The PE Deal Team's Guide to Commercial Due Diligence & Primary Research in 2026

If financial due diligence tells you where a company has been, commercial due diligence tells you where it's going — and whether the investment thesis behind your deal actually holds up against market reality.

In 2026, that distinction has never mattered more. Global PE dry powder has hit $3.7 trillion. Median buyout EBITDA multiples reached a record 11.8x in 2025. Nearly 80% of GPs expect multiples to stay flat in the coming year. The old return levers — multiple expansion and cheap leverage, which accounted for 59% of returns between 2010 and 2022 — are gone.

What's left is what's under the hood. Operational value creation now drives 75% of PE returns, which means the quality of your commercial diligence directly determines the quality of your returns.

This guide is a practitioner-level walkthrough of how to run commercial due diligence using primary research — expert interviews, B2B surveys, and channel checks. It covers the full deal lifecycle: from pre-LOI thesis testing through post-close value creation. It's written for the associate, VP, or principal who has 30 days, four concurrent workstreams, and a two-person deal team — and needs to walk into IC with proprietary insight their competitors don't have.

What Is Commercial Due Diligence in PE?

Commercial due diligence (CDD) is the systematic, forward-looking assessment of a target company's market position, competitive landscape, customer dynamics, and growth potential. It's conducted as part of the investment evaluation process, typically alongside financial, legal, tax, and operational diligence workstreams.

But CDD isn't just one workstream among many — it's the one that answers the question every other workstream depends on: will this business grow?

Where CDD sits in the diligence stack

Think of the diligence process as answering three sequential questions:

1. Quality of Earnings (QoE): Are the historical financials real? (Backward-looking)
2. Commercial Due Diligence: Will the business continue to perform — and can it grow? (Forward-looking)
3. Value Creation Planning: What specific operational levers will we pull to drive EBITDA growth post-close? (Action-oriented)

QoE validates the past. CDD validates the future. And the value creation plan turns CDD findings into an execution roadmap. Without rigorous CDD, your QoE is a rearview mirror and your value creation plan is a wish list.

What CDD actually covers

A thorough CDD workstream answers questions across five dimensions:

• Market: How big is the addressable market? What's the realistic growth rate? What are the secular tailwinds and headwinds?
• Customers: How sticky are they? What's the real churn rate vs. the CIM's version? What's willingness to pay? Would they expand, renew, or switch?
• Competition: Who are the real competitors (not just the ones management mentions)? What's the target's relative positioning on product, price, and service? Who's gaining share?
• Business model: Is the revenue model durable? Is there pricing power? What's the mix of recurring vs. non-recurring revenue, and how defensible is each stream?
• Growth potential: Are the growth initiatives in the management plan realistic? What would operators, customers, and competitors say about the target's ability to execute?

Why CDD Matters More in 2026 Than Ever Before

The macro environment has fundamentally changed the economics of PE deals — and every shift points in the same direction: commercial diligence is now the highest-leverage activity in the deal process.

The math has changed

A decade ago, 5% annual EBITDA growth could secure a 2.5x MOIC. Today's borrowing costs of 8–9% mean that same return now requires 10–12% annual EBITDA growth. That kind of growth doesn't come from financial engineering. It comes from commercial reality — real customers buying more, real markets expanding, real competitive advantages holding up.

Capital is abundant, quality assets are scarce

More than 40% of the dry powder ready for deployment has been available for the past two years — 15 percentage points higher than the five-year average. That aging capital creates deployment pressure, which means GPs are willing to pay up. Large-deal multiples ($500M+) averaged 15.8x over the last five years. At those prices, the margin for error on commercial assumptions is razor-thin.

LPs are watching

In a January 2026 survey, 53% of 300 LPs ranked a GP's value creation strategy as a top-five metric in selecting a manager — replacing sectoral expertise as the third-most-important factor. LPs aren't satisfied with paper gains anymore. For the first time since 2015, sponsor distributions have exceeded capital contributions, making DPI — actual cash returned — the primary predictor of a firm's survival. That means GPs need to buy right and execute, not buy and hope.

