How acquisition teams use ChurnLens for revenue quality due diligence.
SaaS acquirers face a unique risk: buying a company whose revenue looks healthy but is about to collapse. ChurnLens provides the churn risk analysis that prevents bad acquisitions.
The highest-leverage moment for a SaaS acquirer is the window between receiving the data room and signing the LOI. That is when you still have negotiating leverage — the seller has not yet locked in a price, and any finding that materially affects valuation can move the deal terms. ChurnLens is built to run in that window: upload the revenue-ledger CSV from the data room, and within minutes you have a reconstructed churn analysis that either confirms the seller's reported numbers or quantifies exactly how far off they are.
The four findings that most commonly move the purchase price are: zombie MRR (paid accounts with no product usage, certain to churn at next renewal), annual-plan renewal cliffs (revenue concentrated in contracts expiring on the same date), revenue concentration (a top-5 logo whose departure would shift headline churn by double digits), and the gap between reported net revenue retention and cohort-implied NRR. Each is quantified to a specific dollar amount of MRR at risk, giving you defensible evidence for a price adjustment rather than a gut feeling.
SaaS churn analytics and revenue retention intelligence
Try ChurnLens →ChurnLens analyzes the target's customer data to surface churn risks that are not visible in top-line MRR. This prevents overpaying for a business with hidden retention problems.
ChurnLens — SaaS churn analytics and revenue retention intelligence. Learn more →
The saas acquirers workflow with ChurnLens follows a consistent pattern: ingest the revenue ledger, reconstruct the core metrics under a standardized definition, flag the decay signals that precede headline churn, and produce a report that maps each finding to a specific dollar amount of MRR at risk. The entire analysis runs in minutes from a CSV upload — no live integration, no 90-day onboarding, no dependency on the seller's billing system.
The output is structured around the four failure modes that most commonly cause SaaS acquisitions to underperform post-close: zombie MRR (paid accounts with no usage, statistically certain to churn at next renewal), annual-plan renewal cliffs (revenue concentrated in contracts that expire on the same date), revenue concentration (a single top-5 logo whose departure would move the headline number), and cohort decay (newer customers retaining worse than older ones, signaling product-market-fit erosion). Each is quantified to a dollar figure so the findings are actionable in a price negotiation, not just diagnostic.