article18.04.20245 minutes

Loyalty: What if AI was the Key to a Personalized Experience?


    If your loyalty app isn't hitting its targets or generating the desired engagement, advances in artificial intelligence in terms of personalization could be a good solution to further retain your customer base. Whether you want to integrate customization thresholds or predictive offers, let's start from the beginning.

    Personalization tools are generally used to:

    • Make more relevant targeted offers: Customers are solicited from all sides by brands, and quickly showing them offers or tempting products helps capture their attention

    • Strengthen customer relationships: This is a way for the brand to demonstrate that it is paying attention to its customer’s needs and knows their preferences.

    • Shorten decision-making time: When successful, personalization demonstrates the right offer to the right customer at the right time. The customer hardly has to make any effort to obtain the desired products or services.

    It goes without saying that the potential of artificial intelligence (AI) is making giant strides in creating standout digital experiences, whether through virtual assistants that provide immediate responses, tailored content recommendations, or image recognition captured with your camera. For a loyalty application where every interaction counts, AI can propel personalization technologies that transcend traditional engagement methods. "The power of artificial intelligence lies in its ability to filter vast amounts of data from multiple touchpoints, creating recommendations that are not only relevant but incredibly timely," explains Josh Rochefort, UX Designer at nventive.

    Imagine being able to understand the needs of your customers so well that you can anticipate them even before they express them! The goal is to create a harmonious journey where customers feel valued and understood, establishing a solid trust bond that transforms single transactions into lasting relationships.


    However, Josh Rochefort reminds us of this cautionary note to keep in mind: "The line is thin between personalization that delights and one that can seem intrusive. Crossing this limit can have the opposite effect and cool customers rather than bringing them closer." The aim, then, is to find the right balance where personalization enhances the customer experience without compromising their comfort or trust.

    So, how can artificial intelligence concretely improve your loyalty program?

    More than personalized rewards

    Personalization certainly plays a role in crafting offers, but we should also recognize its significant impact on the rewards aspect. The days when traditional loyalty programs could settle for generic offers are gone. Moving from generic to personalized by wisely exploiting accessible data is a leap towards deepening engagement directly, ensuring that even if an offer is not spent, it still generates a sense of understanding and appreciation among users.

    The advent of artificial intelligence goes even further in personalization, as observed in the PayPal CashPass program, which reaches a level of personalization previously unimaginable. PayPal uses AI to structure and examine merchant transaction data worldwide, which amounts to nearly half a billion dollars. Thanks to this program, PayPal can recruit merchant partners based on the power of their personalization engine, thus providing added value to program members. This precision transforms each interaction into an opportunity to meet and anticipate user needs, creating a loyalty experience that is both intimate and intuitive.

    Understanding personalized thresholds

    Gamifying the loyalty experience by showing a score with targets to reach or offering bonus points for a limited time creates opportunities to multiply interactions with the program. But combining gamification techniques with personalization innovates at another level. The concept of personalized thresholds comes into play, further refining personalization for the user. An offer is relevant only if the user is able to take advantage of it. By learning customer habits and behaviors, it is possible to personalize an offer's threshold. Loyalty programs can offer membership levels based on member engagement.

    «To get offers, what is required for one user versus another can be completely different. For example, if it's not in my habits to go to the store, it shouldn't be part of my requirements to reach another level, it's too strict a blocker. But if I enjoy completing the weekly challenges that are proposed to me, the number of challenges to succeed could increase to encourage me to come back more often. The idea is to keep me engaged as long as possible.»

    — David Hamel, Vice President of Strategy, CX, and Design

    Thus, the level of engagement required to move up a level could be adjusted according to the buyer's profile, or the pricing and discounts granted to a user could vary based on their spending limits.

    Grocery loyalty programs are well known for using this technique on their mobile apps. By identifying shopping habits, groceries can offer personalized discounts on regularly purchased products, allowing the customer to add them to their cart sooner and maximize their purchases with a brand.

    Understanding personalized thresholds is like mastering the art of conversation—you need to know when to speak, what to say, and when to listen. Then, by inviting AI into the conversation, you succeed in refining them even more. By adