Do loyalty programs really build loyalty? The biggest challenges for brands

The B2C (Business-to-Consumer) industry is increasingly turning toward hyper-personalization. Why? According to Deloitte's report "Connecting with meaning," customers now expect companies not only to meet their needs but also to anticipate and even get ahead of them. Businesses that fulfill these requirements guarantee long-term relationships and consumer loyalty, resulting in competitive advantage and sales success.

Loyalty programs are one of the marketing tools that can enable this. However, in the era of artificial intelligence, they should function differently than they did just a few years ago. Simply collecting points is no longer enough to effectively engage and retain customers.

Hyper-personalization is a term used across all aspects of marketing today. What is it? It refers to advanced real-time customization of communication, offers, or experiences to individual customer needs. This is most often possible through the use of advanced artificial intelligence (AI) technologies. Increasingly, there’s talk about using AI-based hyper-personalization not only in the context of broadly understood customer service but also loyalty programs. By integrating CRM systems with AI (which allows for collecting and analyzing huge amounts of customer data), these programs are reaching a completely new level.

The Loyalty Management Market will grow rapidly—from $11.71 billion in 2024 to $41.21 billion in 2032 (with a CAGR of 15.2%).

Better an outdated tool, or none at all?

Modern loyalty programs with extensive personalization (usually based on AI) offer customers rewards and offers that genuinely interest them. That’s not all—thanks to analyzing vast amounts of data and predicting behaviors, customers also receive experiences and messages better tailored to their expectations. Why all this? Understanding the customer creates emotional engagement with the brand and long-term relationships, which is just a step away from increased sales. According to McKinsey, companies effectively implementing personalization of shopping experiences can generate up to 40% higher revenues than their competitors². Outdated loyalty programs, on the other hand, are the proverbial „nail in the coffin” for businesses in 2025.

As a Gartner study showed, brands risk losing as much as 38 percent of their existing customer base due to poor personalization efforts³. So is it better not to implement any solution in this area than to choose one that doesn’t keep up with current trends? Giving up on building consumer loyalty isn’t the best idea—especially in light of market forecasts that clearly indicate that companies’ interest in building closer relationships with customers will grow (see above). It’s best to rely on companies like RITS—implementing modern IT tools that will be optimally adapted to both business capabilities and real customer needs. Too little personalization in a loyalty program won’t benefit the company, while too much can be perceived by consumers—especially Millennials⁴—as intrusive or even stalking…

9 out of 10 companies plan to modernize their loyalty programs by 2027

Source: Antavo Global Customer Loyalty Report 2024⁵

Customers aren’t loyal to brands, only to benefits—how to change loyalty strategy to work long-term?

Classic loyalty programs are becoming obsolete at a fairly rapid pace. They’re being replaced by value-based loyalty strategies—focusing on providing customers with unique experiences and benefits tailored to their needs. These go far beyond traditional—identical for each customer—discounts and universal promotions. Companies that want to stay current and not lose customers to businesses that understand the needs of modern consumers should reorganize their approach to loyalty systems.

How? Primarily by focusing on personalization, thanks to which the loyalty program will dynamically respond to the individual needs of a specific customer and present offers tailored to them. How to do this? The answer is loyalty programs that integrate CRM systems with analytical tools, which enables continuous monitoring of purchasing history and recipient preferences and allows for proactive communication adaptation. Thanks to this, the customer doesn’t feel encouraged to make purchases only through lower prices but sees real value in the relationship with the brand, which translates into long-term loyalty.

What specifically should companies that care about such effects do?

  • Eliminate unprofitable programs – remove elements that reduce margins.
  • Focus on experiences – invest in experiences that build relationships.
  • Utilize loyal customers – support them as brand ambassadors.
  • Adapt the program to younger consumers – consider the needs of millennials and Generation Alpha.
  • Monitor customer behaviors – observe actual actions and adjust strategy accordingly.
 

Features of a modern loyalty program:

  • Segmentation based on behavioral data so that each customer group receives personalized offers.
  • An iterative approach enabling regular testing of new solutions, measuring their effectiveness, and making improvements based on this.
  • Use of advanced AI technologies that enable predicting consumer needs.

Reward personalization trend—how is AI changing the approach to loyalty and customer segmentation?

The use of artificial intelligence in loyalty programs is not just a trendy slogan or marketing hype. Thanks to AI technologies such as predictive AI, machine learning, natural language processing, and graph neural networks, loyalty systems are currently undergoing a real revolution. As Deloitte research⁶ proves, artificial intelligence algorithms present in modern solutions in this field not only collect and analyze customer data but also understand the nuances of human behavior, e.g., they capture hidden patterns, emotional triggers, and customer preferences that they are often not even aware of. Thanks to this, they can provide:

  • personalized recommendations that take into account the purchase history and customer preferences, which increases the chances of making a purchase;
  • dynamic offers adjusted in real-time – machine learning algorithms predict which rewards will be most attractive at a given moment;
  • sentiment analysis-based segmentation – natural language processing (NLP) technologies enable monitoring of customer opinions and emotions, allowing for a quick response to their needs.

37% of loyalty programs use some form of AI, and 50% plan to use it in the future

Source: Epam and Antavo Global Customer Loyalty Report 2025⁷

Problems with classic loyalty programs—what flaws do they have and why do most companies implement them incorrectly?

Outdated loyalty models cannot meet the demands of today’s market. They are often ineffective due to lack of personalization, complicated point collection processes, poor customer engagement, or offering inappropriate rewards to customers. They simply can’t keep up with the dynamically changing expectations of modern customers. What other disadvantages do they have?

  • Lack of flexibility – standard systems based on collecting points cannot quickly respond to changes in consumer preferences. As a result, offers become outdated and unattractive.
  • Insufficient or incorrect technological integration – without connection to modern analytical tools and CRM systems, companies are unable to fully utilize the potential of customer data.
  • Inconsistent communication – customers do not receive clear and tailored information, which translates into lower engagement.
 
 

The most important success factor for loyalty programs is having the right data to measure them. Companies that effectively integrate loyalty programs with pricing strategies can achieve better financial results.

Source: McKinsey article „Members only: Delivering greater value through loyalty and pricing”⁸

Popular loyalty program models in various industries—retail, fintech, travel

Depending on the specifics of the industry, digital loyalty programs take different forms. In the retail sector, models based on immediate benefits such as cashback, discounts, or exclusive offers dominate. Personalization of offers in this case can positively translate into increasing the frequency of purchases and increasing the value of a specific customer’s basket. In finance, loyalty programs based on transaction data analysis and integration with banking ecosystems are increasingly being used. In the tourism industry, loyalty programs dominate that offer points for flight reservations, hotel stays, or car rentals, which can be exchanged for rewards such as free tickets or service upgrades. There is a noticeable increase in interest in loyalty programs combining gamification, exclusive offers, and multi-channel communication. Dynamically adapting offers to the changing needs of travelers is crucial for maintaining loyalty.

Want to build a loyalty program that actually builds loyalty? Choose experienced specialists who will analyze the needs of your company and customers and select the optimal solution. Contact RITS Digital – with us, you will fully utilize technology to capitalize on customer data.

Interesują Cię najlepsze narzędzia Marketing Automation? Skontaktuj się z nami. W RITS wiemy na ten temat wszystko!

Znajdziemy system optymalnie dopasowany do potrzeb i możliwości Twojej firmy, przeprowadzimy niezbędne testy i sprawą implementację, integrując narzędzie MA z działającymi już systemami.

Aleksander Zamoyski, New Business Account Manager w RITS Professional Services, chętnie podzieli się swoją wiedzą: a.zamoyski@rits.center. Bądźmy w kontakcie!

Warsaw, February 17, 2025 RITS PRESS OFFICE

More news