The top deal-killers are commercial

A recent StepStone/Bain survey of GPs showed that the two most common hurdles to completing deals in 2025 were inflated seller expectations and diligence red flags — specifically poor earnings quality, customer churn, and deteriorating commercial fundamentals. These aren't financial or legal issues. They're commercial issues. And they're identified (or missed) during CDD.

Diligence processes are getting longer and more granular

This has been a defining theme of 2025, and it's accelerating. Deal teams are asking more questions about customer dynamics, retention, and product-market fit than ever before. The bar for IC conviction has risen. Generic industry overviews don't cut it anymore — you need proprietary, customer-level insight.

The CDD Process: From Screening to IC

Here's how CDD typically unfolds in a real PE deal, with the primary research activities that should accompany each stage.

Stage 1: Deal screening & thesis formation (Pre-LOI)

Objective: Decide whether to pursue the deal and form an initial investment thesis.

What you have: A CIM, possibly a management presentation, and whatever desktop research you can assemble.

What you need: Independent validation that the market opportunity is real, the competitive position is defensible, and the growth story isn't just a slide deck.

Primary research at this stage:

• 2–4 expert calls with industry operators, former executives at the target, or adjacent-market participants
• Rapid channel checks to validate market positioning claims
• Desktop research to size the market and map the competitive landscape

Key output: An initial thesis with clearly articulated assumptions that need testing. A go/no-go recommendation on whether to proceed to LOI.

This is where most firms under-invest. The argument for starting primary research at screening is simple: PE firms analyse roughly 80 opportunities for every one investment they make. Primary research at the screening stage kills bad deals faster and builds conviction on good ones earlier. A handful of well-targeted expert calls at this stage can save you weeks of wasted diligence effort downstream.

Stage 2: Confirmatory diligence (Post-LOI)

Objective: Validate or invalidate each element of the investment thesis. Quantify the risks. Identify the value creation levers.

What you have: Access to a data room, management Q&A sessions, and a 30–45-day LOI window.

What you need: Deep, independent insight from the people who buy from, compete with, and operate alongside the target.

Primary research at this stage:

• 8–15 expert calls across customers, competitors, former executives, and industry specialists
• B2B survey of 30–100+ customers to quantify satisfaction, churn risk, competitive positioning, and willingness to pay
• Channel checks with distributors, resellers, VARs, systems integrators, and sales reps
• Targeted calls on specific risk areas identified during thesis formation

Key output: Updated financial model assumptions (base, upside, downside). Identified risks with quantified impact. Preliminary value creation hypotheses.

Stage 3: IC preparation & decision

Objective: Synthesise all diligence findings into a compelling, evidence-backed investment recommendation.

What matters: Your IC doesn't want to read 15 call transcripts. They want to see: what did we learn, what does it mean for the model, and what are the three things that could go wrong?

Key output: IC memo with thesis validation (or challenge), key risk factors with mitigation plans, and a preliminary value creation plan directly informed by CDD findings.

Stage 4: Post-close handoff

Objective: Transfer CDD insights to the operating team so they can actually execute on them.

This is where most firms drop the ball. Diligence insights die in the IC memo. The operating partner or portfolio company CEO never sees the customer feedback, the competitive intelligence, or the market sizing work. The result is post-close value destruction — not because the insights weren't generated, but because they weren't transferred.

Best practice: Create a structured handoff document that translates CDD findings into specific value creation initiatives with owners, timelines, and KPIs.

The Role of Primary Research in CDD

Desktop research — industry reports, public filings, analyst notes, news articles — gives you the baseline. Every deal team has access to it. It's table stakes.

What separates rigorous CDD from box-ticking is proprietary primary research: original, first-hand data collection that produces insight your competitors don't have. The CIM is a sales document. Management presentations are, by definition, biased. Without independent validation from the people who actually buy from, compete with, and operate alongside the target, you're making a multi-million-dollar decision based on one side of the story.

There are three primary research methods that matter in CDD. Each serves a different purpose, and the best diligence programs use all three.

