Given the uniquely personal nature of consumers' relationships with their mobile devices, mobile advertising in theory would seem to be the ideal medium for uniquely personal targeting. In practice however, mobile advertising, as Bob Walczak, CEO of mobile ad network MoPhap, explains below, has lacked one fundamental catalyst compared to its online counterpart: the ability to collect and aggregate relevant anonymous behavioral data in a scalable way.

Behavioral Insider: You've noted that till now mobile lacks an infrastructure for advanced targeting -- particularly of the behavioral kind that's now becoming common online. What stage is mobile targeting in now?

Bob Walczak: The big differential so far between online and mobile, and one thing that's really stymied mobile in the early going, is the [lack of the] ability to handle cookies. Browsers in mobile can't handle cookies. Hence mobile advertiser and publishers can't develop detailed profiles of how mobile is used.

No matter how much talk there's been about mobile targeting by networks, until that hurdle is addressed, you really don't have anything that can legitimately be known as behavioral targeting. The essence of behavioral targeting online is the marriage of supply of publisher inventory and the demand for advertisers, and vice versa -- but no network in mobile has been able to make that happen. Essentially both publishers and advertisers have been flying blind.

BI: Is that kind of visibility possible in mobile?

Walczak:  In mobile advertising the primary data -- in lieu of real cookie data -- has been the form-fill information possessed by carriers, which obviously they are not prone to share, for good reason. We're focusing on expanding expectations of what mobile targeting can be. The departure we're making is to develop cookies on the server side.

BI: How does that work?

Walczak: What we do is identify users by device and identify their device as they enter a site on our publisher network. From there we can aggregate information and create a behavioral profile based on a variety of criteria. Our approach to behavioral targeting is then geared to bringing the three main components online advertisers have grown accustomed to into the mobile sphere, telling them who users are, what they do in real time and what ads they tend to be most responsive toward. If you can combine the three in a mobile context, you've got a heat-seeking missile. You've also finally leveled the playing field somewhat between mobile and online.

BI: So you see mobile as being capable of supporting more behavioral targeting sooner rather than later?

Walczak:  Yes, the goals of targeting on mobile are essentially the same as those online, but the tools haven't been there up till now. So closing that loop with server side cookies is one important thing we're doing. The other is aggregating information about mobile-specific forms of data that are extremely important in making advertising work, but often not acknowledged yet in targeting the new medium. One is the multiplicity of devices out there. Unless and until you can identify them, you don't know the type or format of message that's appropriate. Related to that is the whole area of mobile creative. Mobile is blessed but also cursed with a wide multiplicity of potential creative ad units to deploy. But until you understand the device a consumer is using, you don't really have a clue about what appropriate choices you have in creative.

BI: We've talked mainly so far about mobile's limitations and how it can catch up to online. What unique advantages do you see for longer-term mobile targeting of behaviors?

Walczak: Once the initial hurdles of mobile targeting are cleared, there are incredible advantages that mobile has. For one thing, the intent of mobile searchers and browsers is far more directly related to actionable intent and information, so the quality of targetable information is far more relevant. Looking ahead to the next iterations, we believe that mobile will be the catalyst for intelligent agents or Semantic Web 2.0. These are tools that don't just return links about a subject as in a Web search, but rather are designed to find answers based on an evolving understanding of what a mobile user's interests, needs and style of using information are. The agent actually learns the decision-making process of its user.

 The implications for targeting are enormous, and mobile will be at the center of it. In theory what it entails is knowing not just that a consumer is interested in shopping for a car, or even that their tastes seem to run in the direction of auto type A versus auto type B, but the chain of personalized decision criteria and the decision-making process.