Clean rooms explained, consent data, and legal complexity

**Jonathan:** Hey, Fred. Nice to see you, man. Welcome. Yeah. Welcome to the privacy huddle. So we're out here in Miami. We're at Possible Conference. Yeah. Ton of marketers, ton of agencies. Nice to share this booth with you here. Thank you for hosting us. Oh, no. Of course. Just our usual fee, of course. So look, you're at Habu. A clean room. We've been hearing a ton of discussions on what clean rooms are. One of the things I wanted to dig in with you today is, firstly, there's a ton of complexity around clean rooms. And part of it is just messaging complexity. Right? Like, first of all, what is it? What is a clean room? I hear things like it's a place where your data goes in and it comes out clean, almost sounds like a laundry. It sounds super weird, but can you just shed some light on what a clean room is actually? **Fred:** Yeah. I think the interesting thing to start is what is a clean room or not. Okay. Right? And so to your point, it's like — I just heard yesterday, I had a meeting with a prospect and they were actually telling me, hey, do I clean my data for a clean room? Because they did a cleansing exercise. Right. And this is not the case. A data clean room is a platform to actually enable data collaboration between two parties in a privacy-compliant way. **Jonathan:** What's a good example of a use case where they'd share data? **Fred:** A use case will be, for instance, like we have an advertiser that has conversion data, you have a media company that has ad exposure data, and they both want to understand how a media advertising company contributed to converting users for that specific product that they were advertising. And so both parties can actually share the data and mingle the data to analyze it and then understand the impact. So it's actually used for measurement. But once you've done the measurement, then you can actually kind of push it a little bit further and try to understand, okay, what audiences will perform there on the media campaign, and then you can push the audience in an activation channel. It's really about measurement, addressability, the main two, and we'll say that the initial use case that clean rooms were actually developed for, or initially adopted, I should say, is really insights. Gotcha. Right? So you as a company that have good attributes or characteristics about your viewers or your audience. Me as an advertiser might have a good understanding of my approaches as well. And then you can actually mix it up and see whatever correlations there are between those two audiences. **Jonathan:** So a consumer-facing brand might have a ton of media data. They're spending money on TV and digital advertising for these places. Yep. They know the people. They know their profiles. Yep. They may drive them to a retailer or a grocery store or whatever the case may be. They see the transaction. They don't see what kind of person was there. Yep. And then the consumer goods company drove the person there, but doesn't necessarily know that they made the purchase. And this combination of data helps them complete the journey, complete the insights. **Fred:** Exactly. Yeah. **Jonathan:** How do you make sure that it's all privacy safe, which is kind of our jam at Ketch? How do you do this thing? **Fred:** So, I mean, the beauty of Habu's clean room is that it's not only limited to two parties, two data feeds coming together. And so what we see here is that consent management is an important part to play in the privacy space. And so what you can do in the data clean room is actually have consent data feeding the clean room so that, basically, both parties can actually go and understand what the data can actually be used for, what are the use cases. So some consent management players are actually not providing that level of details, meaning the consent that the user has provided and for what purpose. Well, some players like Ketch do that. Right? And so that's the important part. Right? Because we want to make sure that, one, if it's for analytics, we can potentially do this across a much larger audience than it is for activation. If somebody has not given consent for targeting, then we don't have use for those purposes. So we've been thinking about what to call this. One of the terms we've been throwing around is permissions data. You have your data set, you know exactly what you can and can't do with it. Those permissions come from consumers, basically. I've opted in or I've opted out. And I've opted in specifically or haven't opted out yet for analytics, or targeted advertising, whatever the case may be. And that maybe ties back to those use cases. Here's what I'm actually allowed to do with that data, in a way that is in real time, in a way that gives you confidence, basically, to use the data. Marketers don't have to worry about where the consent comes from. It's here. It's good to go. Just use the data in a way that you use it. **Jonathan:** Tell me about the legal complexity around clean rooms. I mean, just everything around — are you a service provider? Are you not? And this could be something that you're getting with Alysa on next week. What are some of the general themes and trends you're seeing, the legal implications, if you will? **Fred:** I think, I mean, the interesting thing is when you look at the adoption of clean rooms today, especially in the advertising space, a lot of the complexity of adoption has not been about technology. The technology is there, it's ready, and we have actually developed integration with all the major players out there to facilitate that bridge of data. What the complexity is is actually on the legal front — it's not necessarily us in the clean room and the client, but a legal framework that actually plays much more between the two collaborators. But we've seen now tremendous movement in the market because those frameworks are now being put in place. **Jonathan:** Gotcha. Yeah. Awesome. Thanks. You know, was gonna ask you about technical complexity. But you say technical complexity — it sounds like it's more a legal and business thing. Well, in closing comments here, what are some good themes, things to think about? First of all, do we call them clean rooms or are they collaboration rooms? **Fred:** I think collaboration rooms. Gotcha. Yeah. And so, in the advertising space now, we have a multiplicity of clean rooms being spun up. We saw major players — Amazon, Google, Snowflake — all actually bringing the clean room offering to market because advertising is actually being reframed. It's all about that data collaboration. And so it's just about everybody starting to do it, finding a use case, and then scaling up. **Jonathan:** Excellent. Fred, thanks. Enjoy the conference, man. **Fred:** Thanks, JJ. See you, man. Alright. It's really fun. I'll dig into the legal pieces. **Jonathan:** Sounds good.