Commercial Due Diligence
Executive Summary
Key Takeaways
- ✓ Commercial due diligence tests whether the market and customer conditions underlying a target's historical and forecast revenue are likely to persist, a question financial due diligence alone cannot answer since it is scoped to the reliability of reported figures, not the durability of what produced them.
- ✓ Customer concentration analysis is a core commercial due diligence output, since a target with revenue concentrated in a small number of customers carries a structurally different risk profile than one with a diversified base, independent of current reported performance.
- ✓ Market sizing and competitive positioning findings should translate into an explicit, evidenced growth rate assumption in the transaction model rather than an unsupported management-case growth figure carried forward unchallenged.
- ✓ Commercial due diligence is the workstream most directly responsible for testing the forecast assumptions a target's own management case relies on, since management has an inherent incentive to present an optimistic growth case during a sale process.
- ✓ A commercial due diligence finding on customer churn or contract renewal risk should flow into the transaction model as an explicit, traceable haircut to a specific revenue driver, not a generic discount applied to the entire top line.
Objective¶
This guide covers commercial due diligence — the workstream testing whether a target's market position, customer base, and competitive dynamics support its historical and forecast revenue — within the M&A and Transaction Due Diligence pillar. It complements Financial Due Diligence, which tests whether reported figures are reliable, by testing whether the conditions that produced them are durable.
Core Areas¶
| Area | What It Tests | Model Effect |
|---|---|---|
| Market sizing and growth | Whether the addressable market supports the forecast growth rate | Top-line growth forecast driver |
| Competitive positioning | Whether the target can defend or grow share against identified competitors | Market share assumption within the growth driver |
| Customer concentration | Revenue dependency on a small number of customers | Customer-specific churn or retention assumption |
| Contract and pricing terms | Revenue durability under existing customer contracts, pricing power | Revenue recurrence assumption, pricing driver |
| Management case testing | Whether the seller's own growth forecast is independently supportable | Base case versus management case gap, flagged for the deal team |
Customer Concentration¶
A target whose revenue is concentrated in a small number of customers carries a structurally different risk profile than a diversified peer, independent of current reported performance — the loss of a single major customer can materially affect future results in a way average historical growth rates do not capture. Commercial due diligence should quantify concentration explicitly (for example, the percentage of revenue from the top five or ten customers), assess contract renewal timing and terms for each material customer, and translate any identified risk into a specific, named adjustment in the transaction model rather than a general caution noted in the report.
Translating Findings into Model Drivers¶
Commercial due diligence's value is realized only when its findings become traceable transaction model inputs:
Untraceable: Revenue growth assumption reduced by 2% "for market risk"
Traceable: Base case growth driver retained at management case level
− Customer A renewal risk (25% of revenue, contract expires Year 2): explicit churn scenario
− Market growth moderation (independent sizing vs. management case): specific bps adjustment,
sourced to named market data
See Scenario Analysis and Sensitivity Analysis for how commercial due diligence findings are typically represented as a range rather than a single point estimate, particularly where customer renewal or market growth outcomes are genuinely uncertain at the time of signing.
Structural Checks Specific to Commercial Due Diligence¶
| Check | What It Catches |
|---|---|
| Customer concentration is quantified and each material customer's contract status is individually assessed | An undisclosed dependency on a customer whose contract is expiring imminently |
| Market sizing is independently sourced, not solely derived from the target's own management case | A growth forecast that cannot be independently supported, carried into the model unchallenged |
| Every commercial finding maps to a specific, named revenue or growth driver in the model | A commercial risk noted in the report with no corresponding model adjustment |
| Base case versus management case growth gap is explicitly disclosed to the investment committee | A deal priced on an unvalidated, seller-favorable growth assumption |
Common Failures¶
- A management case growth rate carried into the transaction model without independent commercial testing, embedding the seller's optimism directly into the buyer's price.
- Customer concentration disclosed as an aggregate percentage without individual contract-level assessment of the largest customers' renewal risk.
- Commercial findings expressed qualitatively in a report ("moderate competitive risk") without a corresponding quantified, traceable model adjustment.
- Market sizing sourced solely from the target's own investor materials rather than independently verified third-party data.
Continue Reading¶
Prerequisites¶
- M&A and Transaction Due Diligence — the parent pillar
- Financial Due Diligence
Related Glossary¶
Related Technical Guides¶
How OXXON tests thisRun a free structural check with FMAE
Frequently Asked Questions
What is commercial due diligence?
The investigation of a target's market position, competitive dynamics, customer base, and revenue sustainability — testing whether the market and customer conditions underlying historical and forecast revenue are likely to persist, independent of whether the reported financial figures themselves are accurate.
