How Flippa Matches Buyers & Sellers As A Marketplace (Blake Chat Clip)

Have you always matched or is that something that you've just more recently started doing?

Matching's at the heart of the Flippa experience and it has been since day one. So you can match in 2 ways in a marketplace environment and probably not that different to an e-commerce environment actually, where you use a combination of both implicit and explicit preferences. And an explicit preference is obviously where the buyer tells you a little bit about what they want. And that's critical because you can match those fields with the same fields on the sell side, and matching is actually not that difficult. Implicit is a little harder, right, where you're trying to figure out around the edges above and beyond their explicit preferences what they might want to see and what they might consider to acquire. And so we do a lot of work around that, but it's been at the heart of the Flippa experience for a long time.

Got it. On the note of matching, in order to better match, as far as how are you helping some of the businesses as far as create listings, ensure the quality of the listings, and then maybe even help them with pricing suggestions?

Yeah. So there's a couple of things going on there. So top of funnel, we have our valuation product. And it's an intelligent valuations effort. It's backed by 5 different machine learning models. We take both Flippa's own historical data sources as well as we do industry insight. And we then attempt, and we get better at this every month, we attempt to accurately match— sorry, accurately value the asset. And that's based on the age of the asset, the financial inputs, the operational detail, things like Amazon seller ratings if it's an Amazon store versus MRR, churn, and LTV if it's a SaaS business. So everything's sort of balanced out individually. Then we have an onboarding functionality, and as it relates to the question around that experience and how you verify We tend to use a combination of data as well as human verification. The data relates to connections. So we connect to Stripe, we connect to Shopify, we connect to QuickBooks Online, we connect to Google Analytics, we connect to AdSense, and a multitude of others. And we will continue to build out those integrations so as sellers can better list and we can better verify the quality of the asset. That verification, programmatic verification, is then matched to human-level verification. And so we go through a bunch of checks with respect to the asset and the asset sizes. Once they've completed the onboarding experience, that's when the matching starts. Now we do have an off-market too, and the matching actually begins further up funnel. And the off-market is a bunch of stuff that you can't see on Flippa today. It's the same functionality, but there are a bunch of deals which those business owners don't want exposed to a public marketplace. And they typically be high, they're typically higher value in nature. But the matching fundamentals are the same, the verification fundamentals are the same. On the buy side, the onboarding basically asks a bunch of clarification questions about what they're looking for. And so we're trying to qualify the buyer so as we can get a best fit match with the seller. So things like, do they have experience with a particular business model? How many assets do they currently own within that business model? What is their overall budget? What is the breakdown of that budget and how many assets they want to acquire for that total budget? Where are they based? Do they Do they have any biases toward the types of sellers and assets they want to acquire and the location of those and a bunch of other factors? So hopefully that answers the question.