booking.com (2017)
Blog posts and presentations
➔ Design for Continuous Experimentation by Dan McKinley
➔ Scaling Airbnb’s Experimentation Platform by Jonathan Parks
➔ Please, please don’t A/B test that by Tal Raviv
➔ How Etsy handles peeking in A/B Testing by Callie McRee and
Kelly Shen
Thank you!
hookedondata.org
@robinson_es

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6 Guidelines for A/B Testing