There was a time when “location-based marketing” meant out-of-home media placements – signs, billboards, in-store displays, and so forth. Naturally, when GPS chips found their way into mobile phones and from there into everyone’s pockets and pocketbooks, “location-based” came to mean targeting specific users based on their location, as broadcast by the GPS-enabled apps on their phones. The door opened to location-based push notifications, text messages, and in-app ads on our personal screens.

This practice has generated periodic controversy, leading up to the GDPR calling out location data specifically as a definitional example of “personal data” that would be protected by the law. This meant the marketers under GDPR’s jurisdiction would need a legal basis – such as explicit consent – to use it. This, in turn, has shifted some controversy away from questions about location data’s personal status to disputes about the validity of various consent collection processes. Here, the key question seems to be, if consumers knew that an app was collecting their location data – even when they weren’t actively using it – would they knowingly consent to allow that app to sell that data to “carefully screened” data brokers

In the US, wireless carriers have recently been implicated in sales of location data to middlemen that seem to not to have been too carefully screened, which is likely to play into public calls for more regulation. Yet, location-based marketing is, if anything, heating up as marketers seek to message through the rising noise level in an environment filled with elusive, ad-avoiding consumers.

One recent study suggested that “more than 80 per cent of marketers say location-based advertising and marketing produced growth in their customer base (85 per cent), higher response rates (83 per cent), and higher customer engagement (83 per cent).” It’s become a key part of the trend toward deeper customer knowledge and personalisation, provides clearly measurable lift, and is also seen as a hedge against the growing data power of Google, Facebook, and Amazon. And many consumers enjoy the convenience of geotargeted offers. So higher levels of adoption look like a sure bet.

Mainstream location data providers are generally sensitive to privacy, in the sense that they require their app network partners to seek opt-ins (even if their clarity may be disputable), and most of the data they pass on to marketers is aggregated and anonymised so that it’s no longer personally identifiable. However, some research casts doubt on the efficacy of these anonymisation procedures, and, in any case, the sheer scale of location data collection seems to make abuse and leakage inevitable.

Unlike other forms of personal data, such as email addresses or cookie-IDs, continuous tracking of location data is truly a form of surveillance. It renders a person physically accessible and reveals all kinds of data about them that they probably never considered they were revealing.

So, as the pressure mounts on both sides of the location data fault line, the risks to marketers of being caught in some sort of tectonic event is rising steadily. Cautious marketers are looking for ways to reap the benefits of location-based relevance while avoiding the risks of association with dubious data collection. This leads us back to the old out-of-home concept of using location-based displays rather than phones as the primary vectors of engagement (with the user option to move the engagement to the phone if interested). Yes, you guessed it: digital out-of-home is due for a comeback (DOOH!).

DOOH has struggled over the years with measurement problems, lack of scale, lack of standards, and so forth, but technology is starting to boost its appeal. For one thing, 5G is coming and that will make sign-based experiences more dynamic. And programmatic markets will make inventory more accessible at scale. But what’s most exciting to me about the medium is the notion that AI – and computer vision specifically – has the potential to replace targeting based on personal data with something based on recognising signs of interest and contextual conditions (like weather) that can contribute to relevance.

If you’re like me when you read AI you probably thought of Minority Report’s creepy personalised signage trope (except today we know that we don’t need retinal scans to recognise people – facial recognition will do just fine)…and I believe these concerns are valid. But marketers who wish to avoid dystopian creepiness may take solace in the idea that personal recognition may not be the key to starting a productive brand dialog. Sometimes it might just take some information about the situation, an ability to spot an opening, a well-timed opening line and some creative empathy.

  • This article is reprinted from the Gartner Blog Network with permission. 
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