Logo Churn

The Logo Churn Rate report (also commonly referred to as Customer Churn Rate) tracks the percentage of active, paying customer accounts (or "logos") that were lost during a specific period. It is a fundamental indicator of customer retention health, directly influencing key long-term metrics like Customer Lifetime Value (LTV).

Logo Churn Rate is calculated by dividing the number of customers who churned during a period by the number of active customers at the start of that period.

$$\text{Logo Churn Rate} = \frac{\text{Churned Customers}}{\text{Active Customers at Start of Period}}$$

For an in-depth explanation of logo churn as a metric, see the Logo churn guide in the SaaS Metrics Academy.

Overview

The Logo Churn Rate report includes a timeline chart and a breakdown table. This report is crucial for understanding the stability of your customer base. The breakdown table cells are not clickable and there is no detail table.

Timeline chart

The timeline chart displays two lines:

1. Logo Churn Rate (Red Line):

   This is the primary metric, showing the calculated churn rate for the selected period.

2. Average 6 Months (Grey Line):

   This line represents the rolling average of the Logo Churn Rate over the previous six months. Churn data can be notoriously noisy (e.g., a single large customer churn in one month can spike the rate), making the 6-month average a valuable tool for identifying the underlying long-term trend, rather than short-term volatility. This smoothed rate is typically used in predictive models, such as the calculation for Customer Lifetime Value (LTV report).

The report employs a specific time-window convention to ensure meaningful data, especially at daily or weekly intervals:

• Monthly Aggregation:

  If you select an Interval of daily, weekly, or monthly, the churn calculation is performed on a month-to-month basis. This means the churned customers for the preceding month are compared against the active customers at the start of that month, reducing noise and providing a standardized rate that is comparable across your entire history.

• Quarterly/Yearly Aggregation:

  If you select quarterly or yearly, the churn is calculated on a quarter-over-quarter or year-over-year basis, respectively.

The currently ongoing period is marked as a dashed line. You can adjust the chart data using the date picker, interval selector, and filters.

Breakdown table

The table underneath the chart displays a cohort-based view for each period, making it explicit that each data point compares today's state to the cohort that existed 1 or 12 months ago (depending on the trailing window selected).

Note that customers acquired inside the lookback window are excluded — they were never part of the cohort being measured.

The Logo Churn Rate and the 6-Month Average are typically shown in red to visually emphasize the loss of customers.

Choosing the trailing window

The chart toolbar includes a trailing window selector that lets you switch between two ways of measuring churn:

• Trailing 1 month (default)

  Each point compares today's state to the customer base 1 month earlier. This matches typical monthly retention reporting and is the right view for operational use — week-to-week management, finding spikes, and identifying recent churn drivers.

• Trailing 12 months (TTM)

  Each point compares today's state to the customer base 12 months earlier. The 12-month view smooths out volatile months and matches how investors and benchmarks typically discuss annual retention. Use it for board reporting and longer-term trend analysis.

In both modes, customers acquired inside the lookback window are excluded from the calculation — they were never part of the cohort being measured against.

A worked example

Suppose you're looking at the trailing 1-month view as of Apr 30, 2026. The cohort is every customer paying on Mar 31, 2026. Six customers are in the picture:

• Original customers = 4 (Anna, Ben, Cleo, Dan)
• Churned = 1 (Dan)
• Logo churn = 1 ÷ 4 = 25%

A common gotcha: Eli signed up and cancelled inside the window, but his cancellation does not count as churn — he was never part of this cohort. The metric is asking "of everyone paying on Mar 31, how many had stopped paying by Apr 30?" Eli's brief subscription will only enter a future cohort if he's paying when that window opens.

Fiona's reactivation appears elsewhere (as a reactivation movement that increases your total customer count), but for cohort churn she's neither original nor churned in this window.

The trailing 12-month view follows exactly the same logic, just with a wider window — cohort = everyone paying on May 1, 2025, comparison runs through Apr 30, 2026:

A wider window means more customers join and leave inside it, so more get excluded — but only the starting cohort counts toward Original, Retained, and Churned.

Filters

The report supports a wide range of filters to help you analyze churn within specific segments. These include:

• Date range

  Select a custom range or preset periods (last 30 days, last quarter, etc.)

• Interval

  Choose how the rate is displayed: daily, weekly, monthly, quarterly, or yearly. Note the monthly calculation convention explained above.

• Additional filters – plan, region/country, billing frequency, customer age (time since signup), etc. (see all filters)

Filters are applied to both the chart and the table simultaneously.

Exporting the data

You can export the table as a CSV file for offline analysis or reporting by clicking the "Export" icon next to the date picker.

Practical tips

• Focus on the Grey Line: For strategic planning (like LTV analysis, hiring, or capacity planning), rely on the Average 6 Months (Grey Line) to smooth out noise and understand the true long-term trend of customer retention.
• Investigate Spikes: Use the Red Line to spot anomalies. If the Logo Churn Rate significantly spikes above the 6-month average, investigate the customers in that period immediately, as it may signal a product bug, pricing change, or unexpected competitor action.
• Isolate Problem Areas: Use Additional filters to segment churn by the reason for cancellation (if collected) or the initial plan type to prioritize efforts to plug the largest retention leaks.