Through its loyal and rewards program, Starbucks could gather a huge amount of data, which it then used to its advantage to drive more sales from existing customers. With its 30,000 plus stores globally, it rakes in above 100 million transactions each week. Jon Francis, Starbucks’ Senior Vice President of enterprise analytics, data science, research data, and analytics, along with his team of data scientists, set out to improve business performance by using data collected through its mobile apps which have over 17M members. There are three areas where the company was able to improvise using the data it collected.
Personalization of customer experiences as well as promotions
The launch of the Starbucks rewards program via the mobile app led to a massive upswing. It could get their recorded data and using it they could tap into what their customers think and how they behave. They could analyze the customers’ purchase patterns too. With the app, Starbucks could find which coffee their customers get, from which locations and at what times of the day or the week. They even used a cloud-based artificial intelligence engine, Digital flywheel program, which is a recommendation system. So when a customer visits a new Starbucks location, the store identifies the customer through their phone and gives the Starbucks person making their coffee in the preferred or most repeated order of that customer. On the basis of their past behaviour i.e. the purchase history, Starbucks could now even suggest newly launched products this customer would like. Additionally unique rewards and discounts could be offered too. Going a step ahead, Starbucks even collects data on a customer’s ordering behaviour vis-a-vis the weather. Offering a discount to a customer on a hot chocolate on a rainy day is how they offer highly personalized experiences.
Introducing new products
Starbucks keeps launching new products every now and then. Now it uses its collected data to decide what kind of products should be offered. A good example of this is when offering their product out of grocery stores, they knew that 43% of customers skip sugar in tea. So they introduced unsweetened iced tea to drive sales. Similarly if data shows people like decaf coffee they would introduce a product keeping that in mind.
Location is everything from a retail PoV. Starbucks uses location-based analytics powered by Atlas, a mapping and business intelligence tool developed by Esri, to arrive at the most strategic locations for its new stores. From getting to know the customer demographics i.e. spending power, income, population, etc., Starbucks decides where to open their stores for maxim profitability.