SaaS M&A has an information asymmetry problem. The seller knows the data, computes the metrics, and presents the summary. The buyer trusts. This manifesto is the line in the sand.
When you buy a SaaS business, the seller hands you a CIM with a churn number. That number is computed using methodology choices the seller made. Every choice — whether to include downgrades, how to handle involuntary cancellations, which cohort to report — is legally defensible. Every choice happens to make the number smaller.
80% of SaaS acquisitions overpay because of this gap. The average real churn is 4.2x the reported number. On a $1M deal, that's $340K of evaporated value. The buyer never sees it coming because the methodology choices are invisible in a summary metric.
Trust the seller's churn number. Use a 40-point DD checklist that covers legal, financial, and operational risk but not revenue durability methodology. Negotiate price based on the CIM. Discover the real churn 4 months post-close.
Demand the raw subscription CSV. Compute churn five ways yourself. Flag concentration risk, annual-plan exposure, and zombie MRR before you close. Negotiate from data the seller can't manipulate. Know what you're buying.
This isn't an improvement on the old way. It's a completely different approach. The old way asks "what does the seller report?" The new way asks "what does the raw data actually show?" Those are fundamentally different questions with fundamentally different answers.
A summary metric computed by the party selling you the business is not due diligence. It's marketing. The only churn number that matters is the one you compute from the raw subscription export — customer ID, MRR, plan, status, dates. No aggregations. No filters. The raw CSV.
Logo churn alone is meaningless. Revenue churn alone is meaningless. You need both — plus net churn, gross churn, and cohort-adjusted churn — to see the full picture. When logo churn and revenue churn diverge, downgrades are hiding in the gap. One number can't show you that.
A 40-point checklist that says "ask the seller for the churn rate" is not protection — it's theater. Real due diligence is forensic: you're looking for the methodology choices that flatter the number, not trusting the number itself. ChurnLens automates that forensic analysis so every buyer can do it in minutes.
"Demand the raw CSV. Compute your own churn.
Stop trusting seller math."
The long-term vision: a SaaS acquisition market where buyer-side churn analysis is the default, not the exception. Where no buyer trusts a summary churn number. Where sellers know that any methodology tricks will be caught in minutes by automated analysis. When that happens, the information asymmetry closes. Deals get priced honestly. Buyers stop overpaying.
ChurnLens is the tool. The checklist is the entry point. The raw-data methodology is the principle. And the movement is every acquirer who reads this and demands the CSV on their next deal.
Hidden churn is revenue decay that headline metrics conceal: customers on annual plans who have already stopped using the product, paid accounts sitting inactive, or revenue concentrated in a few logos about to leave. A SaaS business can show flat MRR while its real retention is collapsing. ChurnLens surfaces these signals before you buy, so you price the deal on true revenue quality.
ChurnLens analyzes five dimensions: revenue concentration, logo retention, annual-plan churn risk, inactive paid accounts, and MRR decline patterns. Each is weighted into a single 0-100 revenue-quality score benchmarked against comparable SaaS businesses. The score tells an acquirer whether reported MRR is durable or propped up by customers who are one renewal away from leaving, all before the deal closes.
Purchase price is usually a multiple of recurring revenue, so overstated retention directly inflates what you pay. A business with 20% hidden annual-plan churn is worth far less than its MRR implies. Buyers who skip churn diligence discover the decay only after closing, when it is too late to renegotiate. ChurnLens gives that visibility during the evaluation window instead.
Watch for revenue concentrated in a handful of accounts, a widening gap between signups and active users, annual contracts that never renew, and MRR that grows only through discounting. Each pattern signals fragile revenue. ChurnLens automatically flags these red flags from uploaded revenue data and ranks them by how much they threaten the durability of the recurring revenue base.
| Risk dimensions scored | 5 |
|---|---|
| Revenue-quality score range | 0-100 |
| Built for | Acquirers, PE, founders |
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