Before They Buy You, Investors Call Your Enemies

Every few weeks another mid-market deal gets repriced at the last minute, and the seller never sees it coming. The financials looked clean, the management presentation was polished, the data room was complete and yet the offer dropped, or the deal quietly died. In almost every case, the reason wasn’t in the numbers. It was in a phone call the seller never knew happened.

Before a fund buys a company, it rarely trusts the data room alone. It calls the people around the target, former employees, key customers, churned accounts, suppliers, and rival operators to hear how the business actually behaves when no one is preparing a slide for it.

In our diligence work at Nexus Expert Research, these conversations are the single most common place a deal thesis either hardens or falls apart. They’re usually run as structured 45–60 minute calls through expert networks, focused on unit economics, demand durability, and the risks that never make it into a pitch deck. They’re discreet, but entirely legal: as long as experts stay away from material non-public information (MNPI) and NDA-protected details, this off-channel research is now a routine pillar of institutional due diligence.

Here’s what actually happens on those calls, who gets called, what gets asked, and where the line sits.

Why the numbers on paper are never enough

On-paper performance rarely tells you how a business behaves with its customers, staff, and partners. That gap is exactly what buyers are trying to close.

Commercial and operational due diligence pairs document review with direct conversations, giving a fund a grounded view of the customer base, supplier relationships, and day-to-day operations beyond what the seller chose to show. The point isn’t to catch anyone lying, it’s to check whether reported performance and pipeline quality match what stakeholders see on the ground.

So deal teams triangulate. They compare management’s claims against what customers say about reliability, what ex-employees say about culture and churn, and what suppliers say about payment discipline and bargaining power. That mix of perspectives is often what moves a model from “looks fine” to “now we actually understand the risk.”

Take a pattern that recurs across software diligence. Management reports low logo churn and files most departures under “budget.” Then three churned-customer calls independently describe the same onboarding failure, accounts that never reached first value and quietly left. Suddenly the churn story is about product, not price, and the buyer’s growth assumptions look very different. None of that was visible in the data room; all of it came from three phone calls.

Who investors really call outside the target

Buyers don’t call random insiders. They systematically target specific groups, each answering a different question.

Former employees and ex-executives

Ex-management and senior operators have lived inside the company but no longer have any incentive to sell a story. They can describe how strategy was actually executed, why key initiatives stalled, and how decisions really got made, the kind of context that never appears in board minutes. With proper cooling-off periods in place, they can share experience and high-level patterns without touching MNPI.

Key and churned customers

Active customer calls test how painful the problem really is, how essential the solution feels, and whether pricing is seen as fair or opportunistic. Churned-customer calls are often more valuable still: they reveal the true reasons accounts leave service gaps, product limits, a competitor’s move, which internal churn codes routinely mislabel.

Strategic suppliers and channel partners

Suppliers and partners expose bargaining power, margin pressure, and operational reliability. A logistics partner knows how often shipments slip. A distributor knows whether it actually prioritizes the target’s products over a rival’s. These calls surface concentration risk, informal incentives, and contract dynamics that dominate a buyer’s downside scenarios.

Industry rivals and adjacent operators

Operators in similar businesses can benchmark the target’s pricing, product quality, and go-to-market discipline against peers. That outside-in view answers the question every valuation depends on: is this growth a genuine advantage, or just a good year in a good market?

What they ask and the signals they’re hunting

Unit economics and real demand

First, buyers want to know how money actually moves through the business: customer lifetime value, payback periods, discounting behavior, and whether margins are sustainable or inflated. They’re listening for tells like “we had to discount hard to close” or “we love the product but procurement hates the pricing”, throwaway lines that can reshape an entire model.

Product, operations, and talent

Next, reliability and execution. How often do outages happen? How fast do they get resolved? Is the frontline empowered to fix problems or buried in bureaucracy? On people, the signals are patterns, not one-offs: high voluntary turnover in a core function, inconsistent performance management, or a company that reorganizes every eighteen months.

