Understanding early product adoption can reveal powerful signals about long-term retention. By analyzing churn in relation to the number of Monthly Active Users (MAUs), you can pinpoint which accounts are at greater risk of churning, and which are more likely to become loyal customers.

For the purposes of this guide, we define an account as "adopted" if it has at least three unique users who perform any activity (e.g., logging in) in each of the first three months after activation.

This guide shows you how to analyze MAU and its impact on churn by comparing accounts with more than three active users in the first 90 days to those with three or fewer.

Tracking early product adoption

To begin, you'll want to track how many users on an account were active during their first three months. If you’re not already importing this data into ChartMogul, check out our article on custom attributes.

Your customer usage data can be synced with ChartMogul via CSV upload or automatically using our API.

Once added, this custom attribute, called something like MAU_First_3M,  will appear on the customer record.

You can view and filter this attribute just like any other in ChartMogul.

Filtering your churn rate by monthly active users

To compare churn performance by product adoption level, navigate to the Customer Churn Rate report and follow these steps:

1. Click the Apply a filter or saved segment button.
2. Search for the attribute MAU_First_3M.
3. Create the filter is less than or equal to 3.
4. Click Add.
   
5. Repeat steps 1–4 to add another segment where MAU_First_3M is more than or equal to 4.

This will allow you to compare segments with strong early adoption vs. those with weaker adoption.

Comparing churn by monthly user activity

The chart above shows churn rate for two cohorts over a 7-month period:

• Accounts with 4 or more monthly active users in their first 3 months (shown in turquoise).
• Accounts with 3 or fewer monthly active users in their first 3 months (shown in dark blue).

What the data shows

Accounts with greater early product adoption churn significantly less over time. Notably, churn in low-usage accounts spikes sharply in November, while high-usage accounts maintain a lower rate throughout.

This pattern confirms what many SaaS teams have experienced anecdotally: accounts with broad early adoption are more likely to stick around.

Potential action items

• Enhance onboarding to encourage team-based adoption early, guiding new customers to invite additional users within the first 30 days.
• Set proactive CS triggers by flagging accounts with 3 or fewer active users after 60 days for potential outreach or intervention.
• Leverage product marketing to highlight high-value use cases across departments, motivating admins to bring more teammates into the product.

What we learned

Segmenting churn by monthly user activity gives you a valuable leading indicator of customer retention. By tracking and filtering based on this attribute, you can identify accounts at risk earlier, guide users more effectively and create CS and product experiences that retain more customers.

Ultimately, this approach lets you connect early product adoption to business outcomes, making your  retention strategy more data-driven.