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Square Is Collecting Coffee Shop Data And You Won&...

Square Is Collecting Coffee Shop Data And You Won’t Believe What They Found

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Square Register has become a favorite point of sale tool in cafes, and cafes in turn are a favorite of customer of Square. So much so that Square conducts a lot of their register R&D in their own secret café deep inside their mid-Market headquarters. Recently, Square pulled anonymous usage data from literally thousands of cafes around the United States in order to discover some very interesting trends about café customers. Alex Rafter of Square reached out to Sprudge to give us a look at what they found.

First: return business is a big deal. Of course, any café owner knows how important regulars are, but Rafter tells us that according to Square “one in every 20 customers at cafes and coffee shops come back to the store that same day. Over two consecutive days the number jumps to more than one in 10 (11%). And during a typical work week, 15% of customers will come back at least twice.”

There’s unfortunately no way for Square to measure if the same-day repeat customers actually left the premises—there’s probably a fair percentage of those customers that make more than one purchase during an extended stay in the cafe. But it’s interesting to know that those customers, the same-day repeat customers, are worse tippers than the one-purchase-a-day folk. Rafter told us that “those who revisit the same day tip about 20% less than single-visit customers.” So, while they may be spending more overall, they don’t tip as well during each visit.

We were interested to know as much about the data that Square collects on café business as possible. Some other interesting data points that Square collected nationwide over the month of August include:

  • 45-50% of tippable transactions receive tips.
  • Customers who visited more than once a day tipped an average of 13.6% while single-visit customers tipped an average of 17.0% for their coffee.
  • The busiest hours for cafes are between 8 a.m. and 10 a.m.
CoffeeStand

via Square.

Unfortunately the data collected did not look at whether or not regular customers, i.e. those who visit at least twice a week, tip better than non-regular customers. Square has access to an incredible amount of data from cafes, and while most of it’s not public, insights like these hint at what’s possible. One can imagine how interesting it would be to see city-specific or time-specific data on tipping, or how tipping relates to transaction frequency…the mind reels.

“The business of repeat customers affects businesses every single day,” said Alex Rafter. He says that with the huge numbers of customers coming into cafes it can be hard to detect patterns, but that analytics like what Square is showing can help cafe owners (and the simply cafe curious) see things like just “how many of their customers may return after their morning coffee for an afternoon espresso fix.”

Square and other more modern, mobile Point Of Sales systems attempt to streamline the increasingly electronic transactions happening in cafes and other service establishments. In the process, they collect a whole lot of data. Doing analytics across this treasure-trove of info can give interesting tipping and social insights like the ones Square has shared, and this being San Francisco after all, we imagine that some of these same sorts of analytics might be finding their way into premium Square product offerings in the future.

Leif Haven is a Sprudge.com staff writer based in Oakland. Read more Leif Haven on Sprudge


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