It comes in many forms: Speech. Movement. Draw within the lines. Wait, scratch that last one. We didn’t like that last one either. When it comes to measuring foot traffic, trade areas, migration patterns, demographics, cross traffic, and in general get behavioral metrics from mobile location data, yesterday’s state of the art was to get canned results on some buildings or venues someone else has decided you might be interested in.

It is everyone’s favorite game to perfectly forecast earnings by looking in the rear view mirror. We are trying really hard not to fall into the same trap ourselves. Here is why: it is very easy to make random predictions, some of which come true, and then look back and cherry-pick the ones that you were right. Really, a monkey can do it. If you give them a banana for each correct prediction they would get pretty fat, fast!

Is Gamestop’s traffic up? Is Jimmy John’s traffic growing more than Subway’s? Every day some new analysis of cellphone location data portrays to measure the exact foot traffic in one or all of these, and every day we emit a collective gasp at the incredulous claims. Let’s get this quickly out of the way: Gamestop traffic is trending down; Jimmy John is down too and that trend has not changed for 3 years straight; it’s also worse than Subway’s downward trend, except for some bright, but inconsistent, spots in 2019.

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