A practical guide to SaaS due diligence and ARR diligence — how PE, growth equity, and M&A buyers test recurring revenue quality, retention, expansion, billings, and unit economics before underwriting a software multiple.
Software multiples price durable recurring revenue, not a marketing ARR slide. SaaS due diligence asks whether ARR is cleanly defined, whether logos and dollars retain, whether growth is new business or expansion of a fragile base, and whether billings, deferred revenue, and contract terms support the model. It sits next to commercial, quality of earnings, product, and technology diligence — not as a synonym for any one of them.
| Workstream | Core question | Typical output |
|---|---|---|
| Commercial DD | Is the market real and winnable? | TAM, win rates, competitive map |
| QoE | Is EBITDA cash-backed and sustainable? | Adjusted EBITDA, cash bridge |
| SaaS metrics DD | Is recurring revenue quality real? | ARR rollforward, NRR/GRR, cohorts |
Lock the definition: subscription only vs services, usage overage, professional services, hardware, marketplace take-rate, and one-time setup. Rebuild ARR from customer-level data: beginning ARR + new + expansion − contraction − churn = ending ARR. Flag annualization tricks, multi-year prepaid booked as ARR without support, and products labeled “recurring” that are project work in disguise.
Separate logo (customer count) churn from dollar churn and from contraction (downsell / seat loss). Map reason codes: product, price, champion loss, competitor, budget, M&A of customer. High logo churn with stable ARR often means dependence on a few expanding whales — fragile at exit.
Compute gross revenue retention (base without expansion) and net revenue retention (base + expansion − churn/contraction) on consistent cohorts (by start quarter or fiscal year). Read curves at 12 and 24 months. High NRR with weak GRR is a red flag: expansion may be masking a leaky base. Segment by product, segment (SMB vs mid vs enterprise), and acquisition channel.
Bridge billings to recognized revenue to deferred revenue. Test multi-year deals, invoice timing, collectability, and ASC 606 / IFRS 15 policy choices that can front-load growth. Compare cash collections to billings. A growth story that lives only in deferred revenue without collection quality is not the same as durable ARR.
Decompose growth into new logos vs expansion (seats, modules, price). Review price increase history and elasticity, land-and-expand motion, and whether expansion is organic product pull or one-time migrations. Map net-new ARR contribution by cohort age — mature cohorts that stop expanding change the multiple thesis.
CAC by channel, payback period, LTV assumptions, sales efficiency (magic number), and fully loaded customer support cost. Test top-10 / top-25 customer concentration, channel partner dependence, and single-cloud or single-integration lock-in. Tie back to customer concentration and GTM capacity for the plan period.
DI20-WELCOME) — useful for triage, not a full SaaS QoE.
| Stage | SaaS focus | Buyer action |
|---|---|---|
| Pre-LOI / IOI | ARR story, growth quality hypotheses | Public product, pricing, logo, competitive screens |
| LOI | Access to customer-level ARR and cohorts | Write data-room list into exclusivity workplan |
| Confirmatory | Rollforward, NRR/GRR, billings bridge | Rebuild metrics; stress-test IC model |
| SPA / close | Reps on metrics, earnout definitions if any | Align earnout metrics with diligence definitions |
| Post-close | Dashboard ownership, retention governance | Install monthly ARR/NRR pack for board |
| Signal | Severity | Why it matters |
|---|---|---|
| ARR includes PS, hardware, or one-time fees | Deal-Killer | Multiple applied to non-recurring revenue |
| No customer-level ARR; only management dashboards | Deal-Killer | Cannot verify rollforward or concentration |
| GRR weak while NRR looks “best-in-class” | High | Expansion masking a leaky base |
| Top 5 customers >40% of ARR with short terms | High | Exit multiple and financing risk |
| Billings far ahead of collections; AR aging weak | High | Revenue quality and cash conversion risk |
| Cohort curves improve only via redefinition | High | Metric gaming; not retention improvement |
| Price increases drive most expansion | Watch | May not repeat; customer pushback risk |
| CAC payback >24 months with soft retention | Watch | Growth capital intensity kills returns |
| Approach | Typical cost | Timeline | Best use |
|---|---|---|---|
| Full SaaS commercial + metrics DD | $25K–$150K+ | 3–8 weeks | Signed exclusivity, IC-grade underwrite |
| Boutique metrics rebuild only | $15K–$60K | 2–4 weeks | Clean data room, focused ARR questions |
| Public first-pass risk pack | $49 | Minutes to hours | Triage before LOI / shortlist |
Before LOI, buyers use structured public research to pressure-test whether a software story is likely to survive metrics diligence: product positioning, pricing transparency, customer logos, hiring velocity, competitive density, and capital history. After LOI, the same hypotheses drive the data-room request list — customer-level ARR, cohorts, billings bridges — so QoE and commercial advisors do not waste weeks on the wrong questions. The pack is screening research, not a substitute for a customer file rebuild.
⇧ Already delivered: Tesla (TSLA) · Alphabet (GOOGL) · Palantir (PLTR) — real orders, real SEC data, every claim source-cited.
Get a structured first-pass diligence pack on your target — useful input for SaaS growth-quality hypotheses, not a full metrics QoE.
Order report $39.20 → Free brief Sample PDF