How Starbucks uses data and insights to win big

The company conducts over 90 million transactions a week at more than 25,000 stores worldwide — and has managed to tap into its data to make insightful decisions.
4 September 2018

Starbucks crunches a lot of numbers everyday. Source: Shutterstock.

Starbucks serves millions of customers around the world every week. However, not many notice the data that the company gathers, the sophisticated analysis it performs, and the smart intelligence it creates and uses on a daily basis.

According to data collected by students at Harvard Business School, Starbucks conducts 90 million transactions every week, at more than 25,000 stores worldwide. By 2021, it’s expected to have 37,000 stores.

The coffee shop’s mobile app has more than 17 million active users and its ‘mobile order and pay’ feature records more than 7 million transactions each month — in the US, this feature accounts for 27 percent of all transactions.

Starbucks Rewards, the company’s loyalty program has about 13 million active members, indicating strong engagement with patrons.

The loyalty program and mobile app also make it much easier for Starbucks to collect data, test new ideas, and roll out targeted data-driven initiatives.

“With our 90 million transactions a week we know a lot about what people are buying, where they’re buying, how they’re buying, and if we combine this information with other data, like weather, promotions, inventory, insights into local events, we can actually deliver better-personalized service to other customers,” said Starbucks CTO Gerri Martin-Flickinger.

Judging by the numbers, their personalization and customer engagement efforts are reaping great rewards. As of last year, 18 percent of Starbucks’ 75 million customers accounted for 36 percent of the company’s sales. That’s a huge win for the company — and represents a big opportunity if they can win over the loyalty of more customers.

However, it’s not just CX where Starbucks uses customer data to make better decisions.

According to CNBC, the company used a combination of data from several consumer research firms to complement its own data repositories in order to make a move into the grocery business.

Insights derived from that data suggested that customers liked Mango Green Iced Tea and Peachy Black Tea and unsweetened and sweetened Black Iced Coffee — which is what hit shelves when the company made a debut at the local American supermarket.

In the past, company executives have also revealed that Starbucks is using the power of data to drive its real-estate decision-making process.

Through a system called Atlas, the company links to as many external and internal APIs as possible, connecting the data with R (the programming language for statistical computing) to build cannibalization models that can determine impact to existing stores if a new store enters the area.

Finally, through a partnership with a location-analytics firm Esri, Starbucks also uses data to ‘forecast’ the economic viability of opening a new store in a particular locality based on population density, average incomes, and traffic patterns.

Given the innovative ways in which the company is using data, it seems as though competitors in the fast food and beverage business should take notice and learn something.