A cohort is a group of users that share certain event together for a certain period of time (for example: users who make payment for the first time in the last 30 days, or added 7 friends in the last week). In other words, a cohort is a group of people with similar behavioral characteristics.
Cohorts let you group your users based on their actions, such as who performed add to cart event in the last 7 days but didn’t perform checkout event. List of users who belong in a cohort is automatically kept up-to-date, and you can segment funnels, retention, user profiles, flows and drill data based on cohorts you create.
Available for Enterprise Edition
Cohorts feature is available for Enterprise Edition customers.
Some notes on Cohorts before moving forward with how it works and how to add one:
- Cohort list, e.g which users are included in a particular cohort, is generated upon creation.
- This list is regenerated when you edit a cohort.
- The list is also regenerated at least once a day or at most once every hour, depending on the cohort generation time.
Below you can watch a video walkthrough of Cohorts plugin
With Cohorts, you can track user groups that share the same characteristic and you can see the progress over time.
By combining users of a cohort, you can benefit from this cohort in several different areas: User Profiles, Drill, Retention or Push Notification are just a few of these areas.
You can add, view, edit or delete a cohort from
For example, you can see the details of your customers in a single page who have purchased and shared products in your eCommerce application. From this page you can access the information about your users’ country, total time spent, last seen, as well as the device information used by your users.
By observing the common features of your users with a particular pattern from a single page, you can make improvements in your product development process or in your content.
You can also use a Drill segmentation to observe the retention rate of your cohort’s users. For example, you can observe the Retention information within 2 days of your registered users with Facebook Login in two steps as follows.
Or if you want to monitor your users’ User Flow, it is possible to do this again via cohorts. For example, you have defined a special Purchased & Engaged cohorts for your users who have bought a product from your app and have logged in again.
It’s possible to understand what steps your users follow and what they can not follow, and increase your sales by making improvements on your pages based on this information.
Another option is that you may want to use a drill to interact with your users based on the decrease or increase in engagement of your users. For example, your user group who logged in with Twitter has been using your application quite actively in recent days, and this number has fallen in the last 2 days. With a push notification you send your users, you can prevent this decrease and regain your users.
Depending on the behavior of users, you can organize campaigns for these user groups by segmenting them, better understanding them, and you can make improvements to your product.
If you are a mobile app developer or product manager, you are very interested in all the actions users take with your mobile app. Specifically, you need to track the number of installs of a mobile application, the opening rates, clicks, whether the customer is interested, or uninstalled. You can use cohort analysis to evaluate the lifecycle of your mobile app.
In mobile related apps, a cohort is a group of users who complete a specific operation (installation, opening) within a certain period of time. You can evaluate a number of data samples, such as the proportion of active users, and we can also set up cohort events with various in-app events to determine more user interaction with your mobile application.
In e-commerce industry, cohort is a great tool to use. For example, to see the timeout period, revenue per visit, or average order value. Once you start doing cohort analysis you can look back over the past several months for specific groups of users.
These examples can be enhanced with gaming app, web app or social media app. In short, you will use cohorts as a tremendous tool in order to design the best possible benefits for your users.
Setting up a cohort analysis is a highly effective way of working since it helps you to distinguish customers separately. You can access the most accurate information by clustering and follow the individuals who are registered to your product during a certain period. In this way, the analysis and change over time of their interaction are not affected by the individuals in the other group; thus keeping the groups completely independent of each other.
Separating customers into cohorts is also effective in clearly identifying the difference between growth and engagement metrics. These two metrics can be confused with each other; because growth is the increase in the number of customers using a product or service. Generally, increasing numbers automatically increase general participation, but only new customers who access the product will probably stop after a while.
A cohort analysis also helps in comparing the results between two or more groups. For example, if the “first seen on March” cohorts engaging the product more than the January cohort, an analysis of any changes that may occur between the two months may be necessary. In addition, more analysis can be done on the groups to see if the product is attracting a particular group.
A cohort analysis also helps to determine times when logins to the site decrease. Due to time-consuming work, quick decisions can be made to correct problem areas that may cause the decrease.
What you need to do is to separate your customers with cohorts, which is quite simple. Go to
Cohorts menu and define a cohort by clicking
Create cohort button.
First, you must select the people who have performed/not performed a certain events or sessions, and after that, you should set the time.
You can add filters to many subjects such as country of a user, last entry time, input method, etc. and you can collect similar users. If you want to go deeper, you can increase the number of filters.
As in the above example, you can observe users who log in using Facebook over the last 30 days and offer them special campaigns.
Cohorts are calculated when they are created
Each cohort is calculated at the time when they are created and they are not retroactive. Hence you will not see any users before a cohort is created, but only after you create a cohort.
You can also define the same cohort for Twitter login, to observe the difference between Facebook and Twitter logins. For example you can compare users logged in via Facebook or Twitter for the last 30 days. You can observe users who are new, “Entered Users”, to this cohort in the time period specified and those who are not cohort, “Exited Users”, in other words who have not had a session for the last 30 day.
In the User Profiles section, you can observe the details of the cohorts more deeply.
For example, you can get the most detailed information about the country distribution of users including Facebook login cohort, the platforms, devices, genders and ages of these users. Or you can observe how many percents of the users in this cohort are on October 1, the most recent date seen, as in the visual below.
Or you can observe users who have not logged in since October 1, you can reach them with a push notification and trigger them to use your app again.