Cohorts

Follow

A cohort is a group of users that share certain event together for a certain period of time, for example: users who make a 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.

The Cohorts plugin lets you group your users based on their actions, such as those who performed the "add to cart" event in the last 7 days but did not perform the "checkout" event. In addition to the ability of grouping users, Cohorts lets you can see their progress over time.

The list of users who are part of a cohort is automatically kept up-to-date, and you can segment funnels, retention, user profiles, flows, push notifications, and drill data based on cohorts you create.

Availability

The Cohorts plugin is available only in the Enterprise Edition.

Setting up Cohorts

First of all, make sure Cohorts is enabled. To do so, in the main Countly Dashboard, go to Management > Plugins and enable the Cohorts toggle.

After that, you will find Cohorts in the Explore section of your Countly Dashboard, under the Users category.

Cohorts Dashboard

Before diving deeper, let's get to know the plugin interface that consists of 3 main views: Overview, Detail, and Compare.

Overview

Overview is the welcoming screen of Cohorts. As the name implies, it gives you summarized information about your cohorts. In addition to that, you can create, edit, or delete cohorts using this view. You can navigate to each cohort's detail by clicking its row as well.

Screenshot_2021-02-03_at_20.05.53.png

  1. Create cohort button: Opens the drawer to create a new cohort.
  2. Compare button: Takes you to the Compare view.
  3. Cohort's Name column: Display of the cohort's name, when it was last updated, and its visibility setting. You can also add the cohort to your favorites using a star icon. 
  4. Segmentation column: Selected segmentation(s) that apply to the cohort, grouped by Property and Behavior types.
  5. Current Users column: Current number of users in your cohort.
  6. Today's change column: The number of increasing or decreasing users ocurred in the current day and a 30-day trend graph of the number of users in the cohort. 
You can update and delete each cohort using the rightmost elipsis menu of each row in the Overview. Through that menu, you can use the View Users option to access the User Profiles filtered by that specific cohort.
overview.png

Detail

When you click on each cohort or click on the elipsis menu > Show detail, you will access the cohort's details. This view provides you in-depth information about a cohort. While charts help you to understand enter/exit behavior of users, metric distributions show you a detailed breakdown of selected segments.

Screenshot_2021-02-08_at_10.42.59.png

In this detailed view you can see:

  1. A brief description of the cohort at hand.
  2. A button to make edits.
  3. Visualize the number of users (net value) in your cohort for the selected period.
  4. Visualize the entering and exiting users of your cohort for the selected period.
  5. Cutomize the period for which the data is shown.
  6. Shows metric distributions of your users. 
  7. A button to add or remove metrics.

Compare

Sometimes a side-by-side comparison of your cohorts might be handy. The Compare view is designed to meet that need.compare_1_m.png

In this comparison view you can see or do the following:

  1. You can select a period.
  2. Here you choose up to 4 different cohorts to compare.
  3. Graph depicting total users in cohort graph.
  4. Graph depicting the total sessions of users in each cohort (data from Drill).
  5. Graph depicting the average session duration of users in each cohort (data from Drill).
  6. Number of entering users to each cohort.
  7. Number of exiting users from each cohort.
  8. Table showing statistics for each cohort.

compare_2_m.png

Creating Cohorts

Some notes on Cohorts before moving forward with how it works and how to add one:

  1. The Cohort User list, e.g which users are included in a particular cohort, is generated upon creation.
  2. This list is regenerated when you edit a cohort.
  3. The list is also regenerated at least once a day or at most once every hour, depending on the cohort generation time.
  4. Cohorts are not retroactive. Hence you will not see any users before a cohort is created, but only after you create a cohort.

A Simple Cohort

To create a new cohort, go to the Overview and define a cohort by clicking the Create cohort button.

Cohorts provide you a 2-fold segmentation mechanism. The first, user property segmentation, helps you to narrow down your target group of users using user properties. For instance, you may want only iOS users to be present in your next cohort. To do that, you can use the query builder in the USER PROPERTY SEGMENTATION panel, as shown in the image below. You can always extend your query to make your target even more specific using the add property button. If you do not want to specify any user properties, you can also choose to skip this stage. 