Hidden risks and deal-breakers

Finally, the calls are built to flush out what could break the business but isn’t visible on a spreadsheet, top churn drivers, regulatory exposure, and “near misses” around quality, safety, or data handling. When several experts independently raise the same issue, late payments, confusing contracts, a fragile key-person dependency that theme usually becomes a negotiation point or a covenant.

How expert networks turn this into a repeatable process

Expert networks exist to make these off-channel conversations fast, repeatable, and compliant. They recruit and vet thousands of professionals, then match them to a specific investor brief, often within 24–48 hours. For a typical diligence sprint, a fund might run 10–30 calls across different stakeholder groups, each one narrowed to a single tight set of questions.

Calls are short and intense: most run 45–60 minutes by phone or video, enough for one topic or one company. Pricing is hourly and scales with seniority and sector. For institutional buyers, the major networks GLG, AlphaSights, Guidepoint, Third Bridge, typically price calls in the $500–$2,000 per hour range, with GLG’s client rates often cited around $1,500–$2,000 an hour and one industry comparison putting the median at roughly $1,150 including premium experts. Beyond live calls, transcript subscriptions (for example, Tegus) commonly run $15,000–$50,000 a year. Networks differ on model: some sell prepaid credit bundles, while others, including Nexus, work on a transaction-based, pay-as-you-go basis.

On market size, estimates vary by methodology, but industry sources cluster in a consistent band. Inex One, an expert-network marketplace, put the global market at roughly $3 billion in 2025, growing about 12% a year since 2023; research firms such as QY Research and Business Research Insights estimate $4–4.9 billion for 2025–2026, with projected CAGRs from the high single digits into the mid-teens through the early 2030s. Concentration is high, QY Research reports the top five networks (GLG, AlphaSights, Guidepoint, Third Bridge, Capvision) held about 55% of global revenue in 2025 and demand is heavily driven by dealmakers: Business Research Insights estimates roughly 70% of private-equity and consulting users rely on expert calls for due diligence and market intelligence.

Before publishing: link each figure to its original source page and keep the “as of” year visible. Discover’s 2026 quality system rewards sourced, dated data and quietly suppresses vague, uncited ranges. Market-size numbers vary between research houses, so the honest framing above (“estimates vary… cluster around”) is a feature, not a weakness.

The compliance line: what experts can and can’t share

The “secret” here is discretion, not anything shady. Reputable networks are built around hard compliance lines that protect both clients and experts.

Off-limits: material non-public information, unreleased financials, unannounced deals or products, anything NDA-restricted. Serious networks screen experts for MNPI risk, enforce cooling-off periods (often six months or more for former employees of public companies), and require per-call attestations.

Fair game: industry judgment, experience from prior roles after an appropriate gap, and analysis of already-public information. Think qualitative calls (“this sales model is hard to scale”), directional ranges (“peers tend to run EBITDA in the mid-teens”), and descriptions of common practice. The value is in pattern-spotting, not leaking a specific number that could move a market.

From the buyer side, compliance teams look for documented MNPI screening, conflict checks, long-term record retention, and written cooling-off and data-residency policies before signing. That paper trail is what lets a fund show, months later, internally or to a regulator that the research stayed on the right side of the line.

The off-channel voices behind a deal

Why these quiet calls decide billion-dollar bets

These conversations rarely make headlines, but they often decide whether a deal gets signed, repriced, or quietly walked away from. When several experts independently confirm that customers treat the product as mission-critical and churn is genuinely low, a buyer gains the confidence to underwrite aggressive growth and pay a higher multiple. When they don’t, the model corrects fast.

And because a panel can be assembled in days, this is now the fastest way to bring lived experience into an investment decision, compressing what used to take weeks of travel into a handful of focused, documented calls. In a market where one mispriced deal can drag a whole fund’s returns, that quiet research has become one of the most leveraged tools in modern investing.

If you’re building a view on your next acquisition and want the off-channel voices your model is missing, talk to the Nexus Expert Research team about designing a compliant, high-signal expert-call program around your thesis.