Understanding Cohorts

Understanding customer behaviour over time

The purpose of cohort analysis is to identify trends and patterns in customer behavior that can help you to better understand your customers and make data-driven decisions about for your marketing, product development, and customer retention strategies.

For example, use cohort analysis to track the behavior of customers who made their first purchase in a particular month. Compare this group's behavior to the behavior of customers who made their first purchase in other months, looking for patterns such as differences in purchase frequency, average order value, or customer lifetime value.

Cohort analysis can also be used to evaluate the effectiveness of marketing campaigns or other initiatives.

Overall, cohort analysis is a powerful tool for ecommerce businesses looking to gain deeper insights into customer behavior and make data-driven decisions that can help you grow and succeed.

Understanding and creating a cohort

Here we'll be guiding you on how to create a cohort to display your customer lifetime value (CLV) and how it has evolved over time.

Viewing your CLV in cohorts enables you to observe how the metric varies based on when a customer is acquired, while also tracking how the CLV changes monthly.

1. Create a cohort in just 1 minute

2. How a Cohort is built.

Now it's essential to understand how to view your Cohorts. Cohorts are constructed based on four primary factors, all of which focus on when customers made their initial purchase (or second purchase if that option is chosen):

Date: The acquisition month when a group of customers first made their purchase.
Customers: The total number of customers who made their first purchase in your store in a given month.
Month 0-12: These are the months after the acquisition month and are used to track the KPI.
KPI: Your chosen metric averaged by a specific variable. You can see this number in each of the small colored boxes. For instance, in this example, the KPI is CLV (sales averaged by customers).
In the Cohort you just created, you can see your customer lifetime value and how it is developing on a monthly basis.

Grouping your customers together in the months they did their first purchase, will help you gain insight into the best months for customer acquisition.

It's important to note that the month in which you acquire customers can have a significant impact on the development of your KPIs such as CLV.

Example: Customers acquired in November might have a lower CLV

due to Black Friday.

You can also spot different months that might have done incredibly well, and think back to what marketing campaign you ran at the time.

3. How to read your Cohorts.

To better understand how to analyze your Cohorts, it's essential to know about two ways of viewing them: horizontally and vertically.

Once you understand these two approaches, you'll have a new way of analyzing your customer data.

Horizontally:

Track how customers acquired in a specific month are doing over time, based on the KPI you're focusing on, such as customer lifetime value (CLV).

By doing this, you can monitor how the CLV of customers from a specific acquisition month is changing, month by month.

Vertically:

Analyzing a cohort in this way allows you to compare and examine the performance of all acquisition months. By doing this, you can determine which acquisition months have the greatest impact on your KPI.

Examining only one row of data is not very informative. Therefore, it's best to combine both methods of analyzing a cohort to gain a better understanding of the acquisition months over time.

Use both views to uncover insights into your customers.

Now that you've gained insight into the cohort from both views, you can observe how customers from various acquisition months have evolved over time. 

This enables you to identify significant changes in your KPI, which is also highlighted by the colored boxes.

By pinpointing the months with the most significant changes, you might be able to link it to specific events, such as a successful marketing campaign that resulted in an increase in CLV.

The possibilities of Cohorts are endless, and the reasons why a KPI increased might be very specific to your business.

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