Expert calls

What they are: Structured interviews (typically 45–60 minutes) with former executives at the target, customers, competitors, suppliers, and industry specialists.

What they deliver: Qualitative depth. Contextual understanding. The "why" behind market dynamics, competitive shifts, and customer behaviour. They surface insights that don't appear in any database or report — because they live in the heads of practitioners who've operated in the market.

When to use them: Throughout the deal lifecycle, but especially during thesis formation (to test assumptions quickly) and confirmatory diligence (to go deep on specific risk areas).

What "good" looks like: An expert call that changes a financial model assumption or validates/invalidates a specific element of the investment thesis. If a call doesn't do either of those things, it was wasted.

B2B surveys

What they are: Quantitative research among customers, prospects, or market participants — typically 30–100+ respondents — designed to measure satisfaction, churn risk, competitive positioning, pricing sensitivity, and adoption trends at scale.

What they deliver: Statistical defensibility. Where expert calls give you qualitative depth from 5–15 voices, surveys give you quantitative breadth from dozens or hundreds. An IC can debate anecdotes from three expert calls. It's harder to debate a data set showing 40% of customers are evaluating alternatives.

When to use them: Confirmatory diligence, particularly when you need to validate customer satisfaction, NPS, competitive positioning, or willingness to pay across a large customer base.

The 2026 shift: Surveys have moved from a defensive "check-the-box" exercise to a proactive strategic weapon. With higher entry multiples and longer holding periods, the quantitative data from a diligence survey doesn't just inform the IC decision — it directly feeds the value creation plan. Pricing headroom identified in a survey becomes Day 1 pricing action. Churn risk data becomes a customer success initiative. Product gaps become roadmap priorities.

Channel checks

What they are: Systematic primary research that gathers information from a company's distribution and sales ecosystem — VARs, systems integrators, sales reps, partners, distributors.

What they deliver: Ground-level commercial intelligence. Channel checks tell you what's actually happening in the market: who's winning deals, who's losing them, what customers are saying to their reps, where pricing is headed, and whether the target's growth claims match reality on the ground.

When to use them: Pre-LOI for rapid market validation, and post-LOI for detailed competitive and commercial analysis. Particularly valuable in sectors with indirect distribution channels (software, healthcare, industrials).

How to Structure Primary Research Around a Deal

The difference between primary research that changes outcomes and primary research that fills binders comes down to three things: thesis-driven questioning, precise expert selection, and disciplined triangulation.

Start with the thesis, not the topic

Every primary research effort should begin by articulating the specific investment thesis assumptions you need to validate or challenge. Not "learn about the market" — that's a topic. Instead:

• Thesis assumption: "The target has 60%+ customer retention because switching costs are high."
• Research question: "What would it cost a mid-market customer to switch from the target's platform to a competitor? What specifically creates lock-in? Are there emerging alternatives that reduce those switching costs?"

Map your entire primary research programme to 4–6 thesis assumptions. Every call, every survey question, and every channel check should tie back to one of them.

Ask better questions

Top investors frame ultra-specific inquiries. Instead of "Tell me about electric-vehicle charging," they ask, "How do commercial fleet operators in Texas justify Level 3 charger ROI under current utility tariffs?" That precision reduces expert confusion and ensures you're speaking with someone who has lived through those exact scenarios.

A practical framework for expert call questions:

1. Context questions (10%): Establish the expert's vantage point and credibility on the specific topic.
2. Thesis validation questions (60%): Directly test your investment thesis assumptions with specific, falsifiable questions.
3. Risk and downside questions (20%): "What could go wrong? What would cause this business to lose customers? What's the biggest competitive threat that isn't obvious from the outside?"
4. Value creation questions (10%): "If you were running this business, what would you do differently? Where is there obvious low-hanging fruit?"

Select experts with precision

If you've ever taken a call where the "expert" clearly skimmed your thesis 10 minutes beforehand, you know exactly why the volume-first model fails PE teams. The traditional approach — cast a wide net, hope for relevant matches — wastes time and produces shallow insight.

