Ever have an idea for a new product so good it could hurt your business?
It may seem far-fetched, but that’s what happened to Wawa, the popular convenience store chain that operates more than 750 locations in six East Coast states.
The company had introduced a new flatbread breakfast sandwich. Everybody in the company was excited about it. Sales were taking off and it looked like a clear winner. Then Wawa killed the flatbread.
Because it was too good. It sold so well that it undercut products Wawa had already been selling. Specifically, it was cannibalizing sales from other, higher-margin Wawa products. More flatbread sales ultimately meant less money for the company. So it had to go.
The company behind Wawa’s flatbread decision was Applied Predictive Technologies. APT’s software takes in information from client companies — everything from sales data to local weather patterns — and produces custom reports to understand trends, improve efficiency and hit sales targets.
“In using big data and an understanding of trends, it was valuable to see not just the primary effects but also the secondary,” Anthony Bruce, chief executive at APT, told CNBC. “What you need to do is find observations where what you’ve done is having halo effects, not cannibalization effects.”
That’s how APT’s data-driven platform helped Wawa: It wasn’t just showing what the flatbreads generated in sales, but how it affected the overall bottom line for the company. Data analytics, when applied correctly, can help filter out the “noise” from test results. Starbucks‘ global strategy officer cited APT as the “best source of industry comp intelligence” on a recent company earnings call.
APT is also the company behind McDonald’s recent move to sell breakfast foods all day. The fast-food giant renewed its contract with APT in 2016 to gear up new food offerings and optimize menus. APT’s “Test & Learn” software costs about $1 million per year for a typical three-year license.
See a full interview of APT’s Anthony Bruce by CNBC’s Eric Chemi here:
“APT’s software helped us understand that ‘All Day Breakfast’ generated incremental business by attracting new customers and leading to larger check sizes for existing customers,” said Kristy Cunningham, senior vice president at McDonald’s. “This initiative was a primary driver of growth in our most recent quarter.”
“About 40 percent of ideas just fall flat and there’s no recovery,” APT’s Bruce said. But that doesn’t mean that the remaining 60 percent work outright. It’s a matter of tweaking and honing experiments — that’s the human element — to uncover what’s working and what’s not working.
These hidden effects also work in the opposite direction. Another of APT’s convenience store clients wanted to experiment with installing drinks coolers in their retail locations so customers could buy cold beverages to go, Bruce said. Trouble is, coolers require a lot of overhead in the form of maintenance and electricity.
A simple look at the data suggested the coolers weren’t really driving that much business. But a more detailed analysis showed that they were actually helping the stores overall: Customers came in more often and that created a halo effect where they bought other products as well.
Bruce co-founded APT in 1999. Before that, he worked as a consultant for McKinsey and an investment banker for Morgan Stanley. He got an MBA from Stanford and graduated magna cum laude from Yale in Math and Economics.
It’s Bruce’s data- and bottom-line based thinking that helps APT’s clients endlessly experiment with various possibilities. In 2015, MasterCard bought APT, opening the door for an even bigger dataset to work with and new client-specific approaches.
Source: Tech CNBC
The man helping companies like Wawa and McDonald's make winning decisions using big data