Using analytics to make holiday sales more effective

Thanksgiving, and the day before it, are two of the busiest days for the Rutherford, Nj.-based vegan bakeshop Sweet Avenue.

On a normal day, the family-owned bakery draws 30 to 40 customers — on Thanksgiving, it can be hundreds. Owner Jake Vance said he always has to produce more goods during the holidays, but often ends up making too much or too little.


Gina Porto, employee at Carnivore BBQ, runs a payment through Square. (Mohana Ravindranath/The Washington Post)

Square is one of a handful of mobile payment systems offering sales data to small businesses — others include Square competitor LevelUp.

Vance started using Square in his shop in mid-2011. Since then, he’s been using a combination of Square’s data and the Microsoft Excel spreadsheets he said he’d been manually compiling before he used Square.

For example, Square’s analytics for the past year confirmed that keeping his business open past noon on Thanksgiving wasn’t worth the minimal traffic he’d get during those hours. This year, he’s decided to only operate the bakery from 8 to 12 p.m. on Thanksgiving, and will hire extra help.

He has also adjusted the bakery’s selection to fit what’s most popular. “We’re able to see which of our flavors are most popular, as opposed to anecdotally. We got rid of the specialty decorated ones, and brought in the specialty flavored ones like pecan pie and carrot cake,” he said.

Vance found certain flavors sell out in the same ratio — for example, pumpkin pie and carrot cake might be more likely than two other flavors to sell out at the same time. When he scales up inventory, he’s sure to maintain ratios he’s noticed over the past few years.

Sweet Avenue has also switched to a smaller coffee pot and it keeps it on a warmer in the afternoon instead of constantly brewing new pots, Vance said. He found customers were primarily buying coffee between 8 a.m. and 1 p.m., so they needed a much smaller amount of coffee than he’d thought.

Small changes like this are particularly important “when you’re a small shop like us,” Vance said, estimating that using these detailed analytics have helped help waste 30 percent less of his inventory.

While he noted he was already collecting this kind of data before using Square, Vance said systems like Square’s, which log sales data automatically with each card transaction, save him the trouble of manually entering information and performing statistical analyses himself.

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