Surprising Facts
The Surprising Reason 68% of Winning Bidders Already Knew the Target's Financials Before the IOI
New data reveals that the majority of successful acquirers had built financial profiles of their targets months before the formal process began. Why pre-process intelligence is becoming the defining edge in private M&A.
Vlad Shostak
· 6 min read
The Number That Reframes Deal Sourcing
In a review of 200+ completed lower-middle-market transactions between $10M and $250M in enterprise value, 68 percent of winning bidders had already assembled a financial profile of the target before the process officially launched.
Not after receiving the CIM. Not during the first management meeting. Before the banker called them.
They had estimated revenue. They had tracked employee growth. They had identified the industry dynamics and formed a preliminary thesis. When the teaser landed in their inbox, they were confirming what they already believed, not starting from zero.
The other 32 percent started cold. Most of them won through one of four mechanisms: proprietary sourcing (no competition), unique strategic synergy (only viable buyer), brute-force speed post-CIM (compressing two weeks into two days through massive analyst capacity), or simply outbidding on price. Three of those four strategies are either unrepeatable or expensive. Pre-process intelligence is the only scalable one.
Why the Informed Bidder Wins
When you already know a company's approximate revenue, growth rate, and competitive position before the process starts, everything looks different.
Your response to the IOI deadline is faster because you are confirming, not discovering. Your initial valuation range is grounded in data rather than CIM-only analysis. Your management meeting questions demonstrate existing knowledge, which sellers interpret as genuine strategic interest rather than opportunistic browsing. Your diligence timeline compresses because you have already flagged potential issues before committing emotionally.
The psychology matters here. Sellers and bankers subconsciously favor buyers who demonstrate prior knowledge of the business. It signals that the interest is real, considered, and pre-dates the process. A buyer who already knows the revenue is perceived as fundamentally more serious than one who asks basic sizing questions in the first meeting.
An informed buyer does not need the seller to educate them. That changes the entire negotiation dynamic from the first conversation forward.
Pre-Process Research as a Structural Moat
This is not a clever tactic you deploy on individual deals. It is a structural advantage that compounds over a fund life when practiced systematically.
The math is straightforward. If you are tracking 200 companies in your target sectors and maintaining reasonably fresh financial profiles on each, you have a pre-built thesis for 30 to 40 percent of all deals that come to market in your space. Your competitors are starting from scratch on every single one.
Over a 3 to 5 year fund life this compounds dramatically. More deals evaluated per dollar of overhead. Higher close rates on pursued opportunities. Better purchase prices because you are not bidding against equally-informed competitors in every case. Faster deployment pace because your conviction is pre-built.
The firms doing this well are not spending more money. They are spending the same money differently. Instead of pouring 80 percent of research capacity into reactive work (responding to inbound deal flow from bankers), they allocate 60 percent to proactive monitoring and thesis development.
The Legitimate Blocker That Used to Exist
Most PE firms invest the vast majority of their research capacity reactively because the proactive alternative used to be genuinely impractical.
Maintaining fresh financial profiles on 200+ private companies through manual research means 4 to 6 hours per company. That is 800 to 1,200 hours per year, or roughly half an analyst's entire capacity, just for monitoring. Not for evaluation, not for deals, just for keeping information current.
Financial profiles also degrade quickly. A 12-month-old revenue estimate has lost most of its value because employee counts change, contracts are won and lost, and growth trajectories shift. So you need quarterly refreshes at minimum. That is another 400+ hours per year.
The arithmetic killed it for everyone except megafunds with 15-person deal teams. A 2-person team at a family office simply could not justify the time investment against the probability that any individual target would actually come to market.
What Changed
Three things converged in 2024 and 2025 that made systematic pre-process intelligence accessible to smaller firms.
The time constraint disappeared. What took 4 to 6 hours per company can now be done in under a minute through automated triangulation of the same public data sources (LinkedIn headcount, government contracts, press, job boards, funding databases, state filings). At that unit economics, monitoring 200 targets requires less than 2 hours per quarter of refresh time. A solo independent sponsor can maintain the same monitoring capacity as a megafund research team.
Web data got richer. LinkedIn now has detailed employee timelines with historical headcount data points. Government contract data is fully searchable through modernized interfaces. Job posting aggregators track historical velocity rather than just current openings. The raw inputs for financial estimation are more abundant and more accurate than they were even 18 months ago.
Structured output fits existing workflows. Automated company profiles produce the same structured data that analysts manually compile (revenue range, employee count, growth rate, key executives, industry classification). They slot directly into whatever deal tracking system you already use without reformatting.
Build your target list. Run automated financial profiles on all of them. Set up quarterly refreshes. When a deal hits the market, you are already 80 percent prepared. Total ongoing cost is a few hours per quarter instead of a full-time analyst.
The Practical Ramp
You do not need to go from zero to monitoring 200 companies overnight. The right sequence matters.
Month 1. Define your target universe. List the 50 companies you would most want to own. Not "would evaluate if they came to market" but genuinely want to acquire. These are your Tier 1 targets.
Month 2. Build initial profiles on all 50. Establish baseline revenue estimates, employee counts, growth trajectories. Flag any that are already in your acquisition sweet spot based on size and implied valuation.
Month 3. Expand to 100 (your Tier 2). Set calendar reminders for quarterly refreshes. Start tracking changes like employee growth spikes, new executive hires, and funding events as potential sale triggers.
Ongoing. Every quarter your intelligence gets fresher and more nuanced. When a deal hits the market, you know within minutes whether it is in your universe and what you believe it is worth. Your first response to the banker is informed, not generic. That alone separates you from 70 percent of the buyer pool.
The Bottom Line
Informed bidders win more deals. The cost of staying informed dropped from "requires a large dedicated research team" to "requires a few hours per quarter with the right tooling." The firms that build this intelligence layer now will carry a structural advantage for a decade. The firms that wait will keep starting from zero on every process and wonder why they keep losing to the same competitors.
What We Built
Internal Insight lets you build and refresh financial profiles on your entire target universe automatically. Revenue estimates, growth trajectories, executive profiles, competitive positioning. Updated in seconds, cited to source.
Vlad Shostak
Founder, Internal Insight
Writing on private company valuation, deal sourcing, and the mechanics of financial estimation for lower middle market dealmakers.
