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Ari BuchalterPresident, TechnologyMediaMath
Ari Buchalter, president of technology at programmatic advertising solutions provider MediaMath, oversees all product and engineering teams across a variety of areas, including the demand-side platform (DSP), data management platform (DMP), identity management solutions, creative services and analytics. Buchalter spoke with eMarketer’s Lauren Fisher about MediaMath’s focus on attribution capabilities and the importance of improving cross-device and data onboarding capabilities to enhance the quality of cross-platform attribution modeling.
eMarketer: Where do most marketers stand on transitioning to more advanced attribution solutions?
Ari Buchalter: It is safe to say that every sophisticated marketer understands the challenges inherent with the old way of doing things vis-a-vis last-touch modeling, cookie-based solutions and so forth. We are at a point where everyone agrees on the problem and is trying a series of solutions, but is hitting the limitations of those solutions and trying to figure out how to deal with that.
Over the past five years, the solution has been to build custom, multitouch attribution models that are either delivered by a third-party player that specializes in this sort of thing or to build a model yourself. But many folks are now facing challenges with the fact that the people who build these models are often not connected back to the real-time execution systems or the systems that decide how to spend the money.
eMarketer: What do marketers do then?
Buchalter: We see a lot of frustrated marketers that have models they know are better than what they had before, but the insights end up trapped in PowerPoint or Excel, and the only way they can [take] action is to make very high-level, aggregate decisions like, “I’m going to spend less on this part of my plan and more on this part of my plan.” It’s a shame, because those models are actually built off log-level, granular data.
So what we try to do is focus on the integration point that allows you to take the granular output of those models and plug it right back into the machine learning and systems that can [make] decisions on that information in real time. You can take the outputs of your multitouch attribution and have those weights move your bidding up and down, in real time, based on the characteristics of that impression. We call that “closed-loop attribution,” and that’s something we think is critical to get out of this PowerPoint and Excel paralysis.
eMarketer: Companies looking to attribute across all touchpoints today must account for multiple devices, which means that marketers must use more than cookies to identify audiences. What effect is cross-device having on attribution?
Buchalter: As you said, the cookie is no longer sufficient to do targeting and attribution in today’s world, even in just the desktop space alone. Some browsers, like Safari, are not accepting cookies. And more and more users are clearing their cookies.
Obviously, in a multidevice world, most media consumption isn’t happening anymore in a web-based environment—it is happening in-app. Some 90% of mobile consumption is in-app, and so browser cookies don’t pertain there.
I think these challenges are well understood, and there are multiple solutions. You’ve got your big walled garden players, notably Google and Facebook, but also others like Amazon and eBay that have a large identity graph they can use.
The challenge, of course, is that they are walled gardens. And you can’t get that data out. ... Besides the walled gardens, you have what I call pure-play identity folks like Tapad or Drawbridge, which originally started out saying they were going to be full-service DSPs with cross-device identity but now have started to license their identity solutions.
But even these are creating challenges for clients. One is that if you’re a distinct system and not connected to the execution of the media, then you’ve got to sync, and that can cause latency and data drop-off along the chain. It also means your data is in multiple systems, which concerns some of our clients from a security-risk perspective.
There’s a real need for a scaled, deterministic identity graph alternative. Facebook and Google have theirs, but it’s closed behind the garden and useless for a lot of the applications marketers need. I think you’re going to start to see alternatives pop up where you have deterministic graphs, maybe not quite the size of Google or Facebook, to be able to address these concerns at scale. I think this will happen organically as companies figure out innovative solutions, and you’re also going to start to see some industry collaboration attempts.
eMarketer: Closed-loop attribution means pulling in offline data. How important is this for marketers?
Buchalter: Offline data is critical for a number of reasons. Even for digital advertising, a lot of the actual purchases still occur offline. And so if you show an ad online, you have to measure the impact offline to be able to understand the real benefit.
But the challenge with bringing offline data in is that the match rates aren’t very high. There are a lot of reasons for that. A lot of it is still being done using cookies. So all the limitations we talked about before still pertain. You need a noncookie solution for the web, and you need a cross-device solution to bridge with mobile in-app.
Different partners have different strengths when it comes to offline matching, but marketers tend to work with just one. If you’re working to match a database with phone numbers vs. a database with emails, there might be different partners that would be helpful for you to bring that online.
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