Retailers face challenges in managing customer experience, requiring real-time control over inventory, payment, and delivery systems. To overcome these challenges, retailers can use graph technology to personalize the online customer experience by serving relevant content based on customer desires, interests, and needs. This involves analyzing customer behavior leading up to a purchase and using that data to guide customers along a more profitable path. Graph technology allows for combining diverse data sources into a personalization engine, enabling real-time responsiveness and improving customer engagement. A case study of a global sporting goods retailer demonstrates the effectiveness of Neo4j in creating a personalized experience by unifying disparate data models and providing access to relevant data in real time. The use of Neo4j enables retailers to build recommendation engines that offer relevant suggestions to online shoppers, ultimately driving increased revenue and customer loyalty.