Logo churn rate
Logo churn rate is the percentage of customers — 'logos', meaning whole accounts — that cancelled during a period, counted by number of accounts rather than by revenue. It differs from revenue churn because each account counts equally regardless of size. A business can have low revenue churn but high logo churn if it loses many small accounts, or the reverse. It is a subscription convention; the window varies.
What this means
Logo churn rate = number of customers lost during the period ÷ number of customers at the start of the period. The word 'logo' is industry shorthand for a customer account. Each account is weighted equally — a one-seat account and a thousand-seat account each count as a single logo when they leave. This is the deliberate contrast with revenue churn, which weights by dollars.
Why it differs from revenue churn
Logo churn and revenue churn can diverge sharply. If a company loses many small accounts but keeps its large ones, logo churn is high while revenue churn stays low. If it loses one large account, the reverse happens. Neither is 'right' — they answer different questions. Logo churn signals breadth of attrition and product-market fit across the base; revenue churn signals the financial impact. The denominator (start-of-period accounts) and the window vary by vendor, so define them before comparing.
This page is educational and not financial advice.
- Lost accounts ÷ starting accounts, counted by logo
- Each account weighted equally, regardless of size
- Read with revenue churn to see where attrition lands
How it appears in analytics and logs
A high logo churn rate means many accounts leave even if total revenue holds; a low logo churn with high revenue churn means a few large accounts drive losses. Comparing the two locates where attrition concentrates.
Diagnostic use case
Track how many distinct accounts you lose, independent of their revenue, to spot broad attrition that revenue-weighted churn can hide.
What WebmasterID can help detect
WebmasterID measures engagement signals per account first-party; combined with billing status it helps flag accounts at risk of becoming churned logos without cross-site tracking.
Common mistakes
- Treating logo churn and revenue churn as the same metric.
- Ignoring that one large account can swamp revenue churn.
- Comparing logo churn across mismatched time windows.
Privacy and accuracy notes
Logo churn counts accounts in aggregate and needs no personal data beyond account identity already on file. This page is educational, not financial advice.
Related pages
- Gross revenue retention (GRR)
Gross revenue retention (GRR) measures how much of a cohort's recurring revenue survives churn and downgrades over a period, with expansion excluded. Because upgrades cannot count, GRR is capped at 100% — it can only stay flat or fall. It isolates raw stickiness, separate from a company's ability to upsell. GRR is a subscription convention and the exact construction varies by vendor.
- Net revenue retention (NRR)
Net revenue retention (NRR), also called net dollar retention, measures how much recurring revenue a fixed cohort of customers produces at the end of a period versus the start, counting upgrades (expansion) and subtracting downgrades (contraction) and churn — but excluding revenue from brand-new customers. Above 100% means the cohort grew on its own. It is a subscription-economics convention, and definitions vary by vendor.
- Churn rate
Churn rate measures how many customers (or how much recurring revenue) you lose in a period. Like retention, it is defined by choices: the window, what counts as 'churned', and whether you count customers or revenue. Customer churn and revenue churn can diverge sharply, so the basis must be stated.
- Web analytics
Flag at-risk accounts from first-party engagement.
Sources and verification notes
- U.S. SEC — investor guide to financial statementsBackground on customer/revenue concepts; logo churn is a subscription-economics convention.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.