What matters is operator-level relevance:

• For customer validation: Actual decision-makers at the target's customers — the person who signed the contract, manages the relationship, or decided to renew (or churn).
• For competitive intelligence: Sales leaders, product managers, or executives at direct competitors who see the target in competitive situations.
• For operational insight: Former C-suite or VP-level operators at the target who understand cost structures, growth initiatives, and organisational dynamics.
• For market context: Industry analysts, trade association leaders, or adjacent-market operators who can size the opportunity independently.

Triangulate relentlessly

No single expert has complete information or unbiased views. Leading PE firms triangulate across 5–15 expert perspectives per deal to identify consensus views and outlier opinions that require deeper investigation.

Triangulation means deliberately seeking perspectives that might contradict each other:

• What does the customer say about the target's product quality vs. what the competitor says?
• What does the former executive say about growth potential vs. what the channel partner sees on the ground?
• What does the survey data show about satisfaction scores vs. what individual expert calls reveal about churn reasons?

Where perspectives converge, you have high-conviction findings. Where they diverge, you have the areas that need the most attention — and potentially the highest-value insights.

Update the model after every call

This is the single most important discipline, and it's the one most teams skip. After every expert call, the diligence team should update base case, upside, and downside scenarios based on what was learned. If you're not changing assumptions, ask yourself: did the call actually tell you anything new? If not, your question design or expert selection needs work.

Choosing Your Research Infrastructure

There are three primary models for executing CDD research, and each fits different situations. The right answer depends on deal size, timeline, internal bandwidth, and the depth of insight required.

Option 1: Management consulting-led CDD

What it is: A full-scope engagement with a strategy consulting firm (Bain, L.E.K., McKinsey, EY-Parthenon, Strategy&). They conduct deep market sizing, competitive analysis, and customer interviews, and deliver a comprehensive CDD report.

Typical cost: $200K–$500K+

Typical timeline: 3–6 weeks

Best for: Large platform deals ($500M+) where the investment committee needs a brand-name imprimatur on the commercial thesis. Complex, multi-segment businesses. Situations where the deal team needs full-scope market analysis beyond what primary research alone can provide.

Limitations: Expensive. Slow to mobilise. Much of the deliverable may be market-level analysis that doesn't directly feed model assumptions. May lack the depth of customer-level insight that comes from dedicated primary research.

Option 2: Expert networks (self-serve)

What it is: Platforms like Third Bridge, AlphaSights, GLG, and Guidepoint that connect you directly with experts. You write the brief, review profiles, schedule the calls, conduct the interviews, and synthesise the findings.

Typical cost: $500–$1,500 per call

Typical timeline: 1–3 days to schedule a call

Best for: Teams with sufficient bandwidth to run calls themselves. Situations where you need one or two targeted conversations on a specific topic. Firms with established internal processes for expert call synthesis.

Limitations: Resource-intensive internally. If you're running five angles, you're developing five expertise criteria lists and evaluating approximately 50 potential advisors — all while running other workstreams. Expert quality and relevance can be inconsistent. You get transcripts, not analysis.

Option 3: Done-for-you primary research

What it is: Outsourced primary research where a specialised provider handles the entire process end-to-end — expert sourcing, discussion guide development, interview execution, synthesis, and delivery of finished research outputs.

Best for: Deal teams that are bandwidth-constrained (which is most of them). Situations where you need 8–15+ expert perspectives synthesised into actionable findings. Teams that want finished outputs — not raw transcripts they have to process themselves. Mid-market deals where a full CDD consulting engagement is overkill but DIY expert calls don't provide enough coverage.

Key differentiator: No scheduling calls, no writing discussion guides, no synthesising transcripts. You brief the provider on your thesis, and they deliver the insight.