The second segmentation mechanism is user behavior segmentation, which allows you to narrow down target groups of users depending on if they perform or not the actions you select. The slight difference between this filtering and user property segmentation is that user property segmentation is not dependent on an event. So once you are done with user properties,  you can start adding behavioral conditions using the USER BEHAVIOR SEGMENTATION panel. First, you must select the people who have performed or not a certain event(s) or sessions, and after that, you set the frequency and time range. Again, you can be more specific with a certain beahavior using the add property button.

When you complete either of these two sets of criteria, the add property button will become available, and lets you further customize your conditions. 

You can additionally specify other behavioral segmentations using the + Add Condition button.

Lastly, you can make your cohorts visible to everyone, or keep it private with optional sharing.

create_cohort.pngAs in the above example, you can observe users who logged in using iOS and Facebook over the last 30 days, and offer them special campaigns.cohort_d.png

More Complex Behavioral Scenarios

As you add more conditions, you will see AND/OR selectors appearing between condition rows. For a user to be included in the cohort list, all of those conditions must be true. By selecting OR, however, you can loosen up this hard requirement. If at least one of the items in the OR group is true, then others being false will not matter and the final value of the group will be regarded as true. 

The order of the conditions does not matter.

crashed_d.png

This example reads as "Crashed at least once AND (didn't buy at least once OR didn't view at least once OR didn't start session at least once)". That is, only one of the conditions in the OR group being true is sufficient for that group to be considered as true.

Cohorts in Action

As stated above, you can use cohorts to segment your users in User Profiles, Drill, Retention, Flows, and many other plugins as well. Let's see some examples.

In the User Profiles section, you can observe the details of the cohorts more in-depth. For example, you can get detailed information about the country distribution of the users included in the "Facebook login" cohort and the platforms, devices, genders, and ages of these users.users_f_m.png

You can visualize the users who have not logged in since March 25. Then, you can reach them with a push notification using the Create Message to # users and trigger them to use your app again.users_fl.pngYou can see in a single page all the details of the customers who have purchased and shared products in your eCommerce application. Or you can find users who have added items to their cart, but have not completed an order.

From this user profiles page you can access the information about your users’ country, total time spent, last seen, as well as their device information. 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.users_1m.png

You can also use a Drill segmentation to observe the retention rate of your cohort’s users. For example, you could observe the Retention information within 2 days of your registered users with Facebook Login in only two steps, as shown below:drill_m.pngDepending on the behavior of the users, you can organize campaigns for these user groups by segmenting them, better understanding them, and you can make improvements to your product.

Another option is that you may want to use a drill to interact with your users based on the decrease or increase in their engagement. For example, your user group who logged in with Twitter had been using your application quite actively in recent days, but then this number has dropped in the last week:drill4.png
With a push notification you send to your users, you can prevent this decrease and bring them back:
drill_act2.png
If you want to monitor your users’ User Flow, it is possible to do this again via cohorts. For example, say you have defined a special "Purchased & Engaged" cohort for the users who have bought a product from your app and have logged in again. It is possible to understand what steps your users follow and what they cannot follow, and increase your sales by making improvements on your pages based on this information.flows_m.png

Benefitting from Cohorts

If you are a mobile app developer or product manager, you are very much interested in all the actions users take within 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 (like installation or opening) within a certain period of time. You can evaluate a number of data samples, such as the proportion of active users. You can also set up cohort events with various in-app events to determine the degree of user interaction with your mobile application.

In the e-commerce industry, Cohorts 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 applicable for gaming apps, web apps, or social media apps. In short, is a key feature that helps you design the best possible benefits for your users.

Outcomes of Cohort Analysis

Precision Data

Setting up a cohort analysis is a highly effective way of working since it helps you distinguish customers individually. You can access highly accurate information by clustering and following the individuals who are registered to your product during a certain period. This way, the analysis and change over time of their interaction are not affected by the rest of your audience, giving you the power to target your strategies better and to understand users both in an individual or segment level.

“Engagement” vs “Growth”

Separating users or customers into cohorts is also effective when 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 will increase general participation (i.e. the engagement), but only new customers who access the product will probably stop after a while.

Comparison Between Different Behaviors

Cohort analysis also helps when comparing the results between two or more groups. For example, if the hypothetical “first seen on March” cohorts engaging with the product more than the "first seen on January" cohort, an analysis of any changes that may occur between the two months may be necessary. In addition, more analyses can be done on both cohorts to see if the product is attracting a particular group within each.

Fast Decisions

Cohort analysis also helps 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.

Was this article helpful?
0 out of 0 found this helpful

Looking for help?