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Ulta Beauty’s use of centralized first-party data to build unified customer profiles based on preferences and transactions across different channels and AI-driven personalized recommendations in real-time drives a 95% repurchase rate

May 29, 2025 //  by Finnovate

Ulta Beauty centralized scattered customer data to build unified profiles, by looking at preferences and transactions across different channels. Ulta deployed advanced AI and ML models to understand the customer, predict what they’re likely to do next and send them personalized recommendations. The messages can change in near real time based on new customer actions. Ulta also measures the results.  This new capability helps Ulta build stronger relationships and drive growth. The retailer said that nearly all its customers come back. This personalization has led to 95% of customers repurchasing products at Ulta, according to  CMO Kelly Mahoney. But there’s another benefit to this approach, too. Using AI for print campaigns — those aimed at magazines, for example — has reduced costs without hurting effectiveness, the retailer claimed. Ulta’s loyalty program, Ulta Beauty Rewards, is central to its data-driven personalization. Each interaction — whether it’s a product review, app click or in-store visit — feeds the retailer’s marketing engine.

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Category: Channels, Innovation Topics

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