Mobile technology has marketers excited. As consumers spend more time connecting to the internet on a device beyond a traditional laptop or desktop computer, they are creating more signals marketers can use to target and tailor ad messages. Some of those signals are being leveraged via in-store beacons, which can trigger location-specific messaging to drive purchases.

This combination of online ad serving and offline activity is exciting, but it's also very much still in its nascent stage, lacking clear benchmarks and best practices. Fortunately, marketers don't have to wait for beacons to mature to realize their full promise of offline-to-online marketing. It's possible to leverage very similar strategies right now using mobile as a proxy to tie offline information back to mobile and desktop ad serving.

Mobile data emphasizes physical context, and that's where the true value comes from. The promise of beacons is that the mobile signals create an understanding around physical location. But marketers can get a similar 360-degree view of the consumer using cross-device data and targeting.

The key here is a metric called store visitation rate, which comes close to closing the loop for understanding the ROI and offline performance driven by digital marketing. Marketers can monitor how often a particular control group visits a brick-and-mortar store, and then compare that to a test group to see if exposure leads to in-store visits. This is consumer-level data that can be used to target consumers on another device, as well as optimize campaigns.

For example, a restaurant chain can collect data on users who have visited their locations in the last 30 days, and build this as a targetable audience segment on a desktop. They can serve this audience specific "frequent diner" messaging, such as a discount coupon or free appetizer offer. When that offer is then redeemed, the brand has a very good sense of the ROI its efforts produced.

It's also possible for marketers to segment audiences with mobile demo data (such as gender within a specific region), which is helpful for campaigns targeted to a specific audience or timed event. For example, auto brands can reach prospects who have visited a dealership in the past 30 days and serve ads to draw them back during a major sale event.

Where beacons show how consumers have responded to location-specific messages, focusing on mobile data and using it in a desktop advertising strategy actually gets much closer to a closed-loop system. For hotel and hospitality marketers, it's possible to target specific airports with flight cancellations, which are received in real-time. Marketers can use location data to understand the consumer conversion patterns surrounding those airports, verifying the mobile targeting strategy. Simultaneously, data from the desktop, such as past purchase behavior, average order value and loyalty/membership data, in turn inform targeting tactics for different segments on mobile as well.

Beacons have a lot of promise, especially in the retail sector. But most marketers will have to wait for clearer use cases and well-defined protocols. They can wait, or, they can use mobile as a fairly accurate proxy to understand consumer behaviors, and tie that data back to mobile and desktop marketing efforts.

This creates a stronger foundation for a marketer's data set, allowing them to create more informed consumer profiles for their campaigns. In theory, this delivers better targeting, optimization and overall performance, especially if that performance metric is transactional. In an increasingly competitive landscape, advertisers need to use every advantage they have in following the consumer's non-linear path to purchase.