Brewing Loyalty with AI: Starbucks` AI-Powered Rewards Program Redefining Personalization
| Case Code: MKTG482 Case Length: 7 Pages Period: 2010-2025 Pub Date: 2025 Teaching Note: Available |
Price: Rs.400 Organization : Starbucks Corporation Industry : Food & Beverage Countries : United States Themes: Digital Marketing, Artificial Intelligence, Digital Strategy |

Abstract
Case Intro 1
Case Intro 2
Excerpts
Abstract
US-based coffeehouse chain Starbucks used artificial intelligence (AI) to create one of the most sophisticated customer loyalty ecosystems in the world. It used the customer data collected through its loyalty program, the Starbucks Rewards Program, to improve customer engagement through predictive analytics, gamification, and personalized marketing.
The case traces the digital journey of Starbucks from its loyalty program and its mobile payment app to the creation of its proprietary AI engine, Deep Brew. It highlights how the company used machine learning to customize and personalize offers, and behavioral data to predict what consumers would order.
However, the increased use of technology came with its own drawbacks in the form of digital overreach and growing concerns about privacy.
Issues
The case is structured to achieve the following teaching objectives:
- Understand the use of AI to bring about hyper-personalization.
- Analyze how gamification and behavioral targeting enhance customer lifetime value
- Explore how Starbucks integrates technology seamlessly into a physical retail environment
- Evaluate how a balance can be achieved between data privacy, personalization, and customer trust.
Contents
The AI Barista That Knew Your Order Before You Did
Background Note
Deep Brew: How It Was Built & What It Did
Results of Embracing AI
Risks & Ethical Dilemmas
The Future of Starbucks’ AI Strategy
Exhibits
Keywords
Starbucks; Deep Brew; AI: digital journey; data; behavioral data; customer data; loyalty program; hyper-personalization; gamification; behavioral targeting; customer lifetime value; data privacy; customer trust; personalization; Customer Lifetime value; RACE model; AI Personalization Framework
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