Brands spend millions on advertising, and those dollars are shifting more and more to digital channels. In fact, 2019 is projected to be the first year when digital ad spend will surpass traditional venues like television, print, out-of-home, and radio. Given that we’re about to hit this important milestone, and that digital ad targeting has become so nuanced and sophisticated, it’s curious that marketers have so far been slow to wake up to the opportunity to target buyers locally.
Of course, an opportunity missed by others can be doubly valuable to those savvy enough to capitalize on it. Let’s pause to consider the case of multi-location brands. Whether your example is Target, Starbucks, Jiffy Lube, or any other major brand whose marketing strategy is ultimately about driving traffic to stores, you will find most digital marketing dollars still being spent at the national level, where consumers may be targeted based on demographic criteria (as with lookalike audiences) or interest patterns (as with tracking cookies), but with only a very general sense of geography.
It would not make any sense, for example, to serve an ad to a consumer in a state where a brand has no stores, but aside from that, typical ad spend is more or less geographically agnostic. This fact derives from assumptions in traditional advertising, where brands theorized that their job was to build awareness and hope for conversion. When it comes to ecommerce, where location is not a factor, the model is still roughly correct. But when local stores come into play, brands could do a much better job of reaching out to consumers at the precise times and places where they are most likely enter a store and make a purchase.
Localized Targeting with Google
Google has helped to define this opportunity by integrating its Ads product in several ways with Google Maps and Google My Business. Now, you can add so called “location extensions” to your ads, pointing consumers to the nearest store location, as well as sponsored local listings that can be positioned prominently within Google’s local results. What’s more, with Local Inventory Ads, retailers can cause their listings to surface for product searches, creating a hugely expanded set of opportunities for local stores to rank for granular, high-intent keywords.
But that’s just scratching the surface. For those who want to delve into more sophisticated solutions, Google Ads scripts provide a very powerful means of designing ad campaigns that can be triggered and modified according to a variety of contextual factors. Let’s say you’re promoting a chain of ice cream shops. If you assume people are more likely to want ice cream on hot days, then it makes sense to dial up your ad spend as temperatures increase, and to dial it down when it’s raining or when the weather turns colder. Using Google Ads scripts, you can integrate with the Weather Channel’s API in order to automate those spend modifications and target them locally. In other words, you can bump up your spend specifically in Florida when the weather’s hot without affecting your Maine locations. And we’re not just talking about cross-country variations. In the county in California where I live, temperatures vary by as much as 10 to 15 degrees depending on whether a town is on the coast or inland. Ad spend can now be precisely configured to match these fluctuations.
Weather is not the only locally relevant factor that can be linked to Google ad campaigns. Consider that for most chains, one store’s offerings may differ slightly from another’s, and that stores may promote themselves through special in-store events and similar activities. As long as you can track all of these location-specific details in a database, you can link that data to your ad campaigns and provide locally relevant ads that showcase the special features of each location. Take the case of in-store events: campaigns can be designed to target local users in advance of the event with unique details such as event name, description, location address, phone number, and RSVP link.
Why would you take the trouble to do all of this? Because locally targeted campaigns do a better job than national campaigns of reaching the right audience. Money spent on ice cream ads in a rainstorm is money running down the drain. Local targeting ensures that you’re spending ad dollars to reach the right audience at the right time.
Mobile Targeting: Using Location to Boost Relevance
Brands use various means to track and target loyal customers. One of the most popular of these is the ubiquitous loyalty program. How many times have you been asked to join a loyalty program by a cashier at your local retailer? After a while, many consumers grow tired of these requests. In fact, studies show that consumers only participate in half of the loyalty programs they belong to.
Location tracking can help you to identify loyal customers in terms of actual store visits, rather than participation in a voluntary program. A multitude of apps these days -- weather apps, messaging apps, fitness apps, games, and more -- include location tracking as an opt-in feature, and a surprising number of mobile users have granted these apps permission to track their location even when the app is not running. Marketplaces can give brand marketers access (properly anonymized) to consumer location data, which can then be correlated with the geographic coordinates of a brand’s store locations, or those of its competitors.
Multiple targeting opportunities flow from this connection. With location tracking data, brands now know exactly how many times a consumer has visited a store location, and can target offers based on this frequency. Loyal customers, defined as those who have actually visited a store multiple times, can receive different kinds of offers from those who have only visited once or twice.
At first, this type of targeting may appear very similar to typical demographic targeting of the sort that is used to create lookalike audiences on Facebook. Here’s where it is helpful to bring up the difference between so-called deterministic targeting and probabilistic targeting. Geographic targeting is deterministic; it’s based on concrete data attributable to the user. Much demographic data, on the other hand, is probabilistic, meaning that it is inferred from behavior. If you buy a certain skin cream online that is generally marketed to women, a probabilistic model will guess that you are female, but this could be incorrect. The physical location of your phone, by contrast, is a verifiable fact. Deterministic signals like location are far more reliable than probabilistic signals.
Again, this difference means money spent on locally targeted ads is much less likely to be wasted. With local targeting of the type I’m describing here, you can serve a highly relevant mobile ad to a consumer who is more likely to be receptive to its message.
As with Google ads, mobile targeting can also contain locally relevant content such as products, offers, amenities, or events specific to the location that is nearest that particular consumer. Weather and other factors can also be used to modify campaigns. In fact, localized Google advertising can work together with mobile display. Properly configured cross-channel campaigns can mirror and reinforce each other, providing multiple paths to reach the same precisely defined set of local consumers.
Precise targeting means better budget utilization, more conversions, and higher return on ad spend. Multi-location brands owe it to themselves to explore this opportunity while it is still underleveraged by most advertisers.