How is commercial due diligence different from financial due diligence?
Financial due diligence tests whether reported historical earnings are reliable and normalized. Commercial due diligence tests whether the market and customer conditions that produced those earnings — market growth, competitive position, customer retention — are likely to continue, a forward-looking question a purely financial review does not address.
Why is customer concentration a central commercial due diligence focus?
Because a target with revenue concentrated in a small number of customers carries structurally higher risk than one with a diversified base — the loss of a single major customer can have a disproportionate effect on future performance regardless of how strong current reported results are.
How should commercial due diligence findings affect the transaction model?
As explicit, traceable adjustments to specific revenue or growth drivers — a customer concentration finding as a specific churn assumption on the relevant customer's revenue contribution, a competitive threat finding as a moderated market share growth rate — rather than a generic, unexplained discount applied to the entire forecast.
Why is commercial due diligence particularly important for testing a seller's management case?
Because management, in a sale process, has an inherent incentive to present an optimistic growth case, and commercial due diligence is the workstream specifically tasked with independently testing those growth assumptions against market sizing, competitive dynamics, and customer-level evidence rather than accepting the management case at face value.
Does commercial due diligence overlap with the target's own strategic plan?
It reviews and tests the target's strategic plan as one input, but is not limited to it — an independent commercial due diligence provider builds its own market sizing and competitive analysis, since relying solely on the target's own plan would not independently validate the assumptions a buyer is being asked to pay for.
Related Articles
M&A and Transaction Due Diligence
Transaction due diligence is the structured process by which a party to a proposed transaction — most often a buyer, but also a seller preparing for sale or a lender financing the deal — investigates a target business before committing capital. It is organized into distinct workstreams (financial, commercial, operational, technical, legal, tax, ESG), run from one of three process postures (buy-side, sell-side, or vendor), and its findings feed directly into the financial model used to price the transaction and support the investment decision. This page is the hub for the Knowledge Centre's transaction due diligence content: what due diligence is, how each workstream and process posture differs, and how model risk specifically enters a transaction — the angle this platform is built to address in depth.
Financial Due Diligence
Financial due diligence investigates a target company's historical financial performance — earnings quality, working capital trends, net debt, and off-balance-sheet obligations — to establish a reliable, normalized baseline before a transaction is priced. It is distinct from a forward-looking financial model review: financial due diligence establishes what actually happened historically and whether reported earnings are a reliable indicator of sustainable performance, while a model review tests whether the forecast built on top of that baseline is structurally sound. This guide covers financial due diligence's core areas and how its outputs — normalized EBITDA, the net working capital peg, net debt — flow directly into deal pricing.
Forecast Driver
A forecast driver is a labelled input cell, most commonly a growth rate, a margin percentage, a unit count, or a price, that a forecast formula references rather than embeds directly. It is the structural unit that makes a forecast auditable and sensitizable, because changing the driver cell changes every downstream calculation that depends on it, consistently and traceably. A forecast driver is structurally distinct from a hardcode, a value typed directly into a calculation cell with no traceable source, even where the two produce an identical output in a given period.
Revenue Forecasting Methods
Revenue can be forecast using several structurally different methods, and the choice of method has a direct effect on how defensible and auditable the resulting forecast is. This guide sets out the four principal methods used in institutional financial models — top-down forecasting from market size and share, bottom-up forecasting from unit economics, trend and growth-rate extrapolation from historical results, and cohort-based forecasting for subscription and other recurring-revenue businesses — with guidance on when each method is appropriate and how the methods can be combined within a single forecast.
Scenario Analysis
Scenario analysis is the process of recalculating a financial model's outputs under a defined set of alternative assumptions that together represent a coherent possible future state. Each scenario changes multiple assumptions simultaneously to reflect a plausible economic environment or operational outcome — for example, a scenario in which both construction costs are higher than expected and revenue is lower than expected during the ramp-up phase. Scenario analysis is distinct from sensitivity analysis, which changes one variable at a time while holding all others constant. Scenario analysis tests the model under internally consistent combinations of assumptions; sensitivity analysis tests the model's response to changes in individual variables in isolation.
Sensitivity Analysis
Sensitivity analysis is the quantitative assessment of how much a financial model's output changes when a single input variable is changed by a defined amount, while all other variables are held at their base case values. It measures the responsiveness — or sensitivity — of outputs to individual assumption changes. Sensitivity analysis is distinct from scenario analysis, which changes multiple assumptions simultaneously to reflect a coherent alternative state. Sensitivity analysis isolates the effect of individual variables; scenario analysis tests the combined effect of assumption sets.