Kevin Tan

Usually it's tied into a purchase or something else, so there's information about, information can be verified and validated.

So we get a lot of declared demographic data that way.

There's also data across a whole range of sites based on people's interests, the types of media they consume, the types of things that they buy.

We also have another part of our business onboarding of offline data.

And we're the company that does the largest amount of this outside the United States, although we do it in the US now.

We started outside the US and we basically take offline data records.

And those can either be from a brand or those can be from, say, a research company.

And we take those and we match those to digital signals so they can be activated in the digital.

I mean, it ultimately is data.

So we use a proprietary methodology that's based on heuristic modeling.

So we take a bunch of different data signals.

So those could be things that we use, such as geolocation data, that could be demographic data, that could be private ownership data or interest, et cetera.

We have so many data points per individual kind of consumer.

And we use those to match up against data records.

The reason that we use this type of methodology globally is that globally there's a lot of different privacy regulations around the planet.

And some of those don't allow some of the one-to-one matching that you do with PII, say with an email address or a telephone number.

That's correct.

Sorry, I tend to use a lot of that.

We've set up a methodology that works pretty well around the globe in terms of privacy.

It also doesn't require the backbone spine of direct marketing data that works well for a lot of companies in the U.S.