Latest / The Buyer & Seller Podcast with Fexingo: Business Brokers, Exits, and Private Sales Explained / How a Pool Service Business Sold at 85x EBITDA with Route Density Data
Transcript
- Lucas: So a guy named Mike Delgado in Phoenix ran a pool cleaning business for about twelve years. Nothing fancy — just him, two trucks, a part-time helper, and a few hundred residential accounts. Last year he sold it for 85 times EBITDA. And that multiple wasn't because the revenue was growing fast or because he had some proprietary chemical formula. It was his route map. Luna: Route map meaning how the stops were organized on any given day? Lucas: Exactly. Mike had been obsessive about clustering customers within a five-mile radius of his home base. He wouldn't take a client that was more than a fifteen-minute drive from the next. Over time, his service density became absurdly efficient. His trucks were servicing eight to ten pools per eight-hour shift with almost zero deadhead miles. Utilization rate was above 95 percent. Luna: That is high. I know a lot of field service businesses struggle to get above 70 percent utilization. The travel between jobs just eats into the billable window. Lucas: Right. And that's the data point that got private equity interested. Because if you're a PE firm rolling up pool services across the Southwest, you don't just want recurring revenue contracts — you want proof that the route density is repeatable. Mike sold them not just his customer list but twelve years of GPS logs, chemical delivery patterns, and customer pickup windows. It was basically a logistics playbook disguised as a pool business. Luna: So the buyer was paying for the data set as much as for the cash flow. That reminds me of how some of those last-mile delivery companies are valued on route optimization algorithms rather than delivery volume. Lucas: It's the same logic. A pool service route, a pest control route, a mobile mechanic route — they all share this underlying network effect. The more stops you pack into a tight geography, the lower your cost per stop and the higher your margin on each contract. Mike's EBITDA margin was running around 40 percent, which is good for a service business, but the margin on the last stop of the day was something like 60 percent because the drive was thirty seconds. Luna: That makes you wonder — was he deliberately turning down business that was too far away, even if it was profitable on paper? Lucas: He did. He told me he walked away from a 50-thousand-dollar annual contract once because the house was eight miles off the main cluster. He said the extra drive time would have cost him a second truck in the long run. That kind of discipline is rare. Most owners take any customer they can get. Luna: But it paid off in the exit. So what was the actual sale process like? Was it a competitive auction, or did the PE fund approach him? Lucas: It was a targeted process. He hired a broker who specialized in service businesses — the same broker we've mentioned before on the show. They built a data room that emphasized the operational metrics: average stop time, gallons per pool, seasonal variation in chemical usage. The broker identified five regional PE platforms that were actively rolling up pool services. Two of them bid. Luna: And the winner paid 85 times EBITDA. What was the actual dollar figure? Lucas: Mike's EBITDA was about 180 thousand dollars, so the enterprise value was roughly 15-point-3 million. That's a big number for a three-truck operation. But the buyer saw it as buying a template. They can overlay Mike's density model onto their existing portfolio companies and improve margins across the board. Luna: So the multiple is partially a reflection of the platform value — the acquirer's ability to deploy that data across other businesses. Lucas: Exactly. It's not that Mike's business was generating 15 million in cash flow. It's that owning his data saves the buyer from having to figure out the density optimization themselves. They can replicate it. And in a roll-up, even a small improvement in utilization across a pool of, say, fifty route-based businesses adds millions to the bottom line. Luna: What about the risk that the model breaks when you scale? I mean, Mike's density was built organically over a decade. Can you just drop that into another market? Lucas: That's the million-dollar question. The buyer is betting that the principles — tight geographic clustering, refusing fringe accounts, optimizing for stop density rather than revenue per stop — are transferable. They'll probably pilot it in one or two markets first. But Mike's data gives them the confidence to try. And if it works, the returns are enormous. Luna: I want to zoom out a bit. This episode fits into a broader pattern we've been tracking. A few episodes ago we talked about a pest control business that sold at 60 times EBITDA on the strength of recurring service contracts. That multiple was about the contracts. Here, the multiple is about the route density data. What's the common thread? Lucas: The common thread is that buyers are paying for defensibility. Recurring revenue is defensible because it's sticky. Route density data is defensible because it's hard to replicate quickly. The more you can prove that your business has something a competitor can't copy in six months, the higher the multiple. Luna: So if you're a small business owner listening and you run a route-based service — landscaping, pool cleaning, mobile repair, even a food truck — what's the actionable takeaway? Lucas: Start tracking your route density metrics now. Map every stop. Calculate the average distance between consecutive jobs. Aim for a utilization rate above 85 percent. And if you have to turn down business to keep your route tight, do it. The exit premium you'll get later will more than compensate for the revenue you leave on the table today. Luna: That's a counterintuitive piece of advice. Most owners think growth means saying yes to every sale. Mike's story suggests the opposite. Lucas: Exactly. And that's why we do this show. There's a lot of conventional wisdom about scaling a service business that actually hurts your exit value. Mike's case is a great example of how thinking like a future seller from day one can change the way you operate. Luna: If this conversation made you think about your own business's defensibility, I'd just say — these episodes are ad-free because of listeners who find them useful and choose to support the show. You can do that at buy me a coffee dot com slash fexingo. It's a low-key way to keep the conversations going. Lucas: Yeah, and honestly, the feedback we get from the community is what fuels the content. Every episode idea comes from a question someone sent in or a case we heard about from a listener. So if you've got a story like Mike's, we'd love to hear it. Reach out anytime. Luna: So to close — Mike's pool business didn't sell for 85 times EBITDA because of some fancy technology or a huge customer base. It sold because he had the discipline to build a tightly woven route and the foresight to document every mile. That data was worth millions. Lucas: In the end, the business was a logistics company that happened to clean pools. And that reframing is what unlocked the value. For anyone thinking about an exit, ask yourself: what's the hidden data asset in your operation? Luna: That's a great question to sit with. Thanks, Lucas. Lucas: Thanks, Luna. See you next time.