What is a Cohort Analysis? | How to Do Cohort Analysis?

What is a Cohort Analysis? | How to Do Cohort Analysis?

Cohort analysis, one of the latest features offered by Google Analytics, has been creating quite a bit of confusion among analysts. And, the confusion stems from the nature of this new feature.

For one, cohort analysis is not like page or session analysis, i.e., it's dynamic. So, it doesn't merely sum up your page or session activities over a certain timeframe, but rather the user groups' behaviour over time.

Secondly, producing actionable insights from cohort analysis isn't that easy. For instance, the visitors are coming back to your site in the last few weeks, but how to use that information with other data drawn from analyses?

Let's discuss cohort analysis in depth today and clear out all that confusion.

What Exactly Is Cohort Analysis?
Types of Cohort Analysis
Types of Cohort
Three Major Aspects to Figure out Cohort Analysis
How to Do Cohort Analysis
Using Cohort Analysis Effectively In the Business
Advantages of Cohort Analysis

Customer Retention and Cohort Analysis

What Exactly Is Cohort Analysis?

Bruno Estrella, who currently leads growth at Webflow, defined cohort analysis as one analytical technique that helps you analyze the behaviour of a defined group of people during a specific period of time. As such, the aim is to uncover insights about customer experiences and figure out ways to improve those experiences. Let's understand this definition better through an example.

Suppose a customer named Tom came to your website three months ago when there was a fifty percent discount going on and brought a trial set of your products. You started using carefully placed cookies to track the behaviour of people like Tom. You would like to know if they come back to buy stuff and how often they do that.

Now, when you sit down to analyze your cookies, you would want to figure out the number of users like Tom who came to your website and purchased the same trial set. You found out that about seventy percent of the buyers of the trial set didn't come back. It's time to think about ways to remedy the situation.

Firstly, you might consider that the buyers have forgotten you in all the information that they are inundated with on a daily basis. In such a scenario, running retargeted ads at the end of their use of the product might prompt them to buy more.

Secondly, the visitors might be stopping and dropping off from the 'shipping' page. The problem might be with your high shipping cost, and the solution lies in offering free shipping or discounts at that point.

So, the analysis gave you two clear ideas to improve your conversion rates for all such groups now and in the future. You need to take the right actions and note the improvements made in your conversion and retention rates.

Volume of Data Created, Captured, Copied, and Consumed Worldwide from 2017 to 2022
The volume of Data Created, Captured, Copied, and Consumed Worldwide from 2017 to 2022

Types of Cohort Analysis

There are mainly two types of cohort analysis. These are:

Acquisition Analysis

This type of cohort analysis is performed on the basis of the acquisition of the customers. For example- when the customer was acquired, or when they purchased or subscribed to your products or services. This can be done daily, weekly or monthly, depending upon the requirement.

Behavioural Analysis  

This type of analysis is performed on the basis of customers' behaviour patterns. This type analyzes the actions of the customers. For example- how often does a customer order from a particular restaurant, how do customers interact with a company's social media channels, etc.?

Data-Driven Marketing | How to do Data-Driven Marketing?
Data-Driven Marketing uses data to promote the growth of the business. Read to learn how to do Data-Driven marketing effectively.

Types of Cohort

The following are the different types of cohorts that businesses use for cohort analysis. Let us take a detailed look at these groupings:

