What Strong Commercial Due Diligence Looks Like

The LOI is signed. The management presentation was polished. The deck showed 120% net revenue retention (NRR) and a TAM that justified the multiple. Six months after close, churn accelerates, the sales pipeline stalls, and the pricing model turns out to be a patchwork of one-off deals the CRO calls "strategic flexibility." Your commercial thesis just got stress-tested by reality, and it lost.

The True Bill

Commercial due diligence failures don't surface as a single line item. They compound across your first 18-month value creation plan as a series of surprises that each seemed manageable in isolation.

A pricing architecture that looked like a $4M annual recurring revenue (ARR) opportunity during DD turns out to require 14 months of re-contracting work and a customer success team you don't yet have. A sales motion that appeared scalable based on annual contract value (ACV) growth turns out to depend on three enterprise reps who leave within 90 days of the acquisition announcement. NRR that looked like 112% was calculated to exclude a customer category accounting for 30% of logos.

The industry average for value creation plan misses in PE-backed (private equity) software is telling. Bain research puts the share of deals that underperform original commercial projections at roughly 50-60%. The commercial DD process is the single biggest lever for changing that number, and it's consistently underinvested relative to financial and legal diligence.

If your commercial DD is a two-week sprint driven primarily by management-provided data, you're pricing in a risk premium that's invisible on the model.

Execution

Three steps change the commercial DD outcome.

Step 1: Audit revenue quality, not just revenue quantity. Pull three years of cohort-level retention data directly from the CRM, not from a management-prepared summary. Look at logo retention, net dollar retention, and expansion revenue separately. A company can show strong NRR while bleeding logos in a specific segment. That's a very different business than the deck implies.

Step 2: Pressure-test the pricing model as a commercial system. Don't just benchmark the price points. Map the entire price realization path: list price, average discount, contract length, renewal uplift, and pocket price. A SaaS company pricing at $50K ACV with 35% average discounts and zero renewal uplift doesn't have a $50K ACV business. It has a $32K ACV business with aspirational branding. That gap is often worth $3-5M in earnings before interest, taxes, depreciation and amortization (EBITDA) improvement, or $3-5M in projected value creation that will never materialize without active intervention.

Step 3: Interview churned customers, not just current customers. Reference checks with active customers are selection-biased toward the most successful accounts. The companies that churned in the last 24 months will tell you why the product didn't deliver, where the service model broke, and whether pricing was a factor. Two hours of churned customer interviews will surface risks that 20 hours of document review won't find.

Where It Unravels

A growth equity firm acquired a vertical SaaS business at $28M ARR at a 9x revenue multiple. The commercial DD confirmed strong NRR and a growing enterprise segment. The value creation plan projected $52M ARR in three years, driven by enterprise expansion and a price increase implementation.

Eighteen months in, ARR was $31M. The enterprise segment NRR was 94%, not the 118% in the DD report. The discrepancy: the DD team had accepted the company's NRR calculation, which excluded implementation fees and included one-time professional services revenue in the expansion line.

The pricing model was effectively a floor rather than a structured architecture. Reps had been discounting 40-50% on enterprise deals for two years. The "price increase implementation" plan stalled because no rep had the commercial authority to hold price, and there was no deal desk to support them.

Before: $28M ARR, modeled path to $52M ARR in 36 months, NRR reported at 112%, 9x revenue multiple.

After: $31M ARR at month 18, revised projection of $39M ARR at 36 months, two quarters of enterprise churn requiring a full commercial model redesign.

The root cause wasn't a bad business. It was DD that validated reported metrics without interrogating the commercial architecture that generated them.

Move This Week

Pull the last 24 months of invoice-level data and calculate pocket price by customer segment independently of any management-provided NRR figure.

The gap between reported NRR and invoice-level pocket price retention is the single most reliable predictor of commercial surprises in the first 18 months post-close. If you can't calculate that gap today, you don't yet have a commercial DD process. You have a financial model that trusts its own inputs.

Assess Your Commercial Health to identify the specific commercial risks in your current pricing architecture before they become post-close surprises.

For more on how pricing architecture affects PE outcomes, read The Failure Case of Private Equity Value Creation. For the full hidden cost picture, see The Hidden Costs of Bad Commercial Due Diligence.