When to combine approaches

The smartest deal teams don't pick one model exclusively — they layer them based on what the deal requires:

• Pre-LOI: Done-for-you expert calls and channel checks for rapid thesis validation
• Post-LOI (large deal): CDD consultant for full market analysis + done-for-you primary research for deep customer and competitive insight + B2B survey for quantitative validation
• Post-LOI (mid-market): Done-for-you primary research as the core CDD workstream + targeted self-serve expert calls for ad hoc questions that emerge during diligence

Common Mistakes and How to Avoid Them

After working across hundreds of PE diligence processes, these are the failure modes we see most often — and the fixes that work.

1. Treating CDD as box-ticking

The mistake: Running CDD because the process requires it, not because you're genuinely trying to challenge the thesis. Asking generic questions, checking obvious boxes, and producing a report that confirms what everyone already assumed.

The fix: Before you start any primary research, write down the three assumptions that, if wrong, would kill the deal. Those are your research priorities. Everything else is secondary.

2. Relying on management-curated customer references

The mistake: The target gives you five customer names. You call them. They say great things. You're shocked when post-close churn hits 25%.

The fix: Always conduct independent customer outreach. The customers management wants you to talk to are the happy ones. The ones they don't mention are where the real signal is.

3. Starting primary research too late

The mistake: Waiting until post-LOI to begin any expert outreach. By the time findings come in, the team is already emotionally committed to the deal and the LOI window is closing.

The fix: Start 2–4 expert calls during screening/pre-LOI. It costs almost nothing relative to the deal and gives you a massive head start on confirmatory diligence.

4. Confusing volume with quality

The mistake: Scheduling 20 expert calls because more feels more rigorous. Half the experts are loosely relevant. The team is drowning in transcripts.

The fix: 8–12 precisely targeted calls with thesis-driven questions will produce better insight than 20 generic ones. Every call should have a clear purpose tied to a specific thesis assumption.

5. Not updating the model

The mistake: Conducting expert calls and filing away the notes without changing any assumptions in the financial model.

The fix: After every call, ask: does this change our base case, upside, or downside? If the answer is consistently "no," your questions aren't specific enough.

6. Asking vague questions

The mistake: "Tell me about the competitive landscape in managed services." This invites a 45-minute monologue that covers everything and tells you nothing specific.

The fix: "When your company evaluated managed services providers last year, which vendors made the shortlist, and what was the deciding factor between them?" Specificity gets you specificity.

7. Failing to triangulate

The mistake: Taking a single expert's view as definitive. One former executive says the target's product is best-in-class, and that becomes gospel in the IC memo.

The fix: Deliberately seek contradictory perspectives. Talk to customers, competitors, and former insiders. Where views converge, you have conviction. Where they diverge, you have your risk areas.

8. Letting diligence insights die in the IC memo

The mistake: Brilliant CDD findings that never make it to the operating team. The portfolio company CEO starts from scratch on strategic priorities that were already identified during diligence.

The fix: Build a structured handoff process. Every CDD finding should have a corresponding value creation initiative with an owner, timeline, and success metric.

From Diligence to Value Creation

The best PE firms in 2026 don't treat CDD as a pre-close activity that ends when the deal closes. They treat it as the first phase of value creation.

This matters because the economics demand it. With entry multiples at record highs and borrowing costs of 8–9%, you can't afford a six-month "getting to know you" phase post-close. The clock starts on Day 1, and the insights from CDD should be actionable from Day 1.

How CDD findings translate to value creation initiatives

The key insight: diligence that identifies where the business can improve — not just whether it's "good enough" — is worth multiples of what it costs. It's the difference between buying a company and hoping, and buying a company with a clear playbook for value creation.

Survey data is particularly valuable here. Many portfolio companies lack the internal resources to run quantitative research themselves. The customer survey you commissioned during diligence becomes the baseline against which you measure every commercial initiative post-close.

AI in CDD: What's Real and What's Hype

Nearly half of dealmakers (49%) now use AI tools almost every day. AI is a real and growing part of the diligence toolkit — but it's critical to understand what it does well and where it introduces risk.

