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Experimentation @Booking.com
Jorden Lentze
24th of January, 2019 Many thanks to Willem Isbrucker
1. Booking.com, nice to meet you
2. The business impact of experimentation
3. Experimentation @Booking.com
Jorden Lentze
Product manager, Booking.com
● 1.5 year at Booking
● Previous at Google and ABN AMRO
● Conversion Rate Optimization
● 400+ experiments
● Rotterdam
https://www.linkedin.com/in/customerdrivenoptimization/
Timeline.
1996
Founded in Amsterdam
Winterberg
Winterberg
2012
4,000 employees
2016
13,000+ employees
2000
8 employees
OVER
100
NATIONALITIES
2018
17,000+ employees
28 million
total reported listings
43
Languages supported
200+
Offices
OVER
100
NATIONALITIES
161,000,000+
Reviews from real guests
1,550,000+
Room nights booked
every 24 hours
Agenda.
Source: Kleiner Perkins 2018 Internet trends: https://www.statista.com/statistics/277483/market-value-of-the-largest-internet-companies-worldwide/
1. Booking.com, nice to meet you
2. The business impact of experimentation
3. Experimentation @Booking.com
Why?
9/10 experiments fail
for users.
90% of product decisions have an
inconclusive or negative effect on
a product’s primary metric
Source: VWO 2016.
(8.75/10 tests fails according to AppSumo)
90%
10%
4
Evercore Equity Research
https://goo.gl/rFP
“Booking’s utilization of A/B testing has
contributed to Booking enjoying
conversion rates 2-3x higher than the
industry average.”
3
Product Death Cycle.
2
Experimentation at Booking.com
Base.
Which one performed better?
Variant.
Which one performed better?
Base.
Which one performed better?
Variant.
Base.
Which one performed better?
Variant.
Hypothesize &
Experiment.
• Hypothesize
• Calculate power
• Run for prescribed time
• Stop, rerun or Full On
• Iterate
Base.
Variant.
Search
Search
Experiment on everything.
4
Experiment atomically.
3
Interactions.
Experiment on
Everything
Test Atomically
A lot of
experiments!
+ =
1,000+
concurrent tests.
5
Based on [prior] we believe that
changing [condition]
for users [sample] will make
them [outcome].
We will know this when we see
[effect(s)] happen to [metric(s)].
This will be good for customers,
partners and our business
because [motivation].
Idea ≠ Hypothesis.
Hypothesis Template.
3
Idea ≠ Hypothesis.
• All secondary metrics
selected a priori along with
their direction of change to
avoid Texas Sharpshooter
Fallacy
● All experiments should have
run time calculated
beforehand using the power
calculator of your choice.
Or use ours :-)
https://bookingcom.github.io/
powercalculator/
● Experiments should then be
run for the next closest full
week cycle.
Properly Powered.
Full Week Cycles.
Experiments should:
No HIPPOs.
6
Nobody knows.
6
Teams made for
experimentation.
5
Oleksandr
Kaverin
- iOS developer-
George
R.R. Martin
Springthorpe
- UX Copywriter -
Serhii Tostii
Korin
- Back End Developer-
Simona
Damian
- Jr. Product Mk Manager -
Mat-log
Swainson
- Team Lead -
&
- Client Side Developer -
Jorden
Rotterdam
Lentze
- Product Owner -
Alexi
Munoz
- UX Designer-
Annuhh
Zuiker
- Data Scientist -
Les Paul
Bodron
- UX Designer -
Jay
Rambhia
- Android Developer -
Allow 100% access to
data.
3
Data is fuel for
hypotheses.
3
Guidelines, not rules.
3
Embrace failure.
4
Fail fast.
Learn
3
Don’t assume
correlation.
Don’t assume
reproducibility.
3
Experiment everywhere.
Product
Development.
Data.
Analyze.
Hypothesize.
Experiment.
Iterate.
The Data-Informed Decision Cycle.
Feeding the
experiment engine.
CRO is part of every
team.
Winterberg - At Booking customers drive the product
Most democratic way
to design a website.
Go where the
experiment takes you.
Thank you.
https://blog.booking.com/
Thanks to
Willem Isbrucker
Senior Product Owner, Booking.com
● Search products at
Booking.com
● 2 years at Booking
● Many more in Product
● 1000+ experiments
www.linkedin.com/in/willemisbrucker

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Experimentation as a growth strategy at Booking.com