This document discusses using a data-driven approach to user experience (UX). It recommends setting goals and key performance indicators (KPIs), choosing analytics tools to measure and analyze user behavior, and then optimizing the UX based on insights. Examples of KPIs include the percentage of users who complete purchases or conversions. Data should be broken down by user segments to understand differences in behavior. Behavioral analytics can provide insights into user flows and reasons for actions like cancellations. Common tools mentioned include Google Analytics for trends and basic metrics and more advanced tools for behavioral analysis.

1. Data Driven UX
Amit Levi
VP, Head of Products @ CoolaData
webinfo@cooladata.com

2. What Do You Think
About This Page?

3. What Do You Think
About This Page?
What is the GOAL of this page ?

4. KPI -
75% of users who initiated an order to complete it
Segment -
Breakdown by segments showed a difference
when comparing new vs. returning users
Behavioral -
Looking at path analysis of new users identified
the churn points in the flow
UX Results -
Added social login button to the register page
83%41%
New Returning
View cart Checkout Register Chrun
66%
Checkout Completion
Ratio

5. What Do You Think
About This Page?
What is the GOAL of this page ?

6. What will we cover?
● Why be data driven
● How to be data driven
● What tools to use

7. Why be data driven

8. Why be data driven
The Path to Better Decisions, in One Cute Graph
by ANDREW MCAFEE on MAY 30, 2013

9. What will we cover?
● Why be data driven
● How to be data driven
● What tools to use

10. Set Goals
and KPIs
Choose Your
Weapon
Measure
and
Analyze
Optimize
How To be data driven

11. Examples for KPIs and Goals
80% of users who shopped once will return and perform another purchase within one month
40% of new visitors will register every day
75% of users who initiated an order to complete it
60% of users who started a free trial will convert within 30 days
…
Break This Down to Segments, Analyze the Behaviour PER Segment

12. Old School KPIs - Good to Monitor
Trends
HOW MANY NEW
SHOPPERS DO WE HAVE
WHO IS SHOPPING
WHERE DO THEY
COME FROM?
WHAT IS THE TRENDS
Pageviews / Downloads
Gender, Age…
Location
?
?
?
?

13. Behavioral Analytics - Good to Understand
i
i
“How” do teenagers renew their accounts?
What steps do they take?
What is the sequence of events that leads
to conversion?
“Why” do users cancel an account?
Why don’t they like the new interface?

14. What will we cover?
● Why be data driven
● How to be data driven
● What tools to use

15. What tools to use