  • Time Cohort- Time-based cohorts analyze the type of customers who purchased a certain type of product during a particular timeframe. It helps companies forecast trends and keep an eye out for standout patterns that repeat in consumer behaviour. It also aids companies in improving the lower consumer interest in the services offered.
  • Size Cohort-  Cohorts based on size point to the size of consumers who buy the products or services of a particular company. The size of the client can range from small startups to organizations operating under marketable enterprises. Grouping this element together reveals which consumer purchases the most products. The company can work to improve its offerings so that it can provide a better experience to clients with smaller purchase shares.
  • Segment Cohort- Cohorts based on segments focus on consumer requirements. It analyzes the purchases of customers and helps a company create personal products or assistance curated for specific segments. Companies can prepare better based on what sort of a plan a customer has signed up for. Based on whether they choose the basic or high-end services, the organization can analyze the needs of the client.
  • Prospective Cohort- Prospective cohorts identify and examine the level of exposure of a product at the consumer level. It investigates the follow-up until an outcome establishes itself, concluding the project with definitive results. This cohort can take months or even years to compile the respective data since the outcomes are yet to be determined.
  • Retrospective Cohort- If the considerable follow-up period seems time-consuming and too expensive, companies can choose to go for the retrospective type of cohort. This cohort considerably shortens the waiting period by depending on past exposure and relevant data. It identifies those who developed the desirable outcome instead of following the participants over an undetermined duration.

How to reduce customer friction? | Making Happy Customers
Customer friction is caused when customers feel hesitant to buy goods or services of your company. Lets learn how to reduce customer friction?

Three Major Aspects to Figure out Cohort Analysis

Size of Marketing Related Data Market Worldwide from 2017 to 2021
Size of Marketing Related Data Market Worldwide from 2017 to 2021

To better understand the practice of cohort analysis, you need to know about the three aspects that constitute the analysis. So, cohort analysis entails three highly specific features:

1. A Specific Period in The Past

Cohort analysis is strictly bound by time as it is about defining the group that entered your store at a particular time. Thus, you have to start with deciding the time period that has to be analyzed.

For instance, if you are planning to analyze customer behaviour during a particular promotional event, as mentioned above, your cohort analysis would cover the entire period of the event. Added filters can be included in this analysis, such as whether you want to know how many people visited via Instagram or Facebook.

2. The Lagging Period of the Analysis

The lagging period refers to the time for which the analysis is run. So, if you are planning to analyze how the users behave for a month after their first visit, one month is your lagging period.

The number varies based on your business needs and the ongoing conditions of your company.

3. Termination Time of the Analysis

After both the cohort and the lagging period get pointed out, the termination time of the analysis is dealt with.

So, if you're tracking your cohort's behaviour between April 1st and 7th and have a month as the lagging period, the termination time is May 7th. This date signifies the final signal of the lagging period for the last person in a cohort.

How to Do Cohort Analysis

Cohort Analysis
Cohort Analysis

There are many benefits to conducting a cohort analysis. However, achieving the procedure takes certain know-how before a researcher commits to the plan of action. The following steps will show how to do cohort analysis:

Specify the Objective of Cohort Analysis

The main goal of cohort analysis is to focus on specific groups of data refined down to convey information better to researchers.  Therefore, the first objective is to select your subject and define it in clear-cut terms. You need to have a clear picture of what exactly you want to club and analyze. You must define the objectives your cohort analysis has to follow.

Define the Metrics That Clearly Partner up With the Aim

Right after defining the specifications of the objective, you should trace an outline for suitable metrics. The right metrics will help you keep a tab on the generation of numbers for different aspects of your project. Always choose metrics that are not only separate from the data but also clearly define the characteristics of each grouping. Metrics like user engagement on different events, subscription rates, and more can be used.

Select the Necessary Cohorts

At this step, you should pick out the type of analysis you would want to incorporate into your study. You can check out a list of the different types of cohort analyses you can use. You may also combine some of them to suit your purpose. This is a crucial stage as it determines which cohort will be most suitable for your study.

Perform the Cohort Analysis

After you collect your sequencing and create a plan, carry out the study. At this step, you perform the cohort analysis using the data extracted from different patterns of the cohorts. Remember to keep an eye on the metrics of the project, the reviews, experiences, etc., of your subjects to get the best possible insights from the data. This will help you to get a better understanding of your products, marketing techniques, and most importantly your customers.

