Google Shows Offline Analytics Capabilities With Holiday Store Traffic Data
Like so many others, Google is putting out holiday shopping data this week. I’m sitting on 40 or more studies and surveys that discuss who’s going to show up (or not show up) in stores this Black Friday weekend. But what’s most interesting about Google’s data is not so much the data itself but the […]
Like so many others, Google is putting out holiday shopping data this week. I’m sitting on 40 or more studies and surveys that discuss who’s going to show up (or not show up) in stores this Black Friday weekend.
But what’s most interesting about Google’s data is not so much the data itself but the capability that it reflects. This is the first time that Google is revealing offline analytics. Google’s report on foot traffic during the holiday season represents aggregated data from mobile users with location history turned on.
In the form of a “store foot traffic index,” Google reveals that holiday shopping traffic patterns are different for different categories of stores. Some have greater visitation on Black Friday and some on the Saturday before Christmas.
Another interesting insight is that on Black Friday itself, crowds peak in the afternoon.
Google has started using some of this same foot-traffic data to show when local places are busiest. For example, the following screenshot from the Knowledge Graph shows historical foot traffic data for New York’s Gramercy Tavern.
As I’ve written many times before, the industry is migrating from measuring abstract metrics such as clicks and impressions to “metrics that matter.” These local analytics will soon be essential to show marketers (that sell offline) the true ROI of their ad spending — connecting the dots between online (but especially mobile ad exposures) and offline actions.
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