Swipely's new release includes menu, service intelligence

If you knew for a fact that the fish tacos brought in more repeat customers than any other menu item, wouldn't you try to market them more?

And if George sells more alcohol than any other server, wouldn't you ask him to share his upselling secrets to everyone on staff?

The buzz-y "Big Data" has a lot of applications in the restaurant space, and it's what Swipely is trying to capture with today's new release, "Winter '14."

Winter '14 extends Swipely's cloud-based service to include menu and server performance intelligence and help restaurants "make smarter decisions about their key drivers — food, staff and marketing," according to CEO Angus Davis.

Davis said Swipely added the new features because there is a lot of interest in Big Data, but most of the company's customers are small business owners who don't have a lot of time to crunch or interpret all of that information.

"We're trying to give them insight into what's most profitable or likely to drive repeat customers, or how their servers are doing. They're interested in these insights so they can use them to grow," he said.

How it works

The system supports many market-leading POS systems and the data is stored every time a customer pays using a credit or debit card (estimated to be 70 to 80 percent of the time, Davis said).

Most restaurants are already paying for the ability to accept these types of payments, and Davis said Swipely has reduced the cost of accessing payments.

"What we do is include, essentially, the ability to accept transactions for free if they have our product," he said. "Our product has a certain price point and we eliminate the markup that merchants are paying for."

Data categories

Once that payment information is processed, the Swipely system breaks down data categories for operators to gauge, including, for example:

  • What entrees are most likely to create a repeat customer;
  • What do customers say online about this dish (according to Davis, 40 percent of online reviews mention a specific dish);
  • What is my best customer's favorite glass of wine;
  • Which server has the most success selling the dessert;
  • Who are my top servers measured by sales, customer retention and table turn;
  • Why does Jane excel during lunch sales, but not during the dinner daypart; and
  • Who does the best job turning a first-time customer into a repeat customer.

For the server information, Davis said operators can use that information for training or for decision making. If Andrew, for example, does a good job of selling desserts, other servers who don't can shadow him.

"Being able to use server performance is valuable in many ways — to train, to hold them accountable. Or, if you are thinking about making a change to your fish taco and you want to run it by someone on your team, you can now see which servers sell more fish tacos than other servers, so they can be your go-to for that information," he said.

Also, by seeing which dishes sell more than others, operators can make better marketing decisions.

"You're used to seeing what your best sellers are, but you may not know what's most likely to drive a repeat customer. We give them a screen of which menu items are doing the best job of driving customers to come back," Davis said. "We've found examples of menu items that aren't necessarily popular but that drive high retention rates, and operators should try to push those more."

Restaurants benefit from Big Data

Customers who pay with cash will not have their data stored in the platform. But, Davis said privacy should not be a concern for customers because restaurants are required to collect the information for three years. It's just now being used to organize specific insights.

"Every time I use a credit card, that information is stored for three years anyway. Why wouldn't we turn that into something you can use to provide better customer service?" Davis said.

Davis also offered his take on the Big Data trend, and how it will progress. During its first 10 years, the Internet was used to take stuff that worked offline and move it online, he said. The current trend is that ecommerce is moving ahead of traditional retailers.

"Zappos can sell shoes that, offline, it couldn't before. And they're using Big Data to do that," he said.

Next up, he predicts, will be a convergence between online marketing and in-store operations. For example, in-store operations data tells you that fish tacos are an important dish to feature, and one that should be marketed.

Restaurants should especially benefit from the move toward Big Data because it evens the playing field.

"They've been behind because of lack of time or technology or capital," Davis said. "That's the opportunity we see — to provide ecommerce technology using data and put it into the hands of everyday, local merchants in a way that is easy to use, affordable and doesn't take a huge amount of time. People didn't open a restaurant to be using technology all day, they did it to provide the best food and service."

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