What a real acquisition search looks like from the inside

Deal Desk: Vending site visit didn’t happen, still coordinating schedules. Pivoted to Flippa and found two KDP accounts: a journal catalog at 3x SDE (no ad spend, upside available) and an adult ADHD catalog at 2x SDE (heavy ad dependency, 50% margin).

Main piece: What the acquisition search actually looks like from inside it. Phases, pattern recognition, the deals I’ve passed on, and the capex-adjustment reality that changes every evaluation.

Spotlight: Mid-term rental (MTR), per-room leasing model. $56-60K in, $1,100-2,000/month net, three structural advantages over both standard long-term rental and Airbnb.

The vending site visit didn’t happen last week.

I’ve been trying to coordinate a time that works for the broker, the seller, and me, and we haven’t landed one yet. This is a real part of the search that the acquisition guides skip: the logistics of getting three busy people into the same place are genuinely annoying, and that friction shows up on every deal regardless. Still working on it this week. Still working on it this week.

While I’ve been waiting on scheduling, I’ve been on Flippa looking at KDP accounts. KDP is Kindle Direct Publishing: sellers build catalogs of low- and no-content books (journals, planners, activity books, notebooks) that generate royalties through Amazon’s publishing platform. At the right scale, a well-run catalog is meaningfully passive: no inventory, no employees, no location dependency.

A journal and guest book catalog, listed at roughly 3x SDE. Runs on zero advertising spend, all organic through Amazon search and category placement. That’s unusual, and it matters: the current SDE is what the business generates without a paid traffic layer. Advertising is optionality, not dependency. A buyer who understands Amazon ads has a lever to pull that the current owner isn’t using.

An adult ADHD niche catalog, listed at 2x SDE. I’ll be honest about why this one caught my eye: I deal with adult ADHD myself. I know the audience. I understand the coping mechanisms, the tools that actually help, and the difference between content that’s genuinely useful versus content that’s just packaging keywords. That personal familiarity is a real asset when you’re evaluating a niche. You already know what the audience needs; you don’t have to reconstruct it from analytics.

The financial picture is more complicated. This account runs heavy KDP ad spend. Profit margin sits around 50%, which means roughly half of gross revenue is going back into ads to sustain that revenue. The real acquisition picture shifts: you’re not just buying the earnings, you’re buying the ad dependency that produces them. If ad performance degrades (account suspension, cost increases, algorithm shift), the revenue is exposed in a way the journal account isn’t.

There’s a second personal angle on both listings. I’m about to publish two books through KDP. Owning an established KDP account while doing that would give me a real inside view of how successful catalogs are structured, how Amazon’s ranking and discovery mechanisms actually work, and what operational overhead looks like at scale. That context compounds the cashflow case. I’m requesting more data on both. More in Issue 8.

The acquisition search gets described in podcasts and self-published guides as a linear funnel from criteria to close. The version unfolding in real time looks different.

The search runs in phases, and each one is slower than you’d expect.

The first phase is criteria development, and it’s more iterative than it sounds. You write down what you’re looking for. Then you look at listings for a few weeks and discover that what you wrote down was wrong in several ways. The buy box you have after 30 listings is a product of the search, not the starting condition for it. Writing it down early gives you something concrete to revise, but the week-1 version isn’t the version you actually use.

Then broker outreach. Brokers work buyers they know are serious. A cold inquiry with no capital statement and no specifics gets you put on a list and sent the listings nobody else wants. Arriving as a qualified buyer with criteria and a clear capital position changes the quality of deal flow you receive. The difference between “I’m open to opportunities” and “I have $80K deployable, I’m looking at service businesses generating $70-100K SDE, and here’s why I’m a qualified buyer” is not subtle.

Then listing review, NDA requests, and CIM analysis. Most listings get discarded in the first five minutes. The small percentage that earns a closer look gets an NDA. A smaller percentage of those returns a CIM that actually holds up under scrutiny.

Due diligence comes last, and only on the deals that hold up. Most searches never get there on the first few deals. That’s the process, not a failure.

The first 15 listings are mostly confusing. You read the listing summary, look at the disclosed financials, and you’re not sure what to make of any of it.

Somewhere between listing 20 and listing 30, something shifts. You recognize the structures. You know what the broker narrative is glossing over, because every broker narrative glosses over something. The customer concentration red flag appears in the first paragraph once you know what to look for. Seller dependency announces itself in the business description (“owner manages all client relationships,” “owner handles scheduling personally”). The franchise territory advertisement is distinguishable from a real acquisition listing in the first sentence.

By listing 50, you know in three minutes whether something warrants pulling the CIM.

Engineers develop this pattern recognition faster than most buyers because they’re already good at reading technical documentation for what it says and what it omits. The mechanism is identical. The domain is different.

The cleaning company with clean financials. Solid SDE, reasonable owner dependency, a customer retention rate that held up on closer look. I was moving toward deeper evaluation when it went pending. Someone else moved faster. The lesson: when something genuinely looks clean and the numbers hold up, move. Good deals don’t sit.

The towing company with high-mileage vehicles. Solid headline SDE. Then the disclosures: six vehicles with significant mileage, all due for replacement within a couple of years. The equipment replacement cost wasn’t in the SDE figure. It was a deferred capital expenditure the prior owner had been carrying forward. When I modeled a realistic capital reserve against the adjusted SDE, net earnings looked materially different from the listing.

