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Loyalty Through Personalization: AI-Powered Retail Lessons from Ulta Beauty’s 95% Customer Retention Success

Ulta Beauty is emerging as a leader in using AI-driven personalization to deliver meaningful, tailored customer experiences at scale. By centralising its once-fragmented data and leveraging machine learning technologies, the beauty retailer has achieved an impressive 95% repeat customer rate, optimised its marketing efforts, and carved out a scalable model for long-term growth.

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Ulta Beauty

In a fast-evolving retail landscape where consumer expectations are at an all-time high, Ulta Beauty is emerging as a leader in using AI-driven personalization to deliver meaningful, tailored customer experiences at scale. By centralizing its once-fragmented data and leveraging machine learning technologies, the beauty retailer has achieved an impressive 95% repeat customer rate, optimized its marketing efforts, and carved out a scalable model for long-term growth.

From Fragmented Data to Unified Intelligence

Ulta Beauty’s journey toward advanced personalization began with a common challenge: its vast troves of first-party customer data — collected from emails, loyalty programs, online interactions, and in-store purchases — were siloed and underutilized. While the company had long succeeded in blending prestige and mass-market cosmetics, effectively understanding and acting on customer preferences across channels was a different matter.

“We had an enormous amount of valuable data, but it wasn’t organized or connected in a way that enabled fast, actionable decisions,” explained Kelly Mahoney, Chief Marketing Officer at Ulta Beauty.

To change that, Ulta partnered with analytics firm SAS to centralize its data and build unified customer profiles, drawing on transactions, behaviors, and preferences across channels. This foundation enabled Ulta to deploy AI and machine learning models that not only predict customer behavior but also generate real-time personalized messagestailored to individual shoppers.

Inside Ulta’s Personalization Strategy: A Step-by-Step Approach

Ulta’s transformation into a personalization powerhouse wasn’t an overnight success. The company took a structured, phased approach to implementation, ensuring both scalability and cross-functional alignment. Here’s how Ulta built its personalization engine:

Step 1: Consolidating First-Party Data

Ulta began by pulling together data from its various sources: point-of-sale systems, loyalty program interactions, website visits, mobile app activity, email engagement, and social media behavior. This step was critical to building a 360-degree view of each customer.

Step 2: Building a Unified Customer Profile

With centralized data in place, Ulta used data stitching techniques to map customer identities across platforms. This involved matching loyalty numbers, email addresses, and behavior patterns to create singular, persistent profiles that could be tracked and updated dynamically.

Step 3: Deploying Predictive AI Models

Next, Ulta implemented advanced machine learning and AI algorithms to analyze customer behavior and predict future actions — such as likely purchases, preferred product categories, or timing of the next visit. These insights powered the decision-making logic behind personalized messages and offers.

Step 4: Automating Campaign Activation

Using AI, Ulta connected customer insights to automated marketing platforms that deliver hyper-personalized content across email, SMS, mobile app, social media, and even print. Campaigns adapt in near-real-time based on a customer’s actions or inactions.

Step 5: Measuring Performance and Iterating

Ulta rigorously tracks KPIs like engagement rates, conversion, revenue per message, and repeat purchases. Continuous A/B testing and performance analytics allow marketers to refine messages, timing, and channels for maximum effectiveness.

Step 6: Scaling Across the Organization

Finally, Ulta embedded its personalization strategy into broader business processes — from merchandising to loyalty to in-store operations. This ensures that personalization is not a marketing tactic, but a company-wide capability that supports strategic growth.

“As a high-growth company, our member base increases substantially year over year,” said Melissa Berscheid, Senior Director of Member Marketing and Technology. “We needed a platform that would allow us to keep up and still market efficiently.”

Real-Time Marketing, Real Results

With this new system, Ulta’s marketing can adapt almost instantaneously. For example, if a customer browses skincare products online, they may receive a personalized email or app notification featuring relevant recommendations or promotions — often within minutes. These AI-driven campaigns are also continuously optimized based on customer engagement and performance metrics.

“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.”

The impact has been profound: 95% of Ulta customers now make repeat purchases, and the company has significantly reduced marketing costs, even for traditional channels like print.

Loyalty and Scalability: The Dual Engines of Growth

Central to Ulta’s personalization strategy is its Ulta Beauty Rewards loyalty program, which boasts over 38 million members. Every customer touchpoint — whether it’s writing a product review, clicking on a mobile app feature, or visiting a store — feeds into Ulta’s personalization engine.

This data-backed approach strengthens Ulta’s omnichannel strategy, ensuring that customer interactions across digital and physical environments are seamlessly connected.

A Broader Retail Transformation

Ulta’s success reflects a growing trend in retail, where personalized experiences are no longer a differentiator — they’re an expectation. A 2025 PYMNTS Intelligence report found that 51% of consumers want AI-driven shopping experiences, and personalized offers top the list of demands.

Retailers like Kroger and Macy’s are similarly investing in personalization to improve promotional impact and loyalty. In parallel, technologies like voice commerce, virtual try-ons, and real-time recommendation engines are rapidly reshaping customer expectations.

The Road Ahead

Ulta’s AI-powered personalization strategy positions it well for the future of retail — one defined by real-time engagement, intelligent automation, and customer-centric innovation. By investing in unified data and agile decision-making systems, Ulta is not only keeping pace with industry trends but also helping set them.

“Personalization is the key to unlocking our future success,” said Mahoney. “To do this well, we need to apply data and decisioning alongside campaign activation.”

As customer expectations grow and technologies evolve, Ulta’s personalization playbook may soon become the industry standard for how modern retail is done.

Source: GLO