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Dstillery Adds Self-Serve Ad Tools, Explores Ways Of Weeding Out Bad Geo-Data

The company is using its viewability verification technology as GeoSpatial Analyst Peter Lenz tries to identify actionable location signals.

Dstillery's Peter Lenz
Dstillery’s Peter Lenz

Marketing tech provider Dstillery has been simultaneously waging war against fraudulent web traffic while gauging the expanded role geo-data plays in online-to-offline advertising for years.

Now, as the company adds to its tech stack with dedicated demand-side platform and data management platform functions, we checked in with Peter Lenz, who left his past life as an engineer in the National Parks Service 18 months ago to become Dstillery’s first GeoSpatial Specialist.

GeoMarketing: What does the role of a GeoSpatial analyst at Dstillery entail?

Peter Lenz: It’s evolved over time. Originally, I did a lot of actual in-depth digging into the data analysis for clients. Over the past 18 months, my role has moved more into an internal consultant. If there’s a problem we’ve linked to geo-data, whether it’s collecting the data or analyzing the data or we’re going to build models from it or anything, I typically get called in so that we don’t abuse the data. So that we treat it right. Geo-data is a different thing than cookies or mobile device ID and it takes a little bit of specialized knowledge. My job is to teach people what that knowledge is.

We’ve certainly seen — and to be sure, written — a lot of headlines about device ID and/or location representing “the new cookie” when it comes to behavior ad targeting on mobile. How do you view that notion?

I think a little bit more nuance is in order. Location data is incredibly powerful. If you wanted to, you could use it as the “new cookie,” but then you’re losing a lot of data along with that. Location should be one signal amongst many. If you’re so hyper-focused on just doing geo-, and you leave out all these other things that we can collect, whether it’s looking at URLs, looking at behavior, you’re not getting the full picture. It’s like trying to paint a picture and all you have is black. You’re limiting your pallet and maybe artists do that as an exercise, but you’re missing the richness of all the mega data that we collect.

Does that mean there’s still a great deal of education needed among clients and agencies about the best uses of location and geo-data?

There are some ad firms out there that really get geo-data. And then there are some who think that it’s a “magic thing” and they just have to say, “geo data,” and that solves all their problems. They don’t think about what locations do I want to target, what behaviors, maybe I want to limit certain areas, maybe I only to connect to certain places.

A lot of people say, “I want data from only these DMA’s and I want people who are then intent on buying these kinds of these brands.” And then there are some people who just say, “Use geo data.”

Then, you have to come and you have to educate them. Well, you can’t just say that, you have to have the sense about what you’re doing, you have to think about targeting the real life implications of what those signals actually mean to them.

Aside from knowing what to target with geo-data, what about “the how?” After all, geo-data quality varies, depending if it’s coming from GPS or a cell phone tower or wi-fi or some other method. How do you talk about that issue with clients?

It’s a challenge for marketers. When you get that data, it all looks the same in a sense. One thing that Dstillery has is a great fraud detection technology. One of the things that we discovered when we really started digging into geo, all these things that we built to be best in class for fraud detection, also worked really, really well at filtering out good location data from the bad.

We actually filter out the majority of locations. We think the majority of location data is actually not good enough to bid on. At least not at this moment.

Why is that? What’s the chief cause of low-quality geo-data?

It’s actually user behavior. A lot of people walking around out there with low batteries on their phones and you have to realize that as the battery on the phone goes down, the system goes to more and more power saving methods to locate itself. So users who are trying more and more power saving methods means that the location data quality necessarily goes down along with it.

What sort of location “horror stories” have you encountered in dealings with clients and partners as a result of low data quality?

We recently worked with a company to do targeting of short-term events and they were very much interested in hitting a particular spot while avoiding a bar or house across the street. That’s a tough problem to solve.

They were also talking to another company that does location data and they said, “Oh, we can get you a 150,000 unique devices at this event.” Well, the event only had 30,000 people attending it, so I’m not sure where they found these extra people. It sounded like to me out there are saying, “We use geo-data to find targets,” not “here’s curated, good geo data to find the right targets.” There’s a huge gulf between the good and everything else.

What will it take to improve the situation? The ad industry organizations often point to creating more standards around defining data quality and the methods used to collect that data.

Establishing standards can help. But right now, it’s education. Teaching clients about what geo-data means and what it can accurately do is important. It’s great to have things where we’re saying what those standards are, but geo-data is still kind of the Wild West. I don’t think we’ve learned all the different ways you can access that data. It might be premature to create standards for it. Let’s talk in six months. Six months it might be a perfect time to do that, but right now we’re still learning.