Stella Artois has run a campaign aiming ads at people based on the predicted likelihood that they'll stop by a bar soon.
But the increased use of historical location data to infer consumers' drinking habits could raise some privacy questions that feel a little more visceral than when marketers decide you like donuts in the morning. And Stella is not the only advertiser recently to aim ads at people based on their fondness for imbibing.
Its ads have been targeted using data compiled by Blis, a mobile location data company that gets information through ad calls in mobile exchanges, direct partnerships with app publishers and beacon and Wi-Fi networks. The Stella campaign was handled by its agency Vizeum.
Stella ran mobile display and video ads through Blis, paying only when people exposed to the ads actually visit a pub, for around six weeks throughout the U.K. The cost-per-visit model is similar to one introduced by xAd earlier this month. Advertisers working with Blis can measure lift based on incremental visits from people exposed to ads, and can exclude devices that have been spotted in drinking establishments during a recent period of time to prevent targeting people who would probably be at the bar anyway, whether or not they received ads.
"We have a huge volume of historic location behaviors," said Greg Isbister, CEO of Blis. "We can predict when people will go to that location again in the future." The company says its Blis Futures product applies predictive analytics to anonymized location data gathered over time to identify patterns and create audience segments based on their predicted likelihood to visit a certain type of location.
For the Stella campaign, Blis predicted people were likely to visit a pub in the future if they had gone to one two or three times in the last month.
The practice of gathering location data over time to understand shopping behavior, and as a proxy for consumer interests or propensities, is not exactly new, but it seems to be gaining steam when it comes to advertisers employing this compiled historical data for ad targeting. This sort of offering reflects an evolution from mobile location data applications that simply promise to target ads to people based on where they are at the moment.
Herradura maker Brown-Forman worked with Foursquare during the 2016 holiday season to aim ads at people whose mobile devices were found near liquor stores, bars or restaurants that sell the brand, or had been at those places in the past.
The relatively new ad practices raise questions about what consumers will tolerate when it comes to companies storing locations they visited over time. While Blis does not employ individual-level data and allows advertisers only to target audience categories, the use of historically-gathered location data to paint a detailed picture based on the actual comings and goings of consumers remains somewhat novel. Credit and debit card transaction data showing consumers' actual purchase habits, however, has also been available to marketers for years.
Some people may be uncomfortable with being added to a pool of bar or pub goers, even though the data has been anonymized. If a mobile device ID were to be re-identified and traced back to an individual who is in the market for health insurance coverage or has applied for a job, for example, it might not be helpful for that person to be revealed as a member of a segment for frequent drinkers.
Mr. Isbister said that people can opt-out from the Blis ad targeting through their device ad settings, or by controlling settings for location data collection in the apps they use.
Reveal Mobile is another firm that compiles location data from various partners in order to create audience segments based on historical location data. The company's CEO Brian Handly said he's seen increased advertiser interest over the past 18 months or so in using historical location data compiled over time, though he said he has not heard any clients express concerns about potential misuses of such data to discriminate against, say, people who like to drink at bars.
"We see a lot more people [advertisers] than had been surprisingly slow just to use location data, but certainly we see a lot more people using what we call analyzed data or data compiled historically for predictive advertising and location based retargeting," said Mr. Handly.