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Sales Due Diligence

A sales due diligence checklist for mid-market PE

A checklist is only useful if each item can change your view. What follows is organised that way: five areas, the questions worth asking in each, and — the part most checklists omit — what a poor answer actually signals, because the same red flag can mean two very different things.

How to use it

Work top to bottom. The areas are ordered so that findings in the first change the interpretation of everything below. A weak answer in area five means something different if areas one and two are strong.

The five areas

AreaAskGood looks like
1 · Proposition & pricingWho is this for, and who is it not for? What is realised price against list, and is the dispersion widening?A clear ICP the team can state unprompted. Discount as a decision with an owner, not a habit.
2 · DemandWhere do opportunities come from, and what does acquisition cost do over three years?Demand largely earned. The business can say which channel produces customers who stay, not just who sign.
3 · Sales executionDo stage definitions describe something the buyer did? What is win rate by segment over time?Buyer-verifiable stages. Forecast error consistent enough to correct for. Variance the team can explain.
4 · RetentionIs renewal worked months ahead by a named owner? What does usage do before a churn?Retention managed rather than merely occurring. Churn reasons investigated, not just recorded.
5 · People, data & cadenceWho assembles the numbers? What happens in the weekly commercial meeting?One source of commercial truth. A rhythm that produces decisions rather than updates.

Red flags, and what each one actually signals

Most checklists stop at the flag. The signal is where the value is, because the same observation frequently has two possible causes with very different price implications.

What you seeIt might meanOr it might meanHow to tell
High churnThe product is not delivering valueThe business acquired badly through a channel it has since closedCut churn by acquisition cohort and channel. If recent cohorts are clean, it is the second.
Falling win rateSales execution has deterioratedThe proposition has drifted out of fitCheck variance between sellers. Narrow variance points upstream.
Excellent retentionCustomers love the productSwitching costs are high and nobody has had to defend itAsk what happened the last time a large account signalled it might leave.
Forecast always accurateDisciplined forecastingOnly already-won deals are being countedCompare commit accuracy against overall pipeline conversion. A large gap is the tell.
Revenue concentrated in two sellersA structural riskA genuine asset, if they are stayersTenure, comp, and whether they are in the retention package. Both readings can be true at once.
Rising acquisition costA marketing efficiency problemA proposition problem presenting as a marketing oneLook at conversion rate alongside cost. Flat conversion with rising cost points upstream.

What the gaps tell you

Some of the most useful findings are things that do not exist. Log these explicitly rather than chasing them quietly.

  • No stage history in the CRM. Opportunities are updated at close. The forecast is a conversation, not a calculation.
  • No closed-lost detail. The business does not systematically learn why it loses, so win rate can only improve by accident.
  • Realised price available only in aggregate. Nobody monitors discount at transaction level, which means nobody controls it.
  • Churn reasons uniformly “price”. Price is what customers say. It is rarely why they left.
  • No usage data. Common, not disqualifying, but contracted revenue cannot be tested for durability and that uncertainty should be priced.
  • Everything arrives fast but hand-built. The commercial function does not have systems, it has that analyst.

From checklist to plan

A completed checklist is a list of true observations. Turning it into something a management team will run needs two further judgements applied to every finding.

Materiality to this value thesis. A weak partner channel is critical in one business and irrelevant in another. Grading without reference to the plan produces long lists of accurate and useless notes.

Dependency. The largest opportunity is often the one most dependent on foundations that do not yet exist. Instrumentation first, then the things that stop value leaking, then the things that build.

What emerges is usually three to five workstreams from a checklist of forty-odd observations, each with a named owner inside the business, a measurable first milestone inside thirty days, and an explicit statement of what stops to make room. Expect one or two of them to actually complete inside the first year unless someone is dedicated to running the plan. Knowing which thirty-five findings to leave alone is a substantial part of the value.

A note on scope. This checklist reflects how Altius Partners structures commercial assessment as of 2026. It is tailored on every engagement to the value thesis, sector and available data, and is not a substitute for transaction-specific advice.

Frequently asked questions

What should a sales due diligence checklist cover?

Five areas: proposition and pricing, demand generation, sales execution, retention, and the people, data and cadence beneath them. Ordered so that findings in the earlier areas change how you interpret the later ones.

What is the most common red flag?

Pipeline stages that describe the seller's state of mind rather than something the buyer did. It makes every downstream number unreliable, and it is among the cheapest things to fix.

How many findings should become workstreams?

Usually three to five out of forty or so observations. Deciding what to leave alone is as important as deciding what to act on, because in practice most businesses complete only one or two in the first year after a deal, unless someone is dedicated to running the plan.

Can this checklist be run internally?

Much of it can, particularly by an operating partner with commercial background. The parts that are hardest to do internally are reading seller behaviour from CRM records and interviewing customers who have left.

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