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Real-Time Retail Personalization in the US: A Practical Guide
Learn how real-time data streaming helps retailers personalize, scale, and stay ahead of shifting demand.
Introduction
Today’s shoppers want more than just convenience; they expect personal and timely experiences. We’re surrounded by personalization every day: smartwatches remind us to move, and social apps serve content we enjoy. So, according to Epsilon and GBH Insights, it’s no surprise that 80% of U.S. adults want personalized shopping experiences.
While traditional systems gather and store customer data for later analysis, that delay can miss the moment of opportunity. Shoppers act in the moment, and to meet their expectations, brands must respond just as quickly. This is where stream processing plays a critical role.
Stream processing enables real-time personalization by analyzing data as it is created. It allows brands to deliver tailored content, product suggestions, or messages at the right time.
This blog explores how real-time personalization works, key system characteristics, how to build the right architecture, and common pitfalls to watch for.