Prepare and Illustrate the Results Appropriately

Remember, simply noting down the results will not do. You need to substantiate your findings with your research. You must include all the facts, numbers, graphs, charts, etc., that the course of your research has produced. Lastly, compile your findings and present them in a logical and rational sequence.

Using Cohort Analysis Effectively In the Business

There is no denying that it's difficult to get business value from a single cohort analysis better than the other methods of analytics. Of course, your reactions can't solely be based on the cohort data.

Suppose you are going for the funnel analysis and note the rapid dropping off of some users from a certain part of your funnel. A retargeting campaign gets launched immediately, and you work towards patching up all that's wrong with the funnel. But the feedback cycle isn't that short with cohort analysis.

For instance, you can run a cohort analysis with a month-long lagging period and implement the improvements based on the user experience of a month. But it will take a month for you to actually see the result of your steps when the journey of the present cohort gets completed.

If you make further changes, it will take one more month to see the results. Now that is pretty slow in this fast-paced world of digital marketing. Making a single set of improvements and waiting for a month to see its effectiveness might not seem viable.

But, at the same time, it's true that you get a complete look at the journey of the users through the cohort analysis. It might be slow, but it's helpful in designing campaigns that showcase results immediately. You should also leverage the data from cohort analysis to create long-term value for the company.

Advantages of Cohort Analysis

Cohort Analysis is a cunningly useful tool to measure the performance and key takeaways from consumer psychology. Markets use cohort analysis to improve their performance or promote their best-selling services and products. Let us take a look at some of the benefits cohort analysis provides in research and areas of development:

  • Increases efficiency- Imagine if you were handed a hallway worth of data and ordered to extract meaning from it. As nightmarish as that sounds, you can take the much more efficient path of cohort analysis. The tool offers a range of benefits, such as customer psychology, period of success or failure, etc.
  • Helps to troubleshoot problems- It is crucial to the success of your company to see which products fail to hit the mark among your target consumer. Once you can check out these problem spots through cohort analysis, you can decide whether to improve these services or remove them from the market.
  • Aids in the promotion of goods- Cohort analysis pinpoints services and products that have performed well among your audience. These spots are lush grounds for increasing your profits. Once you locate these best-selling services, you can focus on promoting them heavily and increasing the awareness of your brand through these goods.
  • Offers a clear difference between engagement and growth- A common error is mistaking growth and customer engagement as the same thing. Growth occurs when a client takes what you are offering, however, engagement is when a client only engages with your products and services without taking any action. Cohort analysis will offer a clear-cut difference between the two and let you check whether you have seen real growth or not.
  • Predict future behaviour- Cohort analyses keep a strict eye on the ever-changing trends of consumer behaviour. The study follows key markers that will help researchers chart out a forecast for repetitive patterns in the future. Cohort analysis offers an in-depth look at consumer psychology so that you can predict probable profitable areas that will help bring in revenue.


Cohort analysis gets you the perfect combination between time-based campaign retrospection and continuous customer experience benchmarking.

Thus, the information derived from the analysis has a long-term impact on shaping the future campaigns and policies of the business. It also tells you whether or not to continue with your current campaign or launch something in a similar vein in the next quarter.

And that's all cohort analysis is about!


What is cohort and cohort analysis?

In simple terms, cohort analysis is a type of analytics that takes data from various different sources and groups it into related groups. These groups are called cohorts. The cohorts possess similar traits like colour, time, size, segment, etc.

Why do we do cohort analysis?

Cohort analysis allows one to understand and track customer patterns in a better way. Performing cohort analysis helps to improve issues, make better decisions, and provide a better customer experience. This in turn helps to increase sales and revenue.

How do you do a cohort analysis?

Cohort analysis is done through the following steps:

  • Specify the Subject of Cohort Analysis
  • Define the Metrics That Clearly Partner up With the Aim
  • Select the Necessary Cohorts
  • Perform the Cohort Analysis
  • Frame and Illustrate the Results Appropriately

Must have tools for startups - Recommended by StartupTalky

Read more