Metamarkets Gets Real-Time For Mobile, Geo-Data

Mike Driscoll, Metamarkets’ CEO

“In a space where hundreds of thousands of dollars in ads can be bought in an instant, there’s a significant advantage for those who can see the results immediately instead of waiting hours or days,” says Mike Driscoll, CEO of data provider Metamarkets.

The San Francisco analytics company just unveiled what it claims is the “first real-time analytics platform for programmatic advertising.” That seems like a major boast since there are so many Data Management Platforms constantly expanding their speed and reach of the consumer information they gather. The one clear twist here is that Metamarkets is emphasizing the value of this new platform for mobile ad exchange operators. To prove it, Metamarkets has signed up an all-star list of real-time bidding players for its analytics software, including Chartboost, Flurry, Inneractive, Millennial Media, MobPro, MoPub, OpenX, Smaato, and Vungle. We spoke to Driscoll about what makes this a “first” and how real-time geo-data will be filtered into its findings.

GeoMarketing: What is “first” about this analytics platform for programmatic? How is it different from what, say, Turn or [x+1] or Neustar/Aggregate Knowledge already offer?

Mike Driscoll: It’s a great question. It’s one we get occasionally, when people ask, “How are we different from a DMP or a Demand-Side Platform?” Unlike DSPs, we don’t buy or sell media. We don’t transact on the markets that we work with. We are a technology solution. As for DMPs, one can argue that they don’t transact on markets either. But unlike DMPs, we don’t buy or sell data. We’re not really in the business of collecting data from folks out there, harvesting search terms or audience metrics. We’re a neutral analytics platform.

How do you gather your data then?

Our clients send us streaming feeds of their transactional data and we enable them to see it all in real time. One way to think about that is in comparison with Salesforce. Salesforce doesn’t necessarily own your customer client lists, so they’re not in the business of buying and selling that information. Axiom and others might be in that business. They are a pure technology platform that help people make sense of their sales processes. Likewise, for us, it’s about helping people make sense of these truly enormous and unprecedented size data streams.

Given the list of mobile RTB players you signed on for this platform release, what is the value you’re providing in that space?

One thing we found is that the mobile space has definitely been the most innovative. The mobile exchanges have been the fastest moving.

It’s no surprise that we’ve all recognized the power of geo-data and geo-marketing via mobile devices. Mobile allows you to target individuals. These are individual devices. They’re often not shared with others. That creates a clear opportunity for understanding consumers through their usage of these devices. But there are some data challenges that come along with the opportunities. And we’re really uniquely suited to meet some of those challenges.

When you have both time and space exploding in terms of the granular data that can be accessed, plus the addition of location data, being able to make sense of it real-time is fundamental. To be specific, it doesn’t do anyone a lot of good to know that a person was near a Long Horn Steak House six hours ago.

Aside from being able to pinpoint a consumer in the actual moment, do you see real-time analytics playing a role in targeting more generally? For example, does being able to see geo-data in real-time replace other behavioral touchpoints, like the use of the cookie on the PC-based web?

It’s very clear that the intersection of programmatic and location-based targeting is very powerful. It’s the Holy Grail to allow marketers to deliver the right ad to the right person at the right time in the right place, right?

As for the gradual shift away from the cookie, that can be related to the rise of geo-data. After all, geo-data is factual. A lot of the information and a lot of the data that marketers are targeting on today is inferential. A person can be highly indexed to be a suburban driver according to the cookies on their PC. The great thing about geo-data is that it’s actually based on facts about audiences. I think that piece makes it not just powerful, it makes it believable.

Using location also fits into the way that marketers are used to buying. If you look at the way radio advertising and [Designated Market Area]-based advertising has been bought and sold for years — that’s effectively location-based advertising because it’s geared for specific geographies.

So, from Metamarkets’ perspective, do you see geo-data primarily as a real-time targeting tool? Or mainly to develop a deeper level of understanding of consumers in order to replace more “inferential” marketing categories like demographics?

The short answer is that it’s both. As I say, understanding the audiences that are already there, and that you may want to target against is absolutely important to marketers.

One of the biggest use cases that we’ve seen for the location-based data that we see surfacing on our dashboards is that buyers want to know about targeting based on narrow geographies. Buyers often have [requests for proposals] that say, “We want to buy ‘X’ demographic in Cincinnati, in Cleveland and Pittsburgh. How many uniques can I find in those geo-regions?”

The marketplaces serve that data through Metamarkets in a way that they weren’t able to do before. Certainly allowing them to do media planning with the location-based layers is a very powerful tool.

Secondly, marketers want to look at the performance of a campaign across all of the available consumer attributes they requested. Those attributes may include demographic data, device data. It may include any number of things, but geo- is a huge factor for understanding how audiences are really engaging with an advertiser’s messages. So there are a lot of different ways this real-time information is extremely valuable to marketers, agencies, and the exchange operators themselves.