Google's in-store traffic predictor

Counting people inside the store is a service that could be very powerful — if done with shoppers and merchants in mind

woolworths closing down sale
Credit: David Wright, CC BY-SA 2.0, via Wikimedia Commons

In its ongoing effort to become a force for good for its brick-and-mortar retail clients, Google has rolled out a traffic prediction element within its search. The feature appears to leverage POS data — for those retail advertisers willing to share — so that Google visitors can see the times when that retailer is typically the most busy.

From Google's standpoint, this has lots of advantages. First, that data allows it to try and sell more effective ads to those merchants, pushing ads to go out during typically slow parts of the day. Secondly, the data each merchant shares with Google tells it far more about the business than the business might intend. Feeding Google's insatiable data desires is always a plus — for Google.

For shoppers, the service has a nice benefit, in that it gives a hint as to the best times to visit a new merchant. Right there, that's a win-win for the shopper and the merchant. The shopper would ideally get faster service, and the merchant would have more customers during slower times of the day. Put another way, if you're paying for Google to push you more customers, you'd rather it not happen when your store associates are already overwhelmed with long lines.

As nice as this service is, it's not as powerful as it could be. If the store in question is a favorite of mine, I likely already know when it's the most busy and the most slow. (To Google's presumed point, if I'm already a regular customer, I'm not a good target for Google ads.) A nice touch would be to add digital customer-counters.

How is that better than historical POS data? First, counters measure everyone in the store, not just those making purchases. I know of several popular local merchants that are often crowded with people who won't make a purchase today. From a shopper's perspective, a crowded store is a crowded store. From a selfish perspective, those other people are in my way whether or not they buy something.

More importantly, historical patterns are not always precisely accurate in making predictions. Special sales, good/bad weather, parades, vacations and lots of other factors cause deviations from the norm. If the functionality showed the true current crowding, that's far more valuable than a historical guess. Far better would be an option that said, "Do you want to be texted or emailed when the crowding drops below x number of people?"

That would provide far better service to shoppers and to merchants — as well as making Google an even more critical part of the retail process.

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