How Private Equity Is Buying Up Data Brokerages

Speaker A: Private equity has been on a buying spree across every corner of the services economy. We've done dozens of episodes on it. But there's one sector that flies under the radar, even though it touches almost every other industry. Data brokerages.

Speaker B: Data brokerages? The companies that collect, aggregate and, um, sell information about people and businesses. It feels like a natural fit for pe, but I hadn't thought about it as an acquisition target.

Speaker A: It's actually a perfect fit. These businesses generate recurring revenue from subscription contracts, have high gross margins once the infrastructure is built, and benefit from scale. And the biggest players are still fragmented. There are hundreds of regional data brokers.

Speaker B: If this episode helps you understand the hidden plumbing of the data economy, that's the link. Buymeacoffee.com Vexingo we keep it ad free, thanks to listeners like you.

Speaker A: Exactly. So let's talk about a specific deal that illustrates the playbook. In 2021, Golden Gate Capital acquired Neuster, a data brokerage and marketing services firm, for about $2.9 billion.

Speaker B: NUSTR. That's the company known for its identity resolution technology, right? Linking digital and offline data about consumers with.

Speaker A: That's the one. Neuster runs a massive database of consumer identifiers. Email addresses, phone numbers, device IDs, household demographics. They license that data to marketers for targeted advertising and to financial services firms for fraud detection and risk scoring.

Speaker B: So it's both marketing tech and risk analytics. Double revenue streams.

Speaker A: Right, and that's part of the appeal for pe. You've got two different customer bases buying different products from the same data. The marginal cost of serving an additional client is very low once the data platform is built.

Speaker B: What did Goldengate pay in valuation terms? I remember data brokerage multiples being all over the map.

Speaker A: Reports at the time put the enterprise value at, uh, roughly four times Neuster's annual revenue, which was around 700 million. That's a reasonable multiple for a data company with sticky contracts. But the key is that Goldengate didn't just buy Neuster for its existing business. They bought it as a platform for

Speaker B: consolidation, a rollup strategy. Buy one large player with an established data infrastructure, then acquire smaller regional brokers and fold their data sets into the same system.

Speaker A: Exactly. You can acquire a local data broker that has, say, 50 million consumer records for $10 million, plug those records into Neuster's platform, and immediately start selling access to those records. At Neuster's pricing, the acquisition Multiple might be 5 times EBITDA, but the incremental revenue from those records Might generate a return in two years.

Speaker B: Plus you get the customer relationships. Small brokers often have deep ties to local advertisers or insurance companies. Those relationships are hard to build from scratch.

Speaker A: That's the hidden value. It's not just the data, it's the commercial relationships. PE firms are buying a distribution network for a product that has almost infinite scalability.

Speaker B: What about regulatory risk? Data brokerage is getting more scrutiny. CCPA in California, GDPR in Europe, and now there's talk of a federal data privacy law in the US M it's

Speaker A: a real risk and PE firms have to price that in. But the interesting thing is that regulation can actually benefit larger, well capitalized players. Compliance is expensive. You need legal teams, data governance software, consent management platforms. Small brokers often can't afford that.

Speaker B: So regulation acts as a barrier to entry, protecting the big platforms that PE backs.

Speaker A: Exactly. And the larger players can lobby for rules that make compliance even harder for small firms. It's a virtuous cycle for the consolidators.

Speaker B: Let's talk about what happens after the acquisition. How does a PE firm actually run a data brokerage for growth?

Speaker A: Well, the typical playbook involves three levers. First, you cross sell existing data products to the acquired company's customer base. Second, you invest in technology to improve data matching and reduce latency. Third, you expand into adjacent verticals. From marketing into fraud detection, or from credit risk into insurance underwriting.

Speaker B: Can you give an example of that cross sell in action?

Speaker A: Sure. Suppose you acquire a small broker that primarily sells consumer email lists to E commerce companies. After the acquisition, you can offer those same e commerce clients Neuster's Identity Resolution product, which lets them link email addresses to device IDs and offline purchase data. The client gets better targeting and the broker's revenue per client goes up.

Speaker B: That's a classic land and expand strategy. You start with one product, then layer on more.

Speaker A: Right. And the economics are compelling. The acquired broker might have had a 30% EBITDA margin. After cross selling and technology upgrades, the margin can expand to 50% or more. That margin expansion is what drives the return for the PE fund.

Speaker B: What about the timeline? How long does a PE firm typically hold a data brokerage before exiting?

Speaker A: Historically, the hold period is five to seven years. But there's been a trend toward longer holds, especially for data assets that are central to the digital economy. Some firms are treating these as permanent capital they never intend to sell.

Speaker B: That makes sense. A ah, data brokerage generates steady cash flow and benefits from secular growth in digital advertising and online fraud. Why sell a cash machine?

Speaker A: Exactly. And there's another angle. Data brokerages are becoming essential infrastructure for artificial intelligence training. The large language models need high quality labeled data. Some PE firms are positioning their data brokerages as suppliers to AI companies.

Speaker B: That's a whole new revenue stream. I hadn't connected those dots.

Speaker A: It's early, but we're already seeing deals where PE backed data brokers sign multi year contracts with AI labs to provide training data. The margins on that are enormous because the data is already collected. You're just licensing it for a new use case.

Speaker B: So the thesis is that data brokerages are not just a consolidating industry, they're a gateway to the AI economy.

Speaker A: That's exactly how the smartest PE firms are framing it. They're not buying data brokers. They're buying access to the raw material of the next computing platform.

Speaker B: What about the risks we mentioned earlier? Privacy regulation, consumer backlash. Could that blow up the model?

Speaker A: The biggest wild card? If the US passes a comprehensive federal privacy law that requires opt in consent for all data collection, that could fundamentally change the economics. But most PE firms I've spoken with think the regulation will be manageable. They'll adapt by investing in consent management and focusing on anonymized aggregated data.

Speaker B: And they have the capital to do that, while small brokers don't. So again, regulation favors the consolidators.

Speaker A: That's the bet. And so far it's paying off. Data brokerage multiples have been rising from around three times revenue five years ago to four or five times today. The market is pricing in that consolidation narrative.

Speaker B: What should our listeners watch for if they want to track this trend?

Speaker A: Keep an eye on the iPodOS. A few PE backed data brokers are expected to go public in the next 12 to 18 months. If those IPOs are well received, it will confirm the thesis and trigger even more PE money flowing into the space. And if they flop, then we might see a shakeout. But given the demand for data from both advertisers and AI companies, I think the trend is in P's favor. Data is the new oil and PE is buying the refineries.

Speaker B: Clean analogy and a good note to end on. Thanks for joining us on private equity conversations with Fexingo.

Speaker A: Um, if you want to dig deeper, we'll link to the Neuster deal case study in the show notes. And if today's conversation was worth a coffee to you, you know where to find.