What’s in this article:
- the success of Starbucks Rewards program is due to its simplicity, transparency, and AI analysis that enables one-to-one personalization
People don’t just like drinking Starbucks coffee; they like feeling connected to the brand and reaping the rewards of that relationship. That’s what Starbucks perfected with its Rewards Membership.
Once customers create an account, customers can pay for orders how they’d like (cash, credit card, or through their app), and collect Stars from each order. As customers earn Stars, they can redeem them for Rewards such as free food, drinks, and more.
By giving customers the connection to the brand they love (as well as free treats), Starbucks has millions of Rewards members who contribute to the billions in revenue and that’s not slowing down anytime soon.
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Quarterly earnings show loyalty isn’t drying up
In July Starbucks shared its third quarter earnings for the year, establishing that their loyalty program is as lucrative as ever:
- Q3 Consolidated Net Revenues Up 78% to a Record $7.5 Billion
- Q3 Comparable Store Sales Up 73% Globally; U.S. Up 83% with 10% Two-Year Growth
- Active Starbucks® Rewards Membership in the U.S. Up 48% Year-Over-Year to 24.2 Million
From their quarter earnings, we can see that the Rewards program is a major driver of business. What makes it so successful is its ease of use and the very tangible rewards — free food and drinks — that customers earn.
But how does Starbucks keep customers subscribed to their loyalty program?
AI and personalization keep rewards worth striving for
The Rewards program incentives is one of the ways Starbucks personalizes its marketing. A reward awaits on your birthday if you’ve shared that date with the app. The app notes and remembers your favorite flavors; if you’re a fan of the seasonal pumpkin spice latte, Starbucks may reward you by telling you ahead of non-Rewards members when you can order it at your local Starbucks.
By leveraging AI within their app, Starbucks has been able to achieve true 1:1 personalized offers based on each individual customer’s behaviors and marked preferences.
Matt Ryan, Starbucks chief strategy officer, said Starbucks’ use of artificial intelligence has set them apart from competitors: “Our ecosystem of digital propositions for the customer . . . all operate together as a platform, and it’s that platform that really separates us from the rest of the retail world, which has struggled to be more than bricks and mortar. It gives us the advantage we have moving forward.”
Gerri Martin-Flickinger, Starbucks’ chief technology officer, added that tracking customer spending patterns reveals who would likely respond to offers and “try things they wouldn’t try otherwise.”
Martin-Flickinger explained that this process is completely individualized: “There are no variants; there are no predetermined algorithms around specific offers.” Instead, all promotions are “uniquely generated based on every individual customer’s behaviors and anticipated behaviors.”
Starbucks achieved personalization by automating offers down to the individual customer
In a case study with Formation, Starbucks used the platform to automate the creation, optimization and measurement of offers for each customer using the Rewards system.
That level of fine-tuning involves analyzing huge amounts of data at the granular level, and that’s exactly what Starbucks does. While larger retailers typically segment rather than truly personalize, Starbuck aspired to achieve a far greater level of customization even at scale.
According to Formation’s case study: “Starbucks created millions of offers each week across multiple offer types. Each type of offer was constructed with dynamic actions and rewards to improve certain customer behaviors including frequency, category exploration, cross-sell and upsell.”
Initial offerings were not just about incentivizing purchases but about learning what motivates the customer in general. Starbucks continued to apply machine learning to the data, considering who responded to which offer. To optimize results, the retailer employed an omnichannel strategy to reach out to members not just through the app itself but through emails and texts to get their attention.
On the back end, AI and automation rewards the company with valuable metrics it can tie into its KPIs. But from the customer’s point of view, it adds transparency that increases trust and anticipation.