Where AI accelerates diligence

• Transcript analysis at scale: AI can process dozens of expert call transcripts and surface patterns, contradictions, and consensus views across a corpus — something that would take a human team days.
• Market mapping and deal sourcing: Tools like Grata use AI to identify and classify potential targets across fragmented markets.
• Synthesis and structuring: AI can organise unstructured information into frameworks, timelines, and risk matrices — compressing the time between data collection and actionable output.
• Pattern detection: Cross-referencing findings across multiple diligence workstreams to identify risk signals that might be missed in sequential review.

Where AI falls short

• AI does not replace expert judgment. It cannot assess whether a former executive's view of the target is credible, biased, or outdated. That requires human context.
• AI does not make investment decisions. It can surface data and patterns. It cannot weigh competing considerations, assess management quality, or build conviction.
• Generic AI models introduce risk. Open-web LLMs can hallucinate conclusions, lack traceability, create compliance exposure, and contaminate findings with unreliable sources. Institutional-grade diligence requires institutional-grade tools.
• AI due diligence is now its own workstream. EY-Parthenon and others now offer AI-specific diligence — assessing a target's use of AI capabilities across commercial, technical, and financial dimensions. This adds complexity, not simplicity, to the diligence process.

The bottom line: AI is a structural upgrade to how diligence operates. The firms that will outperform use AI to compress research cycles without sacrificing depth, detect risks earlier through pattern analysis, and maintain traceability at every stage. But AI doesn't remove the need for primary research — it makes the primary research you do more valuable by enabling faster, more thorough synthesis.

The Future of CDD: Five Trends Shaping 2026 and Beyond

1. Deeper, earlier commercial diligence

The best firms are pushing CDD earlier in the deal cycle — uncovering pricing headroom, customer-level margin opportunities, and competitive dynamics with far greater granularity to more confidently underwrite commercial upside. Expect pre-LOI primary research to become standard practice, not an exception.

2. Surveys as a core diligence weapon

Quantitative customer surveys have moved from a "nice to have" to a non-negotiable. With higher entry multiples and longer holding periods, the data from a diligence survey doesn't just inform the investment decision — it becomes the foundation for post-close commercial strategy.

3. Specialisation of research partners

Generalist consulting and market intelligence firms struggle to deliver customer-focused insights within PE timelines. This has created demand for specialised firms that can execute systematic primary research — expert interviews, surveys, channel checks — at speed and at the depth PE diligence requires.

4. AI integration into diligence workflows

2026 marks the shift from exploratory AI experiments to integrated, ROI-generating solutions embedded directly into commercial workflows. Pricing optimisation, deal scoring, sales prioritisation, and customer churn mitigation will be the breakout use cases.

5. Exit pressure reshaping diligence needs

With $3.2 trillion in unsold PE portfolio assets and LPs demanding distributions, exit preparation is becoming a major driver of CDD. Sell-side diligence — vendor due diligence supported by independent primary research — helps GPs build the buyer's confidence and accelerate exits.

Putting It All Together

Commercial due diligence is no longer a supporting workstream — it's the main event. In an environment where multiples are at record highs, leverage is expensive, and 75% of returns depend on operational improvement, the quality of your commercial diligence directly determines your returns.

The playbook is straightforward:

1. Start early. Begin primary research at the screening stage, not post-LOI.
2. Be thesis-driven. Map every research activity to a specific investment thesis assumption.
3. Use all three tools. Expert calls for depth, surveys for breadth, channel checks for ground-level intelligence.
4. Triangulate. Seek 5–15 perspectives and look for convergence and divergence.
5. Update the model. Every call should change an assumption or validate one. If it doesn't, fix your questions.
6. Choose the right infrastructure. Match your research approach to the deal size, timeline, and team bandwidth.
7. Connect diligence to value creation. Every CDD finding should have a corresponding post-close action item.

The deal teams that master this process don't just avoid bad deals — they walk into IC with proprietary insight their competitors don't have, they pay the right price, and they start creating value from Day 1.

If your team needs help executing primary research for an active deal — expert calls, surveys, or channel checks — without the overhead of doing it all in-house, get in touch with our team. We handle the entire process end-to-end, so you can focus on the investment decision.