TIM JENKINS: Our stake in the ecosystem is what’s happening in mobile made measurable. In 2011, when I took over as CEO, the company was trying to find itself. We set out to understand why marketers weren’t spending in mobile. Brand marketers told us it was the lack of tangible ROI.
How does your technology work?
We use a key to match data systems and transactions and close the loop on the measurement side. With our technology, we can associate 150 million mobile devices with more than 100 million households.
We built a database that has the device IDs that are associated with a specific home location – all completely anonymized – which we can reverse geocode to an address. That address is used as a match key with offline data sources like Nielsen Catalina, Acxiom and Experian. On top of that, those same addresses with the same match keys are matched to transaction systems.
Can you give me a use case example?
Think of frequent shopper data. Groceries have frequent shopper cards that capture all your transaction information and that is shared anonymously with data aggregators.
And so when we run a campaign, the advertiser tells us what their segment needs are, we know which households fit in that segment and we push an impression back to our data partners. They get the transaction data and compare that to people who saw an ad vs. those who didn’t see the ad to measure actual sales lift. We know this works because we’ve done over 115 campaigns with 79 brands.
How do you combine different databases, like a CRM database with third-party data?
The CRM data sits in its own environment and it’s not commingled with anything else. We work primarily through Acxiom’s Audience Operating System. In that system, all our household data has been uploaded into Acxiom and they’ve matched that across the CRM files that they have from Fortune 500 companies.
So we’ll take the CRM files of a major department store, for example, and plug it into Acxiom’s Safe Haven [anonymized data-matching tool] and match the CRM data to our household files.
Let’s say I want to target women who have not purchased shoes in six months but are heavy shoe buyers. We will target those devices related with those households, push the data back to Acxiom, which will compare it to the transaction data that’s captured by the retailer and do the same test and control modeling that I mentioned.
What type of ads do you offer?
We are 80% mobile in-app followed by mobile Web and we’re launching multiscreen capabilities in our platform [via a new product called AdHaven Bullseye MultiScreen]. With these new capabilities, we’ll be able to go from online display to mobile.
How does the new product work?
We’ve been able to sync cookies on the display side to the household IDs associated with mobile devices, and then we can do ad serving across display and know that we’re hitting the same devices in the same household in mobile.
Which devices are connected through the multiscreen product?
We’re talking about a laptop to a mobile device to a tablet. We go where there’s scale. Some advertisers are asking about addressable TVs and making deals on the set top advertising side, but that’s a small population today. The majority of our customers tell us if you can connect me between the PC, mobile phone and tablet, we’ve made major strides.
Can consumers opt out of being included in your database?
Consumers have to opt in to be targeted before we’ll use their location information and other information through an ad request. We also give you the opportunity to opt out through the AdChoices icon.
What mobile trends are you keeping an eye on?
What’s here to stay as soon as it becomes more targeted is mobile video. The problem with mobile video today is that most of the mobile video players have not included any location capture capabilities in their SDK. You’ll get IP information, device information, but not location information.
Mobile video is not all that targetable except from a content standpoint and beyond that, it’s difficult to build user profiles around it because the data lacks a lot of the signals that you get from other applications. But that’s going to evolve quickly. We see a lot of potential around the ability to leverage TV assets across other screens.
What are some remaining gaps in connecting consumer data?
Better location data. That is a big weakness in this business. There is so much that is being based on location, but the quality of what we get in location information from the sell side is spotty at best.
Why is that?
It has to do with how the applications were written. For a lot of the apps, capturing location information is an afterthought. A lot of that is being retooled but you can still get a lot of questionable location data.
I’m always skeptical when I see companies that are 100% location-based and talk about being able to get one signal and determine that this person is in that place and meets a certain profile when they might fit different profile two blocks later.
We don’t believe location is the end game. You have to take into account historical buying behavior, combined with where you are and what you’re doing to have a full profile.