Advancing Location-Based Advertising: Moving beyond “Location 101”

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Advancing Location Based Advertising: Moving beyond “Location 101”
Amy Fox

This is the first post in our “Moving Beyond Location 101” series, which will focus on advances in location-based data and technology – as well next-level strategic thinking – for marketers new to the practice.

Location-based advertising has evolved rapidly over a short period of time. In fact, location advertising as we know it today has been around for less than four years, and it’s only getting better over time.

Location 101, the first wave of sophisticated location-based advertising, was facilitated by the growth of display and programmatic, which allowed marketers to employ location data at scale. At that stage, the focus was heavily skewed towards proximity advertising; on reaching consumers near a particular store. For example, if you were marketing a quick service restaurant like Denny’s, you could target lunchtime crowds near your stores with offers for a Grand Slam.

Taking Location Data to the Next Level

Whilst there’s still a lot of value for retailers in the use of location for proximity advertising, the industry has matured in many ways, and now the attention has turned to much more sophisticated applications for location data.

Primarily, marketers now use location to build historical audience & behaviour data profiles. By understanding where consumers go and what their habits are regarding certain types of locations, marketers have an unique opportunity to build a much more thorough picture of them in real life. For example, if someone goes to a school or daycare facility twice a day, five days a week, they’re likely a parent. This data can be supported and enhanced by online habits, like visiting BabyCenter or shopping at ChildrensPlace.com. If that same person then goes to an office every day between those trips to school, we can further identify them as a working parent, building us a more complete picture of our audience.

To give a more detailed example of how this data can be applied to a campaign, let’s say you represent a sport beverage company like Powerade, and you’ve partnered with an NFL team for some promotional activity. You have the opportunity to target everyone in the MetLife Stadium at a game, but you can be fairly certain that only about half the attendees will match your profile (assume about half will be scarfing pizza and beer on the sofa for the next game.) By taking into consideration additional historical behaviour data, you can narrow your target audience down to, not only users seen in the stadium, but also those who have been to a gym three times the previous week, who have attended marathon events or century rides or have been to a sporting goods store.

By overlaying the two subsets of data – we have now reliably filtered out the couch potatoes in the crowd and left ourselves with a fit & active audience with an ongoing interest in NFL.

In reality there can be up to 40 data attributes associated with every programmatic impression, all of which can be used to overlay a new targeting parameter, although it is worth bearing in mind that not all of them are completely reliable or scalable. Location data has given marketers the opportunity to better refine and understand their audiences, ensuring that ads are reaching exactly the right consumers – and impressions aren’t wasted.

Once an audience is identified, location data can also be applied dynamically to creative, so that consumers will see ads relevant to them. For example, that Powerade audience might see ads that feature an offer for $1 off a sport beverage at their closest retailer, and a map to get to that store.

Indispensable data that’s also safe

One important thing marketers should know about historical location data is that publishers are required to obtain customer consent before collecting and passing location data for advertising purposes. When you as a consumer give an app permission to use your location data, they will then pass your GPS location data for advertising purposes. We at Blis use this data, the consent is given at a publisher level.

What we get are anonymized device IDs that we build up into statistically relevant segments. While these are incredibly accurate data sources, they contain absolutely no personally identifiable data (PII).

It’s incredible how far location has come in such a short time (pun intended). That we can leverage location data for far more than real-time location advertising is pretty exciting already, and it is still early days. With increased accuracy and advances in digital advertising overall, it’s even more exciting to think about what we’ll be able to accomplish in the very near future.

Next up in the series: Learn all about the sources of location data, and how to choose which is (or are) best for your campaign.

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Amy Fox is Head of Product at Blis and is responsible for high level product strategy and development alongside the release of new revenue streams and products into the market. As one of the original Blis employees, Amy has grown her career over the last few years from an entry level role in partner relationships through to heading up both Operations and Product sequentially.
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