Search Fund Deal Sourcing | 3,000 Companies per Acquisition — ExitRadar
Search fund operators contact 3,000+ companies to make one acquisition. 37% never close. We break down the full funnel with Stanford and IESE data.
Search fund operators contact 3,000+ companies to make one acquisition. 37% never close. We break down the full funnel with Stanford and IESE data.
The search fund model has generated 35% aggregate IRR and 4.5x returns over four decades. A record 153 new funds launched globally in 2023. The asset class is proven, growing, and increasingly institutional.
And yet the most basic operational problem in the model — finding a business to buy — remains almost comically inefficient.
Stanford GSB's 2024 study and the IESE 2024 International Search Fund Study both converge on the same figure: the average search fund operator contacts over 3,000 companies to close a single acquisition. The median search takes 20 months. And 37% of funded searchers never acquire anything at all — returning whatever remains of their investors' capital after two years of salary, travel, and broken deals.
The discovery infrastructure that supports a $10 billion cumulative asset class is, in most cases, a spreadsheet, a LinkedIn subscription, and persistence.
We built ExitRadar to solve the UK version of this problem. But before explaining what we do, it's worth understanding exactly why the search process is so broken — because the data is more damning than most searchers realise.
Stanford's Best Practices research documented a representative first-year outreach campaign by a single searcher: 3,404 initial contacts produced 256 responses, 124 positive follow-ups, 25 in-person meetings, 16 pricing conversations, and 4 LOIs submitted. One deal closed.
The IESE 2024 International Study — covering 320 funds across 40 countries — corroborates this almost exactly. The average international searcher explored over 3,000 businesses, held 159 personal conversations with owners, signed approximately 4 LOIs, and closed 1 deal.
The conversion rates at each stage are consistent across both studies:
Companies contacted: 3,000+. Responses received: 200–256, roughly 7–8%. Positive follow-ups from interested sellers: around 124, or 3.6%. In-person meetings: 25–50, under 1.5%. Pricing conversations: approximately 16, or 0.5%. LOIs submitted: 4–10, between 0.1% and 0.3%. Deals closed: 1, approximately 0.03%.
The average searcher signs 3.6 LOIs before closing, with the first LOI typically arriving at month 7.8 of the search. The median search duration is 20 months — up from a COVID-era low of 17 months in 2020–2021. Nearly a third of searchers take 20–30 months. One in five exceeds 30 months.
LOIs fail for identifiable reasons: 63% due to issues discovered during diligence, 48% over valuation disagreements, 38% from seller retraction, and 32% from competitive bidding. A critical leading indicator: 40% of searchers who haven't signed an LOI by month 12 never acquire a business.
A typical funded search raises $400k–$670k for a two-year search phase, with the median at $500k for US funds and approximately €450k–€650k for European funds. This capital comes from 10–20 investors contributing roughly $25k–$35k per unit.
The budget breaks down roughly as follows: salary absorbs around 50%, or $120k–$150k per year. Travel and conferences consume about 10%. Legal fees take another 5%. CRM, software, interns, and research account for approximately 13% — $40k–$80k over the full search. And diligence costs — primarily quality-of-earnings reports at $20k–$30k each — consume about 17%, or $100k total.
The pure software and tools budget typically falls between $5k and $30k per year. A lean stack — free CRM, basic aggregators, email tools — costs $2k–$5k annually. Adding Grata ($12k–$18k/year) and email automation pushes the total to $15k–$25k. A full institutional stack incorporating PitchBook or Capital IQ ($12k–$40k/year each) and outsourced origination services like Captarget ($2k–$5k/month) reaches $30k–$50k annually.
Each month of search saved is worth approximately $15k–$20k in salary and overhead alone, before counting the option value of acquiring a better company or avoiding a broken deal. Every failed QoE report burns $20k–$30k. The economics of better targeting are unambiguous — even modest improvements in screening quality generate significant savings against these cost structures.
The headline number deserves its own section because it defines the structural risk of the model.
Of 524 concluded US and Canada search funds in Stanford's dataset, 196 — 37% — failed to acquire any company. The searcher spent two years, burned through $400k–$500k of investor capital, and walked away with nothing. Since 2014, the acquisition rate has actually declined to approximately 57%, meaning 43% of recent searchers fail to close.
Among those who do acquire, roughly 31% produce losses — 20.5% partial, 10.5% total. Run the compounding probability and the chance of a positive-return outcome for any new search fund is approximately 43%.
International search funds show a notably higher acquisition rate of 79%, though the international ecosystem is younger, more self-selecting, and return data is preliminary.
The reasons for failure cluster around sourcing and discovery. Searchers who fail tend to exhibit identifiable patterns: overly narrow criteria, excessive reliance on brokered deal flow, insufficient outreach volume, delayed first LOIs, and failure to develop proprietary sourcing capabilities. The structural irony is clear — the model's rapid growth simultaneously validates its economics and undermines individual success rates by crowding the buyer side.
The post-acquisition failure rate connects to sourcing quality too. The top reasons for losses include operational complexity the searcher didn't fully understand (63%), board disagreements (59%), poor gross margins (46%), and customer concentration (41%). These are problems that better pre-acquisition intelligence and more selective deal sourcing could mitigate.
The IESE 2024 data is unambiguous: 64% of international search fund acquisitions come from proprietary sources, versus 37% from third-party intermediaries. Stanford's Best Practices recommends allocating 80% of search time to proprietary and industry-driven sourcing, with only 20% to brokered deals.
The reason is economics, not ideology.
Research from Axial finds that lower-middle-market companies sourced proprietarily trade at median acquisition multiples approximately 15% lower than comparable brokered deals. Stanford data shows top-quartile search fund performers paid a median 4.5x EBITDA versus 4.8x for bottom three quartiles — while buying larger, faster-growing, and more profitable businesses. The mechanism is straightforward: in proprietary deals, the searcher is often the sole buyer. No competitive auction. No inflated pricing.
The adverse selection problem in brokered deals compounds this. Stanford investors have noted that brokered deals shown to search funds tend to be those already passed on by better-capitalised PE buyers with committed capital. Barriers to entry in business brokerage are low, quality varies enormously, and experienced searchers consistently report that most brokers add limited or negative value to the process.
Proprietary outreach also builds a direct, personal relationship with the seller before commercial negotiations begin. For search fund operators — whose core pitch is a dedicated young CEO committed to preserving the founder's legacy — this relationship quality is the single most important differentiator. In brokered processes, that personal connection is mediated and diluted.
The critical data point that ties all of this together: practitioner estimates suggest over 80% of businesses that ultimately sell are never formally listed with a broker. The vast majority of the market is invisible to anyone who isn't doing proprietary outreach.
The UK was the pioneer international search fund market — the first international fund was raised here in 1992. According to IESE's 2024 data, 35 UK search funds have been raised and 14 acquisitions completed. Spain leads Europe with 67 cumulative funds and 33 acquisitions, followed by the UK, France (21 funds, 12 acquisitions), Germany (20 funds, 10 acquisitions), and Italy (17 funds, 7 acquisitions).
In total, 14 European countries now have search fund activity, with Europe accounting for roughly 180 of the 320 international funds tracked by IESE — making it the world's largest international market.
UK-focused law firms and advisory firms have reported significant growth in ETA transaction activity since 2024. London Business School and INSEAD now offer dedicated search fund modules. The pipeline of new UK searchers is growing.
But the UK search ecosystem has a structural problem that the US doesn't: the broker market for sub-£5M businesses is thin and fragmented. Listing platforms like Daltons Business and BusinessesForSale.com serve primarily the micro-business market — sub-£250K asking prices, too small for most search funds. SME Market is the most search-fund-relevant UK platform, but its inventory is limited. Beauhurst covers high-growth companies but not succession-ready SMEs. Grata is powerful but US-centric. And Companies House — which holds the richest public dataset of UK company information anywhere — offers raw data but no screening, scoring, or intelligence layer.
The result: UK searchers face the same 3,000-company funnel as their US counterparts, but with fewer tools and thinner intermediary networks to help them through it.
This is where it gets interesting — and where the gap between the supply of succession-ready businesses and the capacity of searchers to find them becomes visible.
We maintain a database of 3.4 million active UK companies, built from public Companies House filings. When we score these companies for succession and exit signals — director age, tenure, filing behaviour, capital investment patterns, dividend changes, board structure — the scale of the hidden market becomes clear.
808,126 UK companies have directors aged 60 or above. Of those, 444,428 have a single director — no co-directors, no named successors, no internal succession infrastructure of any kind. 296,248 sole directors have 15 or more years of tenure, the classic founder-operator pattern where one individual has run the business alone for over a decade with no sign of transition planning.
At the sharp end: 45,964 companies score 70 or above for exit readiness on our model and hold net assets above £100,000. Their aggregate assets total £111.9 billion.
These companies aren't listed with brokers. They aren't on any marketplace. Most of their owners haven't consciously decided to sell. But they match every profile of a business where a conversation about succession would be welcome — and where a well-prepared acquirer with the right approach could find a receptive owner.
This is the market that sits underneath the 3,000-company funnel. The companies are there. The data to identify them is public. What's been missing is the infrastructure to score them, rank them, and deliver actionable intelligence on the ones worth approaching.
The search fund model works. The returns prove it. But the discovery phase is the bottleneck — an extraordinarily inefficient process that consumes 20 months on average, costs £250,000–£350,000, and fails entirely for more than a third of operators.
The fix isn't more cold emails or better CRM software. It's better targeting. If a searcher can start with companies already showing exit signals — instead of contacting 3,000 to find them — the entire search compresses. Fewer months burned. Fewer broken deals. More time spent on the 50 companies that actually matter, instead of the 2,950 that never would have sold.
The economics of better screening are stark. One month of search saved: £15,000+. One broken deal avoided: £20,000–£30,000. One proprietary deal closed at 15% lower multiples on a £2M acquisition: £300,000 in value. Against those numbers, the cost of better intelligence is a rounding error.
The businesses exist. The buyers exist. The data to connect them exists. The question is whether searchers will keep grinding through 3,000 companies manually — or start with the ones that are already signalling.
*This analysis draws on Stanford GSB's 2024 Search Fund Study, the IESE 2024 International Search Fund Study, Stanford's Search Fund Best Practices and Search Fund Primer, Axial deal sourcing research, and practitioner data from the ETA community. UK company data is from ExitRadar's database of 3.4 million active companies, derived from public Companies House filings.*
About ExitRadar: ExitRadar scores every active UK company on exit timing and business quality, surfacing off-market acquisition targets with full intelligence briefs — estimated financials, valuation range, approach strategy, and risk assessment. Start with three free reports or explore a sample report.