Google has announced that they will soon roll out a tool for advertisers that uses credit and debit card usage data from stores to obtain insight into the purchasing habits of people who see its ads. The new tool is aimed at bringing physical sales that maybe derived from online ads into the limelight in order to more accurately gauge the effectiveness of online ad campaigns. Google did not announce exactly when advertisers could expect the tool to roll out, except by saying “in the coming months”, which could very well mean before the end of this year. It will go hand in hand with a tool that debuted in 2014 and allows advertisers to track store traffic and look for trends based on advertising campaigns.
According to the press release in which it announced the upcoming tool, Google announced a few other tools for advertisers. One of the more potentially impactful of the bunch is the debut of In Market Audiences for Search advertising, allowing advertisers to reach more customers whose searches match their products and services. Google Attribution, another new tool, is less directly impactful, but allows advertisers to see all their different advertising and sales portals together. This allows them to juxtapose trends in a more holistic fashion to seek out their best campaigns and methods, and allows for more complete demographic and analytics research. The whole thing is made possible by a wider data set than ever before, alongside advanced machine learning tools, which Google has recently put some work into optimizing for this very purpose.
Google’s new tool set may raise some eyebrows in the privacy community due to its insistence on bringing analytics into the physical world. Checking into variables like how many visits a store gets or how much of a product sells is, after all, quite different from figuring out who is doing all that visiting and buying, and whether those people have seen Google’s advertisers’ campaigns. Still, data is aggregated and semi-anonymized, like most data that Google gathers, so those who don’t have a problem with its current methods likely won’t see much wrong with these new tools.