As a website or app owner or marketing manager, your focus tends to be on acquiring new users through different types of marketing campaigns. However, your long-term goals should be to engage the users and maintain a good retention rate to ensure that your acquisition efforts do not go in vain. But, how do you achieve these goals?
First, you need to be able to segment your users into separate groups and perform a focused data analysis. This means that you have to evaluate the behavior as well as performance of the different groups of users that share certain common attributes. For example, you would do well to understand the behavior of new consumers acquired during the holiday shopping season for your ecommerce business. Such a group or segment of users based on a date range or common characteristic is known as a cohort.
Google Analytics enables you to analyze such cohorts by providing access to the Cohort Analysis Report. But, what data do these Cohort Analysis Reports show? How can you configure such reports?
Let us do an in-depth study of the Cohort Analysis Reports in Google Analytics to understand how it can be useful for your business.
Overview of the Cohort Analysis Reports
A cohort analysis compares how cohorts behave over a period of time. So, it is a behavioral analytics method that analyzes data from your web app or ecommerce platform or a similar dataset. The report also breaks up your entire user population into relevant groups for analysis.
Examples of Usage
- These reports help you evaluate individual cohorts and understand how they respond to short-term marketing campaigns. For example, your marketing strategy could be to use emails for “Black Friday” for a couple of days prior to the event.
- The Cohort Analysis Report can show you the dynamically changing behavior and performance of your individual cohorts from day to day, week to week or month to month.
- It empowers you with the ability to organize your user groups on the basis of shared attributes, such as Acquisition Date. This makes it relatively easy to monitor and evaluate the behavior of the different groups in terms of metrics like revenue and user retention.
- The reports also help you understand at what points your users tend to disengage. For example, certain indications can be in the form of less revenue, fewer sessions, and so on. In this way, you can take the necessary steps to increase acquisition and compensate for attrition that cannot be avoided. Additionally, you can find solutions for common attrition problems.
How to Configure the Cohort Analysis Report?
Before you start configuring the report, you first need to follow the steps mentioned below to access or open it:
- Log in to your Google Analytics dashboard.
- Ensure that you choose the relevant view from your “Admin” tab.
- Navigate to the “Reporting” tab and opt for “Cohort Analysis” under the “Audience” section.
Configuring the Cohort Analysis Report
As seen from the above image, the Cohort Analysis Report can be configured by making the following choices from the menu:
This refers to the dimension that is the basis of the cohorts. You can specify the date on which you intend Google Analytics to create the cohort in “Cohort Type”. There is currently just one dimension that you can select, namely “Acquisition Date”. This refers to the date when the user first visited your website or mobile app, i.e., the date of the first session.
This configuration options corresponds to the timeframe that determines the size of each cohort. Here, you specify the time window that you intend to use to look at the “Cohort Type”. For example, if you select “by day”, the cells in the dimension column will show a single date as well as the number of users organized into that cohort for that chosen day.
You can also change the “Cohort Size” selection to “by week” or “by month” and thus view all the users that have the same acquisition date or date range.
This is the actual data displayed in the Cohort Analysis Report. You measure the metric for every cohort. There are numerous metrics on a per-user basis (including sessions per user, revenue per user, goal completions per user, and transactions per user) as well as on a cumulative basis (for example, users, pageviews, and session duration).
This selection helps you analyze a particular metric for a cohort and understand its performance over a specific time period.
This is the time interval that determines what data is displayed in the report. The date range selection corresponds to all the rows of the table. For example, if you opt for “Last 14 days”, the table will have a total of 15 rows (i.e., one for each of the past 14 days and one row for the sum of all the cohorts).
Google Analytics constructs a cohort by using the date range to evaluate the date (for example the acquisition date) mentioned in the “Cohort Type.”
Understanding the Data in the Cohort Analysis Reports
This displays the cumulative metric values for all the cohorts by default.
The first column reflects the cohorts and the number of users present in every cohort, while the remaining columns correspond to the time increments you selected for “Cohort Size”.
For example, when “Acquisition Date” is the dimension, the first column will show the acquisition date for each cohort along with the number of users acquired during that timeframe in terms of days, weeks or months. And, if you chose the time increment to be “by day”, then the remaining columns will each include one day of data. There are a total of 13 time increment columns (0 to 12).
The first row displays the total metric value for all the cohorts, corresponding to each column. All the remaining rows show the values of the individual cohorts. For example, when the columns are day-wise data for the “Page Views” metric, the first row will reflect the “total page views” for the day.
The cells correspond to the time increments (0 to 12) and hold the relevant metric values. So, each cell will represent the number of pageviews per cohort per time increment when the metric is “Page Views”.
The data is shown in five different colors, each indicating the relative metric values. For example, the lightest color corresponds to the lowest metric values and the darkest color represents the highest metric values.
So, the Cohort Analysis Report plays an important role in analyzing how groups of users perform and behave based on a common attribute.
We hope that the above information about cohort analysis and the related report proves valuable to your business. Please share your feedback and queries (if any) in the comments section below.