This isn’t fraud. It’s how small business financials work. The seller reports what they earned. What they didn’t report is what they chose not to spend.

The franchise territory that wasn’t an acquisition. A significant portion of early broker outreach produces listings that aren’t acquisitions at all. New franchise territories start at zero. That’s the build path wearing acquisition clothes. An existing franchise already generating revenue with operating history you can evaluate. Once you know the difference, you spot it in the first paragraph. Until then, you reach out to a few, figure it out, and add it to the filter.

Every small business listing leads with SDE: seller’s discretionary earnings. The number represents what the business generated, adjusted for owner salary and one-time expenses, before debt service. It’s a useful starting point and a misleading endpoint.

What it doesn’t show: deferred maintenance, equipment approaching replacement, working capital gaps between payroll going out and client payments coming in, and any ongoing capital requirement the current owner has been funding from outside the business.

Run this on every deal before you form an opinion on the valuation. The towing company story above is what happens when you don’t.

Six months of searching produces a buy box that looks different from the one I started with.

I’m looking for service businesses with recurring revenue, minimal specialized equipment, a workforce that existed before the current owner’s involvement, and a revenue structure that doesn’t collapse if the seller stops showing up. The cleaning company category stays on the list for that reason: documented systems, recurring client contracts, a workforce that runs independently. The capex profile is manageable because the equipment isn’t a single high-cost replacement event.

Vending stays on the list in a different way. The economics work if the location relationships are strong and the machine quality is recent. Both of those variables need independent verification before the financial case holds, which is why the site visit matters.

The buy box isn’t a fixed document. It’s the current draft of the answer to a question that gets refined every time a deal clears the initial filter and gets examined up close.

Every issue I feature a real cashflow asset with real numbers. Asset type, capital in, annual cashflow, weekly time. Real numbers, real context.

The last four spotlights have covered physical and service business acquisitions. This one is different: mid-term rental (MTR), the asset class that most real estate write-ups describe accurately but incompletely, because they lead with the wrong comparison.

MTR is usually framed as longer-stay Airbnb. That framing undersells the model. The better frame is three structural advantages stacked on top of each other.

Advantage 1: Airbnb-level income without the STR regulatory exposure. Short-term rental markets have gotten complicated. City ordinances, HOA prohibitions, platform fee compression, and tourism-driven occupancy volatility have made pure Airbnb plays harder to underwrite in most markets than they were three years ago. MTR sidesteps most of this. Lease terms of 30 days or more fall outside short-term rental regulations in most jurisdictions. The transient occupancy taxes that apply to hotel-style stays generally don't apply. You’re generating revenue in the same range as STR. Furnished units on flexible leases command a 20 to 40% premium over standard long-term rents, without the regulatory and tax overhead attached to it.

Advantage 2: Multi-tenant income inside a single-family shell. This is the part most MTR coverage misses. Each bedroom gets its own separate month-to-month lease, its own tenant. A 4-bedroom single-family home becomes 4 independent revenue streams. If one tenant leaves, three bedrooms are still generating income. That’s a fundamentally different risk architecture than a standard long-term rental, where one vacancy means zero revenue until the unit is filled again.

The tenant profile makes this work. Traveling nurses, remote workers on project assignments, relocating professionals, contract workers, academics on temporary appointments. These people need a private furnished bedroom with shared common space for 1 to 6 months. They want a functional room in a well-run house, a real lease they can submit to their employer for reimbursement, and a kitchen that isn't a hotel kitchenette.

Advantage 3: The reconfiguration play. Operators who run this model seriously look at the floor plan differently. Common spaces that matter for a family (formal dining rooms, large living areas, bonus rooms) don’t deliver the same value to a tenant who's there for 90 days on a work assignment. Some operators convert those spaces into additional bedrooms, increasing the revenue unit count on the same footprint and the same mortgage. The math on a 3-bedroom that becomes a 5-bedroom is materially different, and MTR tenants generally don't need the family-oriented common space being given up.

What the operator does differently: Furnished Finder is the primary listing platform for the MTR tenant profile. Each room gets its own listing with real photos. Operators who run this well treat the common spaces — kitchen, bathrooms, laundry — as shared infrastructure that needs to be genuinely functional, not just adequate. The tenants paying $900/month for a furnished room in a shared house have options. The operators who keep occupancy above 85% are the ones whose common spaces are actually good.

What it doesn’t solve alone: Even at the high end of the cashflow range, a single MTR property covers a meaningful portion of most Freedom Numbers but doesn’t close them. It works best as a first piece in a stack: a reliable base layer while a business acquisition or Build Track asset compounds toward the remainder.

The capex reality: Furnishing across 4 rooms and shared spaces wears faster than a single-unit rental. Plan for a partial refurnishing cycle every 2 to 3 years. Leaving it out produces a cashflow figure that won’t survive contact with year 3.

Next issue: the vending site visit (scheduling gods willing), more on where the KDP evaluation lands, and the consulting trap. Why the most logical escape from W2 employment recreates the exact architecture problem it was supposed to solve.

More next week.

Charles