David Danziger: I'm desperate for DCR not to become a three-letter acronym for “data clean room.” I have thought about that and I dread it. But “data clean room” seems to be the terminology that's caught on for the general concept of first-party data collaboration among multiple parties.
When I think of Habu, it’s as a software company that works across distributed data platforms and with brands to deliver more comprehensive data. Data collaboration is not necessarily easy right now in terms of infrastructure, integration and application. But those are things that a lot of people are looking to solve.
What companies or kinds of companies are potential partners for Habu?
One group is the major strategics and platform partners. We had an announcement recently in conjunction with Snowflake related to their Media Data Cloud. That's a perfect example. Snowflake does a great job enabling the infrastructure and integration components. And brands are already comfortable working with Snowflake in a first-party container capacity. We play a key role in helping those clients get good insights out of the combined data sets.
Other similar partnerships that come into play are with Google’s Ads Data Hub and Amazon Marketing Cloud. Those are areas where clients already have their data, but they have trouble getting insights out. We can create ways to work together there. We typically refer to those as industry clean rooms.
The other types of partnerships are data collaboration clean rooms, whether it's data companies, identity companies or measurement companies that can help round out the perspective for what a brand is looking for.
Does Habu focus exclusively on advertising and marketing use cases?
The primary area of focus at this stage is advertising and marketing. I think that if you and I were to have the same conversation some years down the line, it could be much broader, because the concept of data clean rooms and gleaning insights from multiple data sets simultaneously is certainly not limited to marketing and advertising.
But it’s a space where we have experience, and we see a maturation and hunger within that market for the concepts we’re bringing in. That’s a long-winded way of saying that the near-term opportunity is advertising and marketing, but longer term I certainly see other opportunities or licenses as well.
For example, one of our clients is a luxury auto brand that has its own first-party data, it works with an agency, it uses The Trade Desk – which means it has log files – and it works with a third-party location data company to connect IDs to retail foot traffic. All the data sits in Snowflake, and can be used in combination by Habu to pull insights from log files, third-party location data and the first-party brand data. Afterwards, we can see who ended up taking a real-world action [showing up to a dealership] and at what point in the funnel they’d been targeted.
These are not easy things to do and data sets to recombine unless CMOs have a group of data scientists sitting around waiting for something to do. Which is not the case.
It’s my impression that Google’s Ads Data Hub is the most developed of the major platform clean rooms, and yet it still seems like ADH has gone quiet. What does that mean for Habu?
I think you’re right that it has gotten a little quiet. I like to think we are the antidote to that, in a way.
One factor is when Chrome delayed third-party cookie removal, some of the conversations became less urgent. But the second part, and why I think of us as the antidote, is that it’s very hard to get useful insights out of Ads Data Hub unless you are a really adept user of BigQuery [Google’s cloud data warehouse, which supports queries using the SQL programming language].
This isn’t meant to be a criticism of Google, but users show up and are confronted with a blinking cursor. It’s up to you to write the SQL to get insights out. That’s a challenge for most marketers. Whereas, if you’re sitting in front of software that already has the data connections and some basics, a business user is able to write in natural English what they want to get out, and that makes it approachable.
To be frank, a big part of the reason I think ADH has gone quiet is that these clean rooms are not the easiest things to use, unless you have a talented team, or software that knows the querying languages and can visualize the results in useful ways.
This interview has been edited and condensed.