ChurnLens is used at any point in a deal lifecycle where someone needs to independently verify a SaaS company's churn and revenue quality without relying on the seller's own dashboard. That spans three audiences: acquirers evaluating a target before LOI, founders preparing to sell (and wanting to know what a buyer will find), and investors underwriting a SaaS position. The use cases below describe what each audience is actually trying to surface — and what the cost of missing it is.
An acquirer has one shot, under exclusivity, to find the revenue quality problems that justify a price renegotiation. A founder preparing to sell has months to find and fix those same problems before a buyer uses them against them. An investor has a portfolio and needs a repeatable benchmarking layer across positions. The underlying analysis is the same — reconstruct churn from the ledger, flag zombie MRR, identify renewal cliffs, score revenue concentration — but the deliverable, the urgency, and the cost of a miss differ by audience. ChurnLens supports all three because the math does not change just because the chair you are sitting in does.
Pre-LOI and pre-close verification: find the revenue quality problems that move the purchase price.
Pre-sale preparation: run the analysis a buyer will run, before the buyer runs it.
Portfolio monitoring: catch the gap between reported and reconstructed metrics before the next round.
As early as you have a revenue ledger, ideally before LOI. The highest-leverage moment is right after you receive the data room but before you have committed to a price. If ChurnLens surfaces a 4× gap between reported and reconstructed churn, that is the evidence you use to either renegotiate the purchase price or walk. Running it after LOI is still useful for confirming representations, but you have already lost negotiating leverage.
Yes — this is one of the highest-ROI uses of ChurnLens. A buyer will run this exact analysis on your revenue ledger; running it yourself first tells you what they will find, gives you time to fix or contextualize the problems, and lets you pre-empt the negotiation rather than react to it. Founders who arrive at diligence with a clean ChurnLens report and explanations for every flagged anomaly consistently command higher multiples than founders who get surprised by their own numbers.
Yes, for portfolio monitoring. The same reconstruction that flags pre-close risk also flags portfolio companies whose reported metrics are drifting away from underlying reality — the earliest warning sign of a deteriorating position. Investors run ChurnLens quarterly on portfolio companies to catch the gap between reported NRR and cohort-implied NRR before it shows up in a down round.
ChurnLens — buyer-side SaaS revenue-quality and churn-risk due diligence. Learn more →