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- Buy & Build Europe #52
Buy & Build Europe #52
Your Weekly <5 Minute Update of ETA, Search Funds, HoldCos
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Today’s Rundown
Seller financing in search funds
AI-rollup 2026 predictions
Operating leverage in search funds
11 mistakes to avoid when buying businesses
2 deal / launch announcements
Database Overview
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Weekly Highlights
Chris von Wedemeyer, founder of search fund investor Legacy Partners, shared his thoughts on why seller financing isnʼt a loan and why it can kill your deal:
Seller financing in ETA transactions functions economically as deferred purchase price rather than a true cash loan, even when it is documented as a debt instrument
In practice, seller notes commonly represent roughly 10–30 percent of enterprise value and increase in higher-risk deals with customer concentration, owner dependence, weaker reporting, or thin management layers
When sellers attempt to structure notes with senior-like protections such as security, aggressive amortization, or limited subordination, it often creates friction with banks, delays underwriting, and materially increases closing risk
Properly structured seller notes absorb intangible risk by aligning price with post-close reality, allowing part of the consideration to flex or be forgiven if goodwill assumptions such as customer retention prove wrong
In European ETA especially, seller financing works best when treated as junior, subordinated, and alignment-driven deferred consideration, whereas treating it like a standalone commercial loan frequently undermines bankability and deal execution
Sahil Patwa, an experienced investor and entrepreneur, shared his bingo card for AI-powered rollups in 2026:
Sahil expects the AI roll-up ecosystem to expand from roughly 150 companies today to more than 400 in 2026, with total capital invested surpassing $3 billion while still representing only about 1 percent of global venture funding
Capital sources are likely to broaden meaningfully in 2026, with private equity providing follow-on capital in multiple deals, at least one venture debt product tailored specifically to AI roll-ups, and the launch of a dedicated $100 million-plus specialist fund
AI roll-ups are expected to move beyond pure software into the physical world, with several platforms using drones, robotics, and computer vision to drive operational efficiency in real-world industries
The model should globalize further, with at least one AI roll-up on every inhabited continent raising more than $50 million, and Europe emerging as a particularly attractive region due to fragmentation and regulatory complexity
The category is likely to mature culturally and analytically, with standardized AI roll-up metrics focused on sustainable margin improvement, broader mainstream visibility through viral content, and formal recognition via a major book or top-tier business school case study
Richard Augustyn, founder of search fund investor Endurance Search Partners, published a piece on ETA: The 1% searching for the 2%:
The core claim is that only a small subset of businesses, roughly the top 2 percent, possess the structural characteristics that allow first-time CEOs to learn, make mistakes, and still compound capital under new ownership
Operating leverage is framed as a practical buffer rather than an accounting concept, where incremental revenue expands free cash flow and balance sheet breathing room instead of increasing capital intensity and execution risk
High-operating-leverage businesses show stable or expanding gross margins, SG&A growing well below revenue such as less than $0.20 per dollar of new revenue, and partially fixed labor costs that absorb growth with minimal incremental expense
Low-operating-leverage businesses compress margins as they grow, require proportional hiring or capex per customer, and force CEOs to absorb inefficiencies directly, shrinking the learning window and increasing covenant and liquidity risk
Disciplined screening for operating leverage allows the top 1 percent of operators to focus their effort on systems that persist and compound, turning operational improvement into predictable free cash flow and earlier equity value realization rather than repeated execution resets
On his podcast Acquisitions Anonymous, Michael Girdley, an experience entrepreneur, shared 11 mistakes to avoid when buying businesses:
Drawing on 20-plus acquisitions and thousands of deals reviewed, he argues first-time buyers most often fail by buying themselves a job where the business depends entirely on the owner’s personal relationships, eliminating scalability, vacations, or a future exit
Many bad deals persist because buyers never ask why they are the “lucky” acquirer, especially when assets have sat on the market for months or years and better-informed insiders such as franchisees or competitors have already passed
He warns against extrapolating temporary performance distortions such as Covid-era revenue spikes or collapses, noting that valuing businesses at peak anomaly earnings leads buyers to overpay for results that are unlikely to persist
Structural risks frequently overlooked include expiring or fragile real estate leases, unfinanceable business models, heavy regulatory exposure, or industries that have already peaked, all of which can destroy earnings even if historical numbers look strong
Poor buyer–business fit also kills returns, whether through lack of customer ownership on platforms like Amazon, extreme operational difficulty, geographic mismatch, or high working-capital intensity that quietly absorbs cash and reduces true owner returns
Deal / Launch Announcements
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