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A/B Testing powered by Big
Data in Booking.com
Saurabh Goyal | February 2018
1
Structure
● A/B testing
● Big Data
● Example
A/B testing
What is it?
3
Which button color is
the best?
OR ?
4
Let the users
decide!
5
Experiment flow.
50%
50%
10% conversion
20% conversion Win!
Lose.
6
10% conversion
20% conversion
What does “the best” mean?
50%
50% Win!
Lose.
7
Metrics:
● Conversion
● Click-through rate
● Logins
● Bounce rate
... anything your business
wants the customers to do!
8
Additional metrics:
● Clicked on an element
● Clicked on a different
element
● Spent time on the page
● Scrolled down
Helps to learn about user
behavior.
9
Building a hypothesis
10
“If I implement X,
the users will do Y,
and it’s good because Z”
11
“If I... add a cat to my presentation,
the listeners will... say AAAaaw,
and it’s good because... they will
remember my talk”
12
13
Success:
Congratulate yourself!
Continue on topic.
Where else can you
apply the same
approach?
14
Failure:
That’s unfortunate.
But don’t give up just
yet!
Analyze what went
wrong.
15
Repeat.
16
17
RepeatAnalysisExperimentMetrics
Steps to a successful experiment:
Hypothesis
18
Learning
is the most important thing
19
A/B testing:
not only button colors
20
Big Data
Sold Incremental
Inventory
22
● Over a million properties
● 1000 Inventory events per minute.
● 3.9 TB data from Inventory events.
23
Data Volume
● Mysql replicator
● Kafka
● Hbase
● RTM
● Oozie
24
Tech used
25
Flow chart
Mysql table
changes
Example
26
User research
27
Brainstorm
28
Almost sold out
29
Our challenges
30
Defining
customer problems
is hard.
31
Metrics
32
Number of Iterations
Thank you!
Saurabh Goyal | February 2017
34
Questions?
35

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A/B testing powered by Big data - Saurabh Goyal, Booking.com