Cohort Analysis

Cohort Analysis

Cohort Analysis is a type of analytics that looks at the behavior or performance of groups of people (cohorts) who share a common characteristic or experience. For example, a cohort could be people born in the same time period or started schooling in a specific year.

In ChartMogul, a cohort is a group of customers who start their first subscription in the same month and year. Cohort analysis allows you to better understand churn, retention, and conversion rates based on when customers subscribe and identify points in your customer lifecycle that result in contraction and churn.

Read more about the lifecycle of subscriptions in ChartMogul, including how we organize and classify MRR movements.

Here's what we cover in this article:

  1. How cohorts are useful
  2. Reading a cohort table
  3. Cohort Analyses in ChartMogul
  4. Configuring your analysis
  5. Understanding the data
  6. Segmenting cohorts

Resources and further reading:

How cohorts are useful

To grow a SaaS business, you need customers to continually renew their subscriptions. So it's important to identify points in your customer lifecycle that result in downgrades (contraction) or cancellations (churn).

Screenshot of a customer churn cohort table with a list of cohorts and churn rates by month, relative to the previous month

Instead of looking at the overall churn rate for all customers, cohorts allow you to compare groups of customers based on when they subscribe so you can answer questions like:

  • Which month in the lifespan of a subscription is churn at its highest?
  • How did last month's product release impact churn?
  • How is retention for customers who subscribed in February during our Valentine's marketing campaign?
  • How is retention for customers who signed up using a discount?

Reading a cohort table

The results of a cohort analysis are visualized using a table that may be different from other charts and reports you're familiar with and can be a challenge to read and understand.

Screenshot of a cohort table with numbers for each element explained here

The cohort analysis you select — and how you configure it — determines the calculation of Cohort Value and the metric ChartMogul displays in table cells.

Columns

The first and second columns display each cohort's name (identified by month and year of conversion, e.g., Feb 2021) and its value. The remaining columns represent each month of the cohort's existence.

Rows

Each row is an individual cohort. Cohorts appear in chronological order. The last row provides an average of the relevant metric across cohorts for each month.

Cells

Cells show the relevant metric depending on the cohort analysis you select (e.g., churn, expansion, contraction, or reactivation) and how you configure it. Future months are blank.

Colors

ChartMogul assigns a color to each metric to help you interpret the results of your analysis. Green indicates the metric with the best value (i.e., lowest churn or highest retention rate) and red the worst. The metric falling in the middle is yellow. The remaining metrics are colored using shades along a green-yellow-red gradient to indicate their value relative to the best (and worst) metrics in your current analysis.

Cohort Analyses in ChartMogul

ChartMogul offers the following cohort analyses, which you access by navigating to Reports > Cohorts.

Churn

  • Customer Churn — the percentage or number of customers who have canceled all of their subscriptions, offset by expansion or reactivation.
  • Net MRR Churn — the percentage or amount (in your primary currency) of MRR lost due to cancellations, offset by expansion and reactivation.
  • Quantity Churn — the percentage or number of subscription downgrades or cancellations, offset by expansion and reactivation.

Retention

  • Customer Retention — the percentage or number of customers who have one or more active subscriptions, including expansion and reactivation.
  • Net MRR Retention — the percentage or amount in your primary currency of MRR from active subscriptions and expansions, minus churn and contraction.
  • Quantity Retention — the percentage or number of subscriptions still active, including expansion, churn, and contraction.

Conversion

  • Conversion of non-subscription customers to subscribers — the number or percentage of customers who previously made a non-recurring purchase and then purchased a subscription in the selected month. (Available on our Scale and Volume plans)

Configuring your analysis

Starting month

Select a time frame for your analysis using the Starting month drop-down menu.

Screenshot of the Starting month drop-down menu allowing you to select a year and month

Show

Use the Show drop-down menu to choose Rate (%) or, depending on the cohort analysis you select, Customers, MRR, Quantity, or Conversion.

Screenshot of the Show drop-down menu with two options: Rate (%) and MRR

Relative to

If you select Rate (%) from the Show drop-down menu, you can use the Relative to drop-down menu to choose Previous month or Starting month.

Screenshot of the Relative to drop-down menu with two options Previous month
  and Starting month

With Previous month, ChartMogul calculates the metric as a rate relative to the previous month. With Starting Month, ChartMogul calculates it relative to Cohort Value.

Include current month

Select Include current month to get the most up-to-date insights by including data for the current month in your analysis.

Screenshot of the Include current month checkbox

Understanding the data

Cohorts

A customer joins a cohort when they become a subscriber for the first time, i.e., when their status changes from Lead to Active. Each customer remains in their original cohort regardless of whether they sign up for or purchase a second subscription (expansion) or cancel (churn) and re-subscribe (reactivation).

Months

Follow the development of each cohort by month, starting with month 0 (when the customers subscribed) and continuing for each whole calendar month of the cohort’s existence.

For example, for a customer who subscribed on April 19, month 0 is April 19–April 30, month 1 is May 1–May 31, month 2 is June 1–June 30, and so on.

While the actual dates for a specific month (e.g., month 3) are different between cohorts, what makes them valuable from an analysis perspective is their distance (in months) to sign up. Knowing, for example, that churn peaks in month 3 is an important insight.

Cohort Value

Depending on the cohort analysis you select, Cohort Value represents one month of:

  • Total MRR (in your primary currency)
  • Number of customers
  • Number of subscriptions acquired

In the following example, the total MRR for subscriptions sold in August 2020 was $9,943.

Screenshot of a cohort table showing the percentage of MRR churn relative to the previous month with the Cohort Value column highlighted

Metrics

Depending on the cohort analysis you select, ChartMogul displays one of the following metrics in table cells:

  • Conversion — the number of non-subscription customers who started a subscription
  • Customers — the number of active customers after churn, expansion, and reactivation
  • MRR — the amount of MRR after churn, expansion, and reactivation
  • Quantity — the number of active subscriptions after churn, expansion, and reactivation
  • Rate (%) — the percentage in change, either relative to the previous month or the starting month

In our example, 5.34% of customers in the June 2020 cohort churned in month 1.

Screenshot of a customer churned cohort table showing a 5.34% churn rate in month 1 for the June 2020 cohort

Select the cell to see a complete list of churn activities.

Screenshot of the Activity table containing a list of MRR movements, each with a description, value, type, and date

Average

The Average row provides an average of Cohort Value and each month of the analysis. ChartMogul accounts for cohort size (i.e., the number of customers) when calculating these averages.

For example, in a given month, a cohort of two customers experiences 50% churn while a cohort of 100 experiences 25%. The average churn rate (across the two cohorts, weighted by number of customers) is 25.49% (total number of customers lost / total number of customers) and not 37.5% (the average of the two percentages).

Learn more about weighted averages.

Segmenting cohorts

Using segmentation as part of your cohort analysis in ChartMogul helps you answer even more complex questions like:

  • When does a particular pricing plan experience its highest churn?
  • Which sales representative has the highest retention rate?
  • How does NPS score correlate with churn rate?

Screenshot showing the placement of the New Segment and Add Filter buttons above a cohort table

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