Easterling cut his teeth at Digital Impact, an email marketing company that taught him how to use data to target users. From there, he started his own search marketing firm that used keywords to target consumers.

Now he works with Twine to help marketers develop new revenue streams from their data.

Mobile Marketing Daily: What are some of the stumbling blocks for marketers and publishers with regards to data right now?

Easterling: Sometimes, it’s just basic technical things and infrastructure stuff that needs to be put into place. It’s also a different asset class—having a mobile ID or basic data infrastructure is foreign to many app publishers.
On the other hand, the idea that data is an asset is a weird one. The inputs are very varied from the devices. People connect very personally with the devices, and that allows personal data to flow, which makes it valuable.

Also, understanding what data is valuable and how and when is best to collect it. Publishers either have no idea how valuable the data is or they overvalue it immensely.

Revenue is coming from data, but the industry is not maturing, and they don’t know how to commercialize it. Publishers are asking, “How do we allocate the right staff?” But now we’re also starting to see data monetization people getting hired.

MMD: Quality data has been a limiting factor for growth in mobile—is that changing, or is the industry justhoping it will get better if they keep spending money on it?

Easterling: First, fraud: You have this cat-and-mouse game, where publishers have an incentive to lie for higher CPMs.So where is the data coming from in mobile? Desktop is the first case.

You’ll find PCs that share a device, then take that dataset and connect it cross-device to mobile, but it’s got a 20% failure rate, so connecting data from desktop isn’t super great.

There are companies out there that have nice brands and shiny Web sites, and they’ve set up media buying arm to vacuum data from the bid stream. There’s no value to that data because it’s hard to separate the good from the bad.

Or the data comes from your app, but you’re small scale, so you go to a company and model it in order to multiply your datasets, but there’s some lost in transmission in that process as well.

There is always going to be challenges with a third party. There’s an incentive for data providers to mix in the bad with good, and they do that by building models and inflating their datasets. Because of that our data is deterministic only, we don’t model it.

MMD: Does the noise come from publishers who don’t know how to collect data, or is it just inherent in the mobile ecosystem that data is going to be a somewhat haphazard?

It’s both. It’s the wild west, and a guy just rode into town with snake oil. There’s a greater need for education and standards in mobile than there is for desktop. But the problem is endemic to data in general, too.

The great thing about a platform like Facebook is the data is controlled and self-cleaning. Outside that, you’ve got to deal with a slippery world, and there needs to be a new methodology for purchasing data.

MP: What would that methodology look like?

Easterling: The historical model is, “Hey, trust us.” But, there’s got to be a better way to do this and bring transparency and quality. It’s being clear whether data is deterministic or probabilistic—and I think those they should be priced differently.

Companies like Nielsen and Datalogix are founded on probablisitc data, but they had rigorous methodologies around how they collected and modeled it. We also need to provide transparency around publisher IDs. These represent ideas that no one else is doing on mobile.

MMD:With how imbalanced the app store is, is selling first-party data the only recourse that smaller publishers have to remain competitive against the giants in the field?

There is going to continue to be consolidation. Data is still not going to help those smaller fish—a lot of VC funds are drying out. But those mid-size apps that do utilize their data can open up a passive revenue stream that can provide significant marginal benefit.

MMD: Last thoughts?

Easterling: 99% of data is fragmented, and all that value is locked up in the ground. It’s the biggest shale gas reserve in the world.  We think a unicorn is going to come out of this. That’s the opportunity, and we’re going to shoot for that.  It’s the largest aggregation of consumer behavior in history matched with the largest fragmentation of consumer behavior.