Latest / The Buyer & Seller Podcast with Fexingo: Business Brokers, Exits, and Private Sales Explained / How a Print Shop Sold at 110x EBITDA with Recurring Data
Transcript
- Lucas: So there's a commercial print shop in Tulsa — two employees, no contracts, no subscriptions — that just sold for 110 times its trailing twelve-month EBITDA. And the buyer didn't even flinch. Luna: 110x? With no recurring revenue? That sounds like a typo. Lucas: That's what I thought when the broker shared the deal memo. But the seller had something better than a contract: a ten-year spreadsheet of every single repeat order, with dates, dollar amounts, and client names. And that spreadsheet told a story. Luna: What story? Lucas: That 90 percent of the shop's revenue last year came from customers who had ordered at least once in each of the prior five years. Not under contract — they just kept coming back because the shop was fast, reliable, and located two blocks from the downtown business district. The seller called it a 'recurrence data set.' Luna: So instead of trying to sell a small print shop, he sold a data asset that proved future cash flow. Lucas: Exactly. And the buyer was a regional packaging company that had been trying to break into on-demand short-run printing for two years. They weren't buying equipment or headcount — they were buying a proven customer base. The multiple made sense to them because they could fold the shop's clients into their own digital platform and cut the shop's operating costs by about 40 percent. Luna: So the 110x isn't really about the print shop's standalone earnings. It's about the synergies the buyer can unlock. Lucas: Right. The shop's EBITDA was only about $80,000 a year. At 110 times, that's $8.8 million. But the packaging company estimated that migrating those clients to their platform would generate an additional $300,000 in annual profit within two years. So their real purchase multiple on projected combined earnings was closer to 23x — still high, but justifiable for a strategic acquisition. Luna: And the seller walked away with nearly $9 million for a business that probably didn't even have a proper balance sheet. Lucas: He had QuickBooks and a shoebox of receipts. But he also had that recurrence spreadsheet. He told the broker he spent a weekend combing through a decade of invoices, categorizing every client by order frequency, average ticket size, and seasonal pattern. That single spreadsheet was the reason the deal got done at that multiple. Luna: Let's talk about how he structured that data. Because I think a lot of our listeners have small service businesses with similar repeat patterns but no idea how to package it. Lucas: Sure. First, he broke clients into three tiers: Tier one were clients who ordered at least once a month for five consecutive years — that was about 40 accounts. Tier two were quarterly regulars — another 60. Tier three were occasional buyers, but he still included them because the data showed a 70 percent reorder rate within twelve months. Luna: So he didn't just cherry-pick the best customers. He showed the full pattern. Lucas: Exactly. And then he calculated a 'recurrence ratio' for each tier: the percentage of revenue that repeated year over year. Tier one had a 98 percent recurrence ratio. Tier two was 85 percent. Tier three was 60 percent. Weighted average across the whole book was 90 percent. That's the number that caught the buyer's attention. Luna: Because 90 percent recurrence without a contract is essentially the same as a subscription in terms of cash flow predictability. Maybe even better, since there's no churn risk from non-renewal. Lucas: Right. And the buyer's CFO told the broker that they had never seen a small commercial printer with that kind of organic stickiness. Most print shops have customer concentration — one or two big clients that account for half the revenue. This shop's largest client was only 8 percent of revenue. The base was diversified and deep. Luna: So what's the lesson for a business owner listening right now who runs, say, a landscaping company or a cleaning service? How do they build their own recurrence spreadsheet? Lucas: Start with your last three years of invoices. Export them into a single CSV. For each client, count the number of months they transacted. Then calculate the average interval between orders. If you see a cluster of clients with intervals under 60 days, that's your recurrence core. Then compute the percentage of total revenue those clients represent. Luna: And if that percentage is high, you've got your story. Lucas: Exactly. And the next step is to clean up your operations to make that recurrence even stickier. The print shop owner had a simple loyalty program — every tenth order got a 10 percent discount — but he never advertised it. He just applied it automatically. Clients didn't even know they were in a program. They just thought he was nice. Luna: That's brilliant. Because it builds goodwill without creating a contractual obligation that might scare off buyers who don't want to inherit liabilities. Lucas: Exactly. And the beauty of this deal is that it shows how data can bridge the gap between a 'lifestyle business' valuation and a 'platform acquisition' valuation. Most small print shops sell for 3 to 5 times EBITDA. This one sold for 110 times because the seller demonstrated that the business was, in effect, a customer acquisition engine. Luna: So the buyer wasn't buying a print shop. They were buying a recurring revenue stream with a built-in distribution channel. Lucas: And they paid a premium for the proof. The seller's broker told me that two other strategic buyers had expressed interest but couldn't get comfortable without contracts. The packaging company had the most aggressive synergy model — they planned to move all print orders to their own digital ordering portal within six months — so they were willing to pay up. Luna: One thing I'm curious about: did the seller have any non-compete or transition agreement? Lucas: Yes. The seller, who is 63, agreed to a two-year part-time consulting role at $50,000 a year. His main job is to introduce the buyer's sales team to his top 20 clients and explain the ordering patterns. After that, he's free to retire. The non-compete is three years, limited to a 10-mile radius from the shop's current location. Luna: That's a clean exit. And he got a multiple that most software companies would envy. Lucas: It really shows that in today's M&A market, data is often more valuable than physical assets. The shop's two printing presses were probably worth $50,000 used. The lease was $3,000 a month. But the recurrence data was worth millions. Luna: And I think that's the key takeaway for any business owner: you might be sitting on a data asset that you haven't even cataloged. If you can quantify your customer stickiness, you can command a multiple that reflects the true value of your recurring cash flow. Lucas: One last thing — the broker told me the seller spent about 20 hours building that spreadsheet. That's a 20-hour investment that generated an extra $5 million in sale price compared to what a standard broker would have marketed the business for. That's a $250,000 per hour return. Luna: Worth the weekend. So if our listeners take one thing away from this, it's to start mining your own transaction history. You never know what story the data will tell. Lucas: And on that note — a quick honest thing. This show is ad-free, and that's intentional. A small group of listeners chips in every month through buy me a coffee dot com slash fexingo, and that support literally makes it possible for us to keep digging into deals like this one. Luna: Yeah, we don't run commercials or sponsored segments. So if you've gotten something out of these episodes over the years, consider joining that group. It's a simple way to keep this resource alive. Lucas: No pressure at all. But for anyone who wants to help, that's buy me a coffee dot com slash fexingo. And now back to the print shop — I actually want to mention one more detail about how the buyer structured the earn-out. Luna: Oh, there was an earn-out on top of the 110x? Lucas: Yes, a small one. The buyer offered an additional $500,000 if the shop's client retention rate stayed above 85 percent for the first twelve months post-close. The seller was so confident in the recurrence data that he agreed to it without hesitation. Luna: And that confidence probably came directly from that spreadsheet. He knew the numbers cold. Lucas: Exactly. So the lesson is clear: data is the new collateral in small business M&A. If you can prove recurrence, you can price like a subscription company.