Most marketers these days have come to understand the power of location data. By analyzing location signals from apps, brands can gain valuable insights about the audiences they are trying to target. In their simplest form, location signals give marketers insight into consumers’ actual locations. When analyzed over time, location data becomes more valuable by giving marketers a window into consumers’ offline behaviors like frequency of store visits, purchase patterns, how long they spend at a location and brand loyalty.
With the emergence of location data, many marketers are making a mistake in its application by focusing exclusively on its simplest form of actual location points. This practice, called geo-fencing, severely limits the potential of location data and also the reach of a digital campaign.
How geo-fencing misses the mark
A geo-fence is a virtual perimeter around a location on a map, which can be triggered by customers entering that location. For example, as a mobile user walks into a store, the smartphone’s location triggers the geo-fence and the user receives a notification such as a product suggestion, promotions, etc. Sounds like a great way to target a potential customer, right? Let’s say someone walks into a Starbucks and they get a coupon for a bagel on their phone. In theory, that person would be more likely to buy the bagel than if they didn’t receive the coupon. However, when we look closer, we run into problems.
First, when marketers rely on geo-fencing alone, they automatically limit the size of their target audience. The Starbucks example given is only successful for a small number of people who may have their Starbucks app open the moment they step into a Starbucks. This is the case for any geo-fence marketing campaign, which presents consumers with messages within apps when they enter a specific geo-fence. When you consider that this means a consumer has to be in the perimeter and also be using that specific app, it becomes clear that this is not something that everybody does or has the ability to do when they are shopping. Additionally, at this point, marketers are reaching consumers at the very end of their path to purchase when they likely have already made up their mind. Unless you are hoping to reach the impulse shopper (and hoping that he/she has that very app open) it remains to be seen if the ROI on this tactic makes it really worth it.
Furthermore, serving an ad to a consumer who’s passing through the geo-fence does not guarantee that the consumer is remotely interested in the product or service advertised. For example, what if the geo-fence in the Starbucks example encompasses a few feet of sidewalk around the Starbucks entrance? Using just the data from the geo-fence to serve an ad to a consumer outside the Starbucks does not guarantee that the consumer is a coffee drinker or remotely interested in buying a coffee.
Geo-behavioral targeting and the power of precision
Unlike geo-fencing, geo-behavioral targeting provides a more holistic view. It allows marketers to target ads based on observations and analysis of time spent by consumers at certain points of interest over time. By targeting consumers based on the understanding of their psychographics, purchase intent and visit patterns over time, marketers have a much better chance to reach the right users at scale, at the right point in the funnel and drive them to a store.
One effective way to use location-based data for targeting is to create audience segments based on consumer behaviors. Looking at the Starbucks example, this means monitoring anonymous users spending at least five to 10 minutes at Starbucks every morning. These consumers are more likely willing to receive an ad than the random consumer passing through the geo-fence. Another example is targeting ads to moviegoers. If you’re a movie theater looking to attract more customers, you’ll have much better success attracting customers that spend at least 90 minutes at the movies every week than those who are simply passing by the geo-fence you’ve set up around the perimeter of your movie theater.
When it comes to location data, the key takeaway for marketers is to not treat it as a single data point. Geo-fencing tactics are useful, but only when applied alongside geo-behavioral data, which gives marketers a 360-degree view of their audience.
Antonio Tomarchio is founder and CEO of Cuebiq, a next-generation business intelligence company that helps businesses understand consumers’ offline behavior and purchase intent. Cuebiq is a spinoff of Beintoo, a mobile industry pioneer with a proven track record of identifying emerging technologies to serve the needs of marketers, the media community and investors. Antonio founded Beintoo in 2011 and served as CEO until February 2016.
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