AI-Powered Loyalty Platforms Bring New CX Opportunities

Data and artificial intelligence are crucial for effective customer loyalty programs. They are also revolutionizing the role of traditional CRM platforms.

Initially, CRM systems changed business interaction with customers. Energizing this process with AI-powered data feeds gave marketers a new way to enhance customer engagement and retention.

However, while similar in function, customer loyalty platforms serve a slightly different purpose and can work together with CRM systems to enhance results. This synergy benefits both businesses and their customers. Data-driven AI features give CRM platforms the ability to elevate customer experience (CX) to the next level.

According to Nikolaus Kimla, CEO and co-founder at Pipeliner CRM, CRM platforms traditionally focus on tracking and managing customer relationships and analyzing data to improve the sales process. On the other hand, customer loyalty platforms are designed to capture and analyze customer data to enhance the customer loyalty experience and identify ways to reward and retain customers better.

“While the two share similar goals — maintaining positive customer feedback and driving additional sales revenue — CRMs focus more on managing the relationship, whereas loyalty programs focus on customer relationship maintenance,” he told CRM Buyer.

The two are not necessarily mutually exclusive, he added. Data and AI use in CRM is primarily beneficial for predicting customer behaviors, optimizing the customer communications experience, and forecasting potential upsell opportunities.

Ulta Beauty Loyalty Strategy

When the two related systems come together, CRM platforms provide a direct channel to gather customer insights and feedback. They are a vital aspect of the customer feedback loop.

“With the data CRMs can help gather, businesses can better understand customer preferences, pain points, and expectations to shape loyalty programs and highlight areas for improvement,” Kimla said.

Jonathan Moran, head of martech solutions marketing at data and AI provider SAS, noted that the Ulta Beauty Rewards program is a vivid example of the two concepts coming together.

Ulta Beauty is the largest beauty retailer in the U.S., with more than 1,300 stores and locations in all 50 states. Over the past several years, Ulta Beauty has reimagined customer experiences and personalized marketing campaigns with a focus on its Ulta Beauty Rewards (formerly Ultamate Rewards) loyalty program.

More than 40 million members benefit from targeted recommendations powered by data and AI from SAS. Using predictive models to optimize campaigns has decreased Ulta Beauty’s marketing costs without reducing marketing effectiveness.

According to Kelly Mahoney, Ulta Beauty’s VP of Customer and Growth Marketing, personalization is the key to unlocking the company’s future success.

“To do this well means applying data and decisions alongside campaign activation. Today, we can leverage analytics and our campaign activation-to-decision messages that reach our guests in almost real-time,” she told CRM Buyer.

Automating and personalizing its marketing efforts has helped Ulta Beauty achieve an impressive 95% sales penetration, meaning 95% of sales come from returning guests, demonstrating high customer loyalty.

In Ulta Beauty Rewards, customers earn one point for every dollar spent on qualifying purchases in-store and online. As they spend more, they advance to higher tiers and unlock greater rewards. Customers redeem points for discounts on future purchases, explained Moran.

Personalized, Flexible Experiences

The goal of loyalty programs is to increase customer retention by offering added value through discounts, special promotions, and exclusive access. CRM programs can help manage customer data, provide clear communication on program rules, and deliver personalized, channel-based offers that enhance the value customers perceive.

“As with Ulta Beauty, CRM technology powered by data and AI can help an organization hyper-personalize messages and offer members of its loyalty program, increasing customer engagement and satisfaction,” offered Moran.

As loyalty programs have become more digital — specifically mobile — he sees an increase in flexibility, point-redemption methods, and gamification in loyalty mobile apps.

“This shift reflects a larger trend toward more personalized, flexible, and integrated customer experiences. These are driven by better technology and increasing customer expectations,” he added.

Overcoming Challenges in AI-Driven Loyalty Programs

Moran explained that while data and AI play a critical role in CRM platforms, they typically do not include built-in loyalty-management features. In contrast, dedicated customer loyalty platforms have these capabilities preconfigured for use across various industries.

Common challenges in loyalty programs include complex rules, confusion, lack of perceived value, limited flexibility, concerns about data privacy, and poor customer experience. AI capabilities can address these issues through A/B testing, multivariate testing (MVT), and ongoing program improvements.

“Loyalty programs that include unstructured data components such as free text and voice input can leverage AI-based text and sentiment analysis to uncover customer insights from this [CRM] data,” Moran said.

Challenges exist when implementing AI-driven loyalty tools for CRM platforms. Their severity depends on the loyalty-management provider used.

Moran says the most significant hurdles include integrating AI tools into loyalty management stacks. Custom work is often required if prebuilt connections and integrations are not present. Another obstacle is ensuring data governance and compliance across a variety of solutions.

“Loyalty data often contains personally identifiable information (PII). If exposed, this can be very damaging for brands and their most valuable customers,” Moran warned.

AI’s Power and Limitations

Kimla asserted that AI is a vital tool for analyzing CRM data and recognizing valuable insights. Not only is it faster than humans when evaluating data, but it is also more effective at identifying patterns regarding customer preferences and feedback.

“Businesses can then use this customer data to create personalized and dynamic loyalty programs with tailored activities and rewards that resonate,” he said.

Also, AI can help identify at-risk customers, opening the door for early, targeted interventions that can help course correct before their loyalty and business are lost.

“AI-driven loyalty programs are only as good as the data they are built on. As the adage goes, ‘Garbage in, garbage out,'” Kimla said.

If the AI draws conclusions based on damaged, missing, or inaccurate data, it may not provide an experience that accurately represents customer interests and feedback.