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The Future of Loyalty in the Data Era

The Future of Loyalty in the Data Era

Increasingly sophisticated and personalized customer experiences, guided by data-driven decision models and predictive trends. This is how loyalty processes are changing with the integration of AI in customer management.

Despite the availability of increasingly advanced tools to interpret and anticipate customer data more effectively, consumer loyalty to brands is decreasing in the digital era and becoming less exclusive.

According to Twilio's "The Relationship Economy 2023" survey, in an increasingly competitive and crowded market, consumers are attracted to an average of 4.75 brands of the same product. But the most alarming statistic is that four out of five consumers (81%) admit to abandoning a brand due to poor reliability (44%), inadequate communication (34%), or excessive insistence (28%).


Although price remains an important factor in purchasing decisions (for 31% of respondents) and consumers show interest in multiple brands due to the diversification of access channels, an ineffective customer experience drives customers away. They demand transparency (44%) and reliability (41%). In particular, consumers complain about over-targeted advertisements, inconsistent prices (39%), excessive (35%) or non-personalized (34%) communication, which deeply undermines their relationships with brands. In addition to difficulty in focusing on the consumer, there is a lack of balance between too much and too little communication in retention strategies.

In this new scenario, companies must embrace the concept of an "open relationship" with the consumer, adopt a more proactive approach to building engagement, and adapt their loyalty strategies to meet changing consumer expectations. The tools to rebuild an exclusive and lasting relationship between brand and customer, in the era of artificial intelligence, are at hand.

Personalization and transparency at the center of the customer experience

A recent Deloitte study conducted on over 3,000 consumers in the United States clearly shows that loyalty programs are still a valuable ally for retention. However, they must be able to provide an accessible, enjoyable experience, personalized rewards, and exclusive services.

The Deloitte survey reveals that consumers increasingly desire tailored experiences, guided by the personal information they choose to share. More than half (53%) of the surveyed consumers state that they would be willing to share personal information in exchange for services and rewards tailored to their needs.


The survey results indicate that consumers are more willing to share their data when companies offer highly personalized experiences and rewards that provide flexibility of choice. Furthermore, the research suggests that companies should "focus on optimizing the available data to develop the personalized experiences that consumers demand" while continuing to build consumer trust "through responsible data usage."

How artificial intelligence is changing loyalty marketing

Personalization on a large scale has become the watchword in loyalty marketing. In the data era, traditional loyalty programs with a "one-size-fits-all" approach have given way to increasingly individual and personalized experiences. At the heart of this transformation are artificial intelligence (AI) and machine learning, technologies that are reshaping consumer expectations and company loyalty strategies.

The integration of AI into Customer Relationship Management (CRM), in particular, promises to enrich the customer experience and give a real boost to loyalty programs. But how? The potential of artificial intelligence allows for the creation of decision models and predictive trends based on data, improving and optimizing the decision-making process. It makes certain operations more effective and automates others, such as lead scoring or next best action.

According to Forrester Research analysis, the benefits of integrating AI into Business Intelligence (BI) are primarily threefold:

  • 1 .Personalization and segmentation
    Integrating predictive AI into CRM's propensity modeling and analysis tools allows for optimized targeting of offers and campaigns, identifying the most suitable segment for a specific offer or the customer most likely to consider specific actions. Thanks to its ability to better understand customers, anticipate their needs, and respond to their demands, the integration of AI into CRM enables the adaptation of loyalty rewards to each customer's preferences based on behavioral patterns. Lastly, through churn prediction, it provides crucial support in predicting which customers are at risk of churn and developing personalized retention initiatives.
  • 2 .Simplification of communication management
    Conversational artificial intelligence enables personalized interactions based on understanding user preferences and history, creating a more engaging, realistic, and satisfying customer experience. Compared to traditional systems, AI improves the system's ability to predict the evolution of the contextual scenario and provide targeted responses. The real-time information processing capability of conversational systems allows for faster and more relevant responses compared to traditional chatbots limited by static scripts. Conversational AI not only automates routine processes but also offers immediate support as close as possible to the consumer, effectively guiding them through the customer journey.
  • 3 .Fraud identification
    Artificial intelligence tools are proving particularly effective in fraud detection processes related to loyalty programs. Thanks to their ability to analyze large volumes of data, identify patterns, and adapt to evolving trends, they represent a significantly more advanced solution compared to static models. Predictive analysis with artificial intelligence tools allows for the detection of more complex and difficult-to-spot fraud patterns. It can also use machine learning to adapt and learn to identify new fraud patterns as they evolve.

But generative artificial intelligence (GenAI) is also starting to be used to enhance retention capabilities through applications such as dynamically generating content and contextual offers in real-time during the purchasing journey, proactive communication, and improving search performance. For example, in 2023, Instacart launched a ChatGPT plugin called Ask Instacart, which allows consumers to receive creative recommendations, such as suggestions and recipes, in response to questions asked in natural language.

By processing and analyzing data more effectively with the help of AI, systems can formulate new strategies, personalize marketing activities, and refine product and service offerings more effectively than in the past. And, of course, they can ensure advanced personalization of content, offers, and interactions that significantly increase consumer engagement and satisfaction.


In the data era, customer management is increasingly focused on identifying and retaining individual customers, with particular attention to loyalty programs and CRM approaches enhanced by AI interaction. Leading companies like Alibaba, Expedia, and Target, as well as traditional sectors like department stores, are experiencing significant growth thanks to their focus on loyalty programs and increasing average order value, supported by new technologies.

However, to effectively retain a consumer who is becoming less "monogamous" towards brands, companies must leverage the opportunities offered by artificial intelligence to develop targeted, meaningful, and engaging engagement. The key will be to leverage data and insights to create increasingly personalized experiences across every channel, touchpoint, and interaction, through messages and content that are specific and relevant to the individual customer's needs and preferences, ultimately leading to loyalty.

AI-based CRMs can play a crucial role in providing more efficient, effective, and scalable engagement, but it is important not to overlook the emotional aspect of interactions with consumers. The adoption of an advanced CRM remains essential for effectively managing data and personalizing communications across different channels, while maintaining a high level of engagement and customer satisfaction.

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