Latest / The Buyer & Seller Podcast with Fexingo: Business Brokers, Exits, and Private Sales Explained / How a Mobile Mechanic Business Sold at 180x EBITDA
Transcript
- Lucas: Luna, I want to talk about a deal that, on paper, looks like a typo. A single-truck mobile mechanic business in Austin, Texas, sold for 180 times EBITDA. Luna: 180 times? That's not a typo, that's a fantasy multiple for a service business. What was the EBITDA — like fifty thousand dollars? Lucas: It was about $42,000 in EBITDA. So the purchase price was around $7.6 million. And yeah, if you just look at the multiple, you'd think the buyer was irrational. But the story behind the revenue is what matters. Luna: Okay, I'm listening. What made this mechanic so special? Lucas: The seller was a former dealership technician who started doing mobile repairs on the side. He built a proprietary CRM — a simple app — that tracked every vehicle he serviced. Not just the job, but the car's entire history: what parts were replaced, when the next oil change was due, even the customer's preferred communication method. Luna: So he owned the data, not the customer. That's powerful. Lucas: Exactly. And the app had a referral mechanism built in. If a customer referred a friend, both got a discount. Over three years, he built a network of about 1,400 active customers — people who booked routine maintenance through the app, not just emergency breakdowns. The recurring revenue portion was about 70% of total sales. Luna: That's the part that justifies the multiple. A buyer isn't buying a mechanic — they're buying a subscription-like customer base. But how do you prevent the mechanic from leaving and taking the customers? In a one-person operation, that's a huge risk. Lucas: That's where the deal structure matters. The seller agreed to a three-year earnout — but it wasn't tied to revenue. It was tied to customer retention. Specifically, 90% of the active customer base had to still be using the app at the end of each year. The seller stayed on as a consultant, but he wasn't the primary mechanic anymore. The buyer already had a bench of technicians in Austin. Luna: So the earnout was based on the system, not the person. That's smart. The seller had to ensure the CRM and the referral loop worked without him. Lucas: Right. And the data showed that customers who booked through the app had a 70% retention rate year over year. The average customer spent about $600 annually. So the buyer calculated a customer lifetime value of roughly $2,000 — assuming a five-year relationship. Multiply that by 1,400 customers, and you get $2.8 million in future revenue. The $7.6 million price starts to look reasonable if you believe the retention holds. Luna: That math works only if churn stays low. But what about the competitive moat? Couldn't another mobile mechanic just build a similar app? Lucas: The seller had a two-year head start and over 1,000 reviews on the app store. Plus, the CRM was proprietary — he owned the source code. The buyer got the intellectual property as part of the deal. So a competitor would have to build the software, get the reviews, and replicate the referral network. That takes time and money. The buyer essentially bought a monopoly on a niche. Luna: It's like buying a software company that happens to have a truck. The mechanic part is almost incidental. Lucas: That's exactly how the broker pitched it. And the buyer — a small private equity firm focused on home services — saw it as a platform play. They already owned a chain of brick and mortar repair shops. This gave them a mobile arm with a built-in customer base. Luna: I'm struck by how the seller set this up. Most mechanics I've met are great with cars, not with software. How did he build the app? Lucas: He hired a freelance developer on Upwork for $15,000. Then he spent about a year testing it with his first 50 customers. He'd literally sit with them after a repair and watch them use the app. If they stumbled, he took notes and sent feedback to the developer. It was iterative, not fancy. Luna: So the technology wasn't the moat — it was the iteration and the customer feedback loop. That's replicable, but only if you have the patience to do it. Lucas: Exactly. The seller told the broker he spent about 10 hours a week just talking to customers about the app. That's not scalable, but it built trust. Customers felt like they were part of building the service. That emotional stickiness is hard to buy. Luna: I wonder if this model could work in other trades. Plumbers, electricians, even lawn care. If you own the customer relationship and the scheduling data, you build a business that's worth more than just the labor. Lucas: It's already happening. I've seen similar deals in pest control and HVAC — but the multiples are lower because those industries are more competitive. The mobile mechanic niche was wide open. The seller got in early. Luna: And the timing helped. Austin's population grew like crazy the past five years. More cars, more need for mobile service. He was in the right place. Lucas: The broker said the buyer's due diligence focused almost entirely on churn data and app engagement metrics. They barely looked at the truck or the tools. That tells you everything about where value is in a service business today. Luna: So for a seller listening, the takeaway is: invest in the system, not just the service. Build the data moat before you try to sell. Lucas: Absolutely. And if today's conversation moved your work forward in some small way, you can support the show at buy me a coffee dot com slash fexingo. It's a simple way to keep this podcast ad-free and focused on deals like this. Luna: Yeah, listener support makes a real difference. We don't run ads, so every contribution helps us keep digging into these transactions. Lucas: That said, back to the mechanic deal. One more detail I found interesting: the seller had a non-compete for two years, but it only covered mobile mechanics. He could still work as a dealership technician. So he essentially got paid $7.6 million to go back to his old job if he wanted. Luna: That's a golden parachute for a mechanic. What's he doing now? Lucas: He actually stayed on as a consultant for the earnout period, but he told the broker he's planning to start a new business — something in the software space. He caught the entrepreneurial bug. Luna: So he went from mechanic to tech founder in five years. That's the American dream, but with a wrench. Lucas: And a CRM. That's the story. A single-truck mechanic sold for $7.6 million because he owned the data, not just the labor. The multiple looks crazy until you see the recurring revenue and the retention rates. Luna: It makes you wonder what other blue-collar businesses are sitting on hidden data assets. A plumber with 500 regular customers and a simple booking app — is that worth 100 times EBITDA? Lucas: If the retention data is there, and the churn is low, absolutely. The market is starting to price in that stickiness. We're going to see more of these deals. Luna: I'd love to see a follow-up in a year — did the retention hold? Did the earnout pay out? That would tell us if the multiple was smart or speculative. Lucas: I'll make a note. If the buyer lets us, we'll check back. For now, I think the big lesson is: if you're a service business owner, start building your data moat today. It could be worth millions. Luna: And if you want to hear more deals like this, you know where to find us. We'll be back next episode with another one.