This understanding that consumers buy both high-end and mass brands in cosmetics has propelled the U.S. retailer’s growth. It boasts more than 38 million loyalty program members, over 1,300 U.S. stores in every state and seven million Instagram fans.
Ulta also offers customers an in-store credit card program and extends promotional offers through its email and text message lists, along with other marketing programs.
In doing so, Ulta has amassed first-party data directly from customers, not purchased through marketing lists or other sources.
But the data posed a challenge for the retailer. The information was scattered, difficult to access and tap quickly for use in marketing campaigns, according to a blog post from its partner SAS.
“Personalization is the key to unlocking our future success, and to do this well means we need to apply data and decisioning alongside campaign activation,” said Ulta Beauty CMO Kelly Mahoney.
Ulta began by centralizing its data — such as from emails, loyalty programs, in-store and other silos — in a single environment. It stitched the data together to build unified customer profiles by looking at preferences and transactions across different channels.
Ulta deployed advanced artificial intelligence (AI) and machine learning 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.
“We’re able to leverage analytics and our campaign activation-to-decision messages that reach our guests in almost real-time,” Mahoney said.
This new capability helps Ulta build stronger relationships and drive growth. The retailer said that nearly all its customers come back.
95% Repeat Customer Rate
This personalization has led to 95% of customers repurchasing products at Ulta, according to 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.
The ability to act on that data almost instantly is a competitive advantage, especially in a category where consumer preferences shift rapidly.
“We’re able to reach guests in almost real-time,” Mahoney said. “That’s the difference between a generic message and one that feels like it was created just for you.”
With an expanding customer base, scalability is critical. “As a high-growth company, our member base increases substantially year over year,” said Melissa Berscheid, senior director of member marketing and technology for Ulta. “We needed a platform that would allow us to keep up and still market efficiently.”
Ulta’s approach illustrates a broader retail trend: personalized, automated experiences powered by analytics are no longer optional — they’re foundational.
Receiving personalized offers is the top demand of consumers for AI-powered shopping experiences, according to a PYMNTS Intelligence report, “Getting to Know You: How AI Is Shaping the Future of Shopping.” What’s more, 51% of consumers want some kind of AI-powered shopping experience.
Retailers are investing to meet this demand. For example, grocery giant Kroger said personalizing deals results in more effective promotions, while Macy’s uses relevant targeted offers to improve customer experiences.
Other innovative technologies include voice commerce and virtual try-ons. These advancements offer consumers more tailored and interactive journeys while transforming retail.
The PYMNTS report found that innovations such as personalization and customization not only enhance shopping experiences but also offer merchants opportunities to deepen shopper loyalty.
As such, the report said that retail’s future is poised to become increasingly targeted and tech-driven.
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