Latest / The Buyer & Seller Podcast with Fexingo: Business Brokers, Exits, and Private Sales Explained / How a Pet Grooming Business Sold at 90x EBITDA with Subscription Data
Transcript
- Lucas: Luna, I spent yesterday afternoon looking at a deal that initially made me double-check the decimal point. A pet grooming business — six locations, all in the Dallas-Fort Worth area — sold for about 90 times EBITDA. Luna: Ninety times? That's not a typo? Lucas: I triple-checked the filing. The business generated about $400,000 in annual EBITDA, and the total consideration came to roughly $36 million. The buyer wasn't another grooming chain. It was a private equity firm that typically buys software companies. Luna: So the question everyone listening probably has is: why would a software-focused PE firm pay that kind of multiple for dog washing? Lucas: Exactly. And the answer isn't about grooming at all. It's about the data and the revenue model. This business had switched to a subscription prepay model about 18 months before the sale. Luna: Like a monthly membership for grooming? Lucas: Right. Customers paid a flat fee — say $89 a month — for one bath and brush session. Additional services like nail trims or teeth cleaning were add-ons. But the key is that roughly 70 percent of revenue came from those prepaid memberships. So the buyer saw a recurring revenue stream with high retention. Luna: And that brings the multiple way up. We've talked on this show about how subscription businesses often trade at 5x to 10x recurring revenue, even if the underlying EBITDA is modest. But 90 times EBITDA still seems high. Lucas: You're right. The recurring revenue alone doesn't explain the full multiple. The second piece was the data. This company had built a customer database with detailed profiles — pet breed, age, health conditions, product preferences, visit frequency. They knew, for example, that golden retrievers in North Dallas spend an average of $1,200 a year on grooming and premium pet food. Luna: So the buyer saw an opportunity to cross-sell — maybe pet insurance, specialty food, even veterinary services. Lucas: Correct. The PE firm already owned a pet insurance platform and a direct to consumer pet food brand. They figured they could double the lifetime value of each customer by funneling them into those other products. The grooming locations become physical retail touchpoints for a broader ecosystem. Luna: That's a thesis that makes the 90x multiple more plausible. They weren't buying a grooming business. They were buying a data asset with a physical distribution network. Lucas: And if today's conversation is nudging you to think differently about your own business — whether it's grooming or something else — the way these episodes stay ad-free is through listener support. If you found this useful, you can toss a few dollars into the tip jar at buy me a coffee dot com slash fexingo. It genuinely helps us keep digging into deals like this. Luna: Yeah, and it means we don't have to run ads. So if you've gotten value from any of these episodes, that's the place to show it. Lucas: Alright, back to the grooming deal. Let's talk about how the owners actually built that subscription model. It wasn't always there. Luna: The original business was a standard pay per visit operation, I assume? Lucas: Exactly. They started in 2019 with one location and grew to six locations by 2023, all cash and carry. But the owner told the broker that revenue was lumpy — strong around holidays and summer, weak in January and February. The subscription model smoothed that out. Luna: How did they get customers to switch from pay per visit to a monthly fee? Lucas: They offered a simple trade-off: sign a 12-month membership, get 15 percent off the regular price and a free add-on every third visit. About 40 percent of existing customers converted in the first six months. New customers were offered the membership at checkout, and about 60 percent opted in. Luna: So they essentially created a predictable revenue stream from a previously transactional business. That's a playbook lots of service businesses could copy. Lucas: That's exactly what the PE firm recognized. They paid up because the subscription data gave them visibility into future cash flows. But there's a third piece that sealed the deal: the customer acquisition cost was almost zero. Luna: Because word of mouth? Lucas: Partly, but also because every dog that came in generated data. The business had a referral program where existing members got a $25 credit for referring a friend. They tracked the referral source, the conversion rate, the lifetime value of referred customers. That data set alone — a map of how customers found them — was worth a lot to a buyer who wanted to scale. Luna: So the buyer didn't have to spend heavily on marketing to grow. They could just replicate the referral engine. Lucas: Right. And that's why the multiple hit 90. The buyer saw a business with recurring revenue, rich customer data, and a zero-cost customer acquisition loop. Those three characteristics together are rare in brick and mortar services. Luna: I want to ask about the mechanics of the sale. How did the broker position this to attract that kind of buyer? Lucas: The broker told me they didn't market it as a grooming business. They marketed it as 'a recurring revenue platform with a physical fulfillment network in a high-growth pet vertical.' They specifically targeted private equity firms that had already invested in pet care or subscription services. Luna: So they reframed the business entirely. Instead of selling a grooming chain, they sold a data and subscription asset. Lucas: Exactly. The broker ran a limited auction — about 15 buyers were invited to review the confidential memorandum. Five submitted indications of interest. Three did full due diligence. The winning bid came in at 90 times EBITDA, all cash, with a two-year earn-out for the owner. Luna: What was the earn-out based on? Lucas: The owner had to help integrate the customer data into the buyer's insurance and food platforms. If they hit certain cross-sell targets — like enrolling 10 percent of grooming customers into the pet insurance product — the earn-out added another $4 million. Luna: So the owner essentially got paid twice for the data: once in the purchase price, and again for making the data work post-sale. That's a smart structure. Lucas: It also aligned incentives. The buyer wanted the data to be usable, and the owner knew where the bodies were buried — or in this case, where the customer insights lived. Luna: What lessons does this hold for a small business owner listening who doesn't run a pet grooming chain? Say they own a dry cleaner, or a lawn care service, or a tutoring center. Lucas: The core lesson is that data and recurring revenue can transform your multiple. If you can convert even 30 percent of your customers to a subscription or prepay model, you start to look like a SaaS business to acquirers. And SaaS multiples are typically 3x to 5x higher than service business multiples. Luna: So the goal isn't to become a tech company. It's to behave like one in terms of revenue predictability and customer insight. Lucas: Exactly. The grooming business didn't build an app or develop software. They just changed their pricing model and started collecting data. That was enough to attract a premium buyer. Luna: I'm also struck by the role of the broker. They actively shaped the narrative to attract a specific type of buyer. That's a skill in itself. Lucas: Absolutely. The broker in this deal had a background in tech M&A and recognized the data angle. That's unusual in the main street brokerage world. Most brokers would have marketed this as 'a profitable grooming chain, great cash flow.' They would have gotten a 4x to 6x multiple from a strategic buyer in the same industry. Luna: So the difference between a 5x exit and a 90x exit wasn't the underlying business. It was how the story was told. Lucas: That's the real takeaway. The owner built a good business. The broker built a great story. And the buyer paid for the story, because they saw a way to multiply the value themselves. Luna: I've heard similar things from business brokers about other sectors — that the narrative around the business can dramatically affect the multiple. This feels like a case study in that. Lucas: It really is. And I think the next wave of small business exits will see more of this — buyers from outside the industry paying premiums for data and recurring revenue, not just for physical assets or customer lists.