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COHORT ANALYSIS
By Olatunji .O.O.
What is Cohort
 Cohort analysis is a time-tested segmentation technique used to
understand user behavior. So instead of telling us just the total number
of users who filled out a form last week, it can tell us that 20% of users
who first visited a site on Monday filled out a form on Wednesday.
 According to Wikipedia; A cohort is a group of people who share a
common characteristic or experience within a defined period (e.g.,
are born, are exposed to a drug or vaccine or pollutant, or undergo a
certain medical procedure). Thus a group of people who were born on
a day or in a particular period, say 1948, form a birth cohort.
A cohort is really just another type of segmentation, the key is that a
cohort is based on date.
An E-commerce Black Friday as an example; I would want to create
a cohort of customers who make their first purchase on Black
Friday. This cohort is important because they made their first
purchase during a very important time, the holiday buying season.
From an analysis perspective we want to segment this group to
observe their behavior over a longer period of time.
 Do these customer behave differently?
 How do they differ from customers that buy at other times of the
year?
 Do they buy multiple times? Do they spend the same amount?
Screen Shots
The aim of using Cohort analysis
 Are they spending money? Are they generating a lot of value for my
business? If they are not generating value, when did they stop generating
value? Was it after one week, one month of one year?
 what products do these people purchase? Are they buying products in
the same general category or are they buying a broad range of things?
 What traffic sources generate repeat visits? Are they responding to
retention based marketing activities? Are they coming directly to the site
because they are loyal?
 As a publisher: what content do these people read? Do they read the
same type of content? Are they looking in different categories? What do
their loyalty metrics look like?
THANK YOU FOR
YOUR TIME

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Cohort analysis on Google Analytics

  • 2. What is Cohort  Cohort analysis is a time-tested segmentation technique used to understand user behavior. So instead of telling us just the total number of users who filled out a form last week, it can tell us that 20% of users who first visited a site on Monday filled out a form on Wednesday.  According to Wikipedia; A cohort is a group of people who share a common characteristic or experience within a defined period (e.g., are born, are exposed to a drug or vaccine or pollutant, or undergo a certain medical procedure). Thus a group of people who were born on a day or in a particular period, say 1948, form a birth cohort. A cohort is really just another type of segmentation, the key is that a cohort is based on date.
  • 3. An E-commerce Black Friday as an example; I would want to create a cohort of customers who make their first purchase on Black Friday. This cohort is important because they made their first purchase during a very important time, the holiday buying season. From an analysis perspective we want to segment this group to observe their behavior over a longer period of time.  Do these customer behave differently?  How do they differ from customers that buy at other times of the year?  Do they buy multiple times? Do they spend the same amount?
  • 5. The aim of using Cohort analysis  Are they spending money? Are they generating a lot of value for my business? If they are not generating value, when did they stop generating value? Was it after one week, one month of one year?  what products do these people purchase? Are they buying products in the same general category or are they buying a broad range of things?  What traffic sources generate repeat visits? Are they responding to retention based marketing activities? Are they coming directly to the site because they are loyal?  As a publisher: what content do these people read? Do they read the same type of content? Are they looking in different categories? What do their loyalty metrics look like?
  • 6.
  • 7.