Credit from Dan Berthiaume
Starbucks is deploying a range of technologies with the goal of a more personalized and frictionless customer experience.
The coffee giant is partnering with Microsoft to deploy several solutions aimed at streamlining different aspects of ordering and picking up items. First, Starbucks is using reinforcement learning technology, a type of machine learning in which a system learns to make decisions in complex, unpredictable environments based upon external feedback, in its mobile app.
Within the app, customers receive tailor-made order suggestions generated via a reinforcement learning platform that is built and hosted in Microsoft Azure. The app makes personalized recommendations based on local store inventory, popular selections, weather, time of day, community preferences, and previous orders.
Now, Starbucks is looking to expand this technology to the drive-thru experience.
Because the technology does not have the individual order histories for drive-thru customers that are available for mobile app customers, it will generate relevant drive-thru recommendations based on store transaction histories and more than 400 other store-level criteria.
These recommendations will be offered proactively on a digital menu display from which customers can order. Eventually, Starbucks says customers will be able to opt-in to recommendations that are even more personalized.
Starbucks is currently testing this technology in its Tryer Center innovation hub in Seattle, with plans to roll it out soon. According to the retailer, reinforcement learning will continue to have an important role at Starbucks in many other applications going forward.
“We’re meeting our customers where they are — whether in-store, in their car or on the go through the app — using machine learning and artificial intelligence to understand and anticipate their personal preferences,” said Jon Francis, senior VP. Starbucks analytics and market research. “Machine learning also plays a role in how we think about store design, engage with our partners, optimize inventory, and create barista schedules. This capability will eventually touch all facets of how we run our business.
Starbucks is also developing a feature for its mobile app, based on Microsoft’s Azure Blockchain Service, that shows customers information about where their packaged coffee comes from, from where it was grown and what Starbucks is doing to support farmers in those locations, to where and when it was roasted, tasting notes, and more.
Each supply chain state change in a packaged coffee product is recorded to a shared, immutable, digital ledger. Eventually, customers will be able to use the Starbucks mobile app to trace the source-to-shelf supply chain movement of their Starbucks packaged coffee.
Furthermore, each Starbucks store has more than a dozen pieces of equipment that must be operational around 16 hours a day. Starbucks is deploying Microsoft Azure Sphere provide Internet of things (IoT) connectivity across this equipment.
The IoT-enabled machines collect more than a dozen data points for every order, from the type of beans used to the coffee’s temperature and water quality, generating more than five megabytes of data in an eight-hour shift. Microsoft worked with Starbucks to develop an external device called a guardian module to connect the company’s various pieces of equipment to Azure Sphere in order to securely aggregate data and proactively identify problems with the machines.
The solution will also enable Starbucks to send new coffee recipes directly to machines, which it has previously done by manually delivering the recipes to stores via thumb drive multiple times a year.
The overarching goal with Azure Sphere, according to Starbucks, is to shift from reactive maintenance to a predictive approach that heads off issues before they happen. Longer term, the company envisions leveraging Azure Sphere for additional uses such as managing inventory and ordering supplies, and will encourage suppliers of its devices to build the solution into future versions of their products.