Things Like This Make You Want to Lose Hope in Brick & Mortar

SafeGraph is a company doing some really cool things. In less than 12 months it’s been able to acquire mobile location data representing nearly 5% of US residents. That data can be used to solve an increasingly large number of problems.

One such example is what their head data scientist showed post-election: that people in the protest marches earned more money than those who celebrated the inauguration.

Not only that, but where these people shop, eat, and spend more of their time.

To me the most impressive part is not the technology: any number of companies with consumer data could do this.

It’s that SafeGraph has been able to get so much data, so fast.

To provide some perspective for that 5% figure, let’s examine our favorite punching bag topic: brick and mortar. Brick and mortar merchants are almost all run poorly by any objective metric. There are myriad opportunities for improvement, and we’ve talked about them at length previously.

Data, as we’ve argued — and shown — is the underpinnings for solutions of value. Therefore, merchants should be crawling over each other to share data with solution providers.

Talk about a fantasy…

To quote ourselves (which you can definitely do that when you’re right about the issue):

BlackBox Intelligence, started by an ex-Carlson CEO, has spent 20+ years building a data pool and has only tapped 2% of the restaurant market

The US hotel industry, for the record, managed to collect data from ~70% of operators over that same 20-year period, and it’s data that’s more granular than what BlackBox sees. I reconcile this with the observation that it takes more capital to start a hotel than a restaurant, so sophistication is thus higher.

Anyhow, Wally Doolin’s 20+ year effort has netted him half of what someone in Silicon Valley managed to get done in a year. Granted it’s not the exact same kind of data, but the scale is phenomenal. This is not a ding on Wally as much as it is an indictment of the restaurant industry, but we should get back to our question:

How did SafeGraph do it?

One could argue that SafeGraph only had to strike agreements with a small number of apps collecting this consumer behavior data. They’d reason it’s only because SafeGraph needed to pursue a small number of partners to get to 5% versus the large number of outlets you’d need to approach to reach 5% in the restaurant vertical.


I’d recommend thinking about it differently.

Any brick and mortar merchant can benefit immensely by sharing data. Yes, without getting to 5% marketshare there could be limited applications of big data insights from multiple locations, but there’s serious upside to just using your own data processed through a third party. It’s the same reason grocers have been sharing data with suppliers for 40+ years: third parties who focus on turning your data into something useful are way better than you are at figuring out what to do.

So what it really comes down to is that these small number of apps were sophisticated enough to understand the value of sharing data with SafeGraph, as it would drive considerable upside in their own businesses. DataGraph then combined data from otherwise-competitors to produce something holistically more valuable.

But the first step was being sophisticated enough to realize you had a problem.

I don’t know if merchants will ever figure it out. Maybe they’re destined to be fully replaced by ecommerce and delivery-only kitchens. When someone spends a year collecting data and gets 2x as much as someone who has spent 20+ years on the same effort, any logical person starts thinking there’s a deeper problem that won’t ever get fixed.

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