A Guide to Cohort Analysis for Product Managers

As the competition between businesses heat up, deeper and more detailed statistics are needed to make the vital improvements with your product, service, or your brand.

In this post, we discuss cohort analysis in detail: what it is, why it is important, how to apply it in various industries, and how to segment your own target markets into cohorts so that you can also benefit from this often underutilized behavioral analytics tool.

What Are Cohorts?

In the simplest of terms, the members of a cohort share certain characteristics.

These members can be individuals, companies, or other groups, and the characteristics they share depend on what we want to look at.

We can look at people with the same age, gender, or education level as a cohort; we can look at businesses with a certain market share or ad spend as a cohort, and we can look at people, companies, or products that operate in or that are used in a certain industry or vertical as a cohort.

When it comes to cohorts in the world of analytics, we are usually interested in target customers (groups of users or other businesses) who performed certain actions (such as made a purchase, interacted with your website, or downloaded your app) within a certain period of time in the past. 

Think of customer signups within the last week, businesses that stopped using your app in the last quarter, or new sales leads generated via your last advertising campaign as individual cohorts. Looking at your customers (or potential customers) as a single cohort in this fashion, you can more easily highlight patterns and trends throughout their customer lifecycles, allowing you to pivot your various operations (onboarding, marketing, product design, outreach initiatives, sales channels, and even your language) so that you are better adapted and optimized to meet user needs and expectations.

In short, cohort analysis allows you to ask specific questions, analyze only the information that is relevant to answering those questions, and then take data-backed actions on your findings.

Cohort Analysis 1
image is taken from intercom.io

How Cohort Analysis Helps Optimize Results

Here are a few tried and tested ways that cohort analysis can make you a better product manager and service provider.

Filter Out the Noise

It can be difficult to extract meaning from aggregate sets of user behavior.

Segmenting users into cohorts and then analyzing their behavior will give you a clearer picture of how users interact with you (and your products or services) throughout the customer lifecycle.

Effectively Test Hypotheses

A/B testing between groups or cohorts can help you identify what you are doing right and what needs to be improved.

All you have to do is compare results from a test group with behavior seen in a control group. Once you know what needs to be fixed and for whom, you can then roll out incremental and iterative changes for everyone.

Know Your Customer Lifetime Value

With cohort analysis, you can calculate the lifetime value of your target users and then use that number to dictate spend for the likes of acquisition and retention.

Optimize Your Conversion Tunnel

Cohort analysis helps you accurately calculate just how user experiences along the purchase journey affect conversion rates as your users travel to the bottom of the tunnel from the top.

You can improve conversion rates even more by segmenting channels and optimizing spend based on revenues.

Understand Growth vs. User Experience Optimization

Your business may grow fast enough for user-engagement issues to be masked.

Focusing primarily on acquiring new users without performing cohort analysis to understand user engagement will have you running the risk of suffering a significant drop in user engagement as time goes on.

Cohort Analysis 2

Using Cohort Analysis for Improving Retention

With cohort analysis, you can segment your customers by the channel in which you acquired them and when they were acquired.

You can then analyze the retention rate of different groups by focusing on poorly performing channels or putting more resources behind channels that deliver higher retention rates.

If you categorize your users by how and when or where they first interacted with you in any way, you can create unique time-based cohorts. This can help you identify when in time engagement tends to drop off and take proactive, preventive measures ahead of time to reengage with users before it is too late.

You can also segment users based on the actions they have or have not yet taken within a given time period. Behavioral cohorts of this type are comprised of users who performed similar actions in the same time frame.

Doing this will help you identify how future users will likely behave based on the behavior pattern of older customers who shared the same behavior profile. In analytical terms, this is known as identifying customer sticking points.

Segmenting Your Target Markets for Cohort Analysis

Effective cohort analysis depends on being able to accurately identify the cohort you want to track.

Since we now know what cohort analysis is and why we should do it, here is the ‘how’ of doing it.

1. Ask the right questions you want answers to.

The objective of your analysis is to give you actionable information based on which you can improve end results for yourself and your users.

What do you want to learn about them or their user experience? Do you want to know how they use your website, how they use your product or service, or how they discuss you in public? The questions you choose to answer will determine how you mine your data in pursuit of answers.

Cohort Analysis 3

2. Identify the metrics that will answer your question.

For your cohort analysis to be effective, you need to identify which user action or event you need to track, as well as properties of the event that are relevant.

For example, if you are tracking a user purchase, you may want to see which channel the user came into contact with you on and where they completed their purchase.

If you want to track churn, you can, for example, if there is a specific product page on which most users drop off or a time frame after which users stop engaging with you.

3. Define your cohort.

The final step involves deciding whether you want to target every user who fits a certain profile or somehow distinguish between them, such as those who bought within a certain period of time or those who completed multiple purchases (or purchases of a certain value).

Having multiple cohorts will help you understand your users on a more granular level and you can tweak your offerings (or the way you interact with users, or the product or service features you place the most emphasis on) accordingly.

The Bottom Line

Cohort analysis is an important tool in the arsenal of the discerning product manager.

Because it can help you better understand what you want to know about your target users, you can use it to improve everything from your marketing initiatives and operations to customer service and product placement.

Iteratively defining finer and finer cohorts can give you a very clear picture of your entire customer base and can offer valuable predictive intelligence when it comes to making mission-critical product decisions.


Frequently Asked Questions


📝 What is a Cohort Analysis?

A cohort analysis is an analysis that allows you to ask specific questions, analyze only the information that is relevant to answering those questions, and then take data-backed actions on your findings.


❓Why should I make a Cohort Analysis?

In order to answer the more specific questions that you have about your users’ activities, you should make a Cohort Analysis.


⌛️ When is the right time to make a Cohort Analysis?

You can apply cohort analysis as soon as your product has a base of customers.


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Mert Aktas

Mert is the Marketing Manager of UserGuiding, a code-free product walkthrough software that helps teams scale user onboarding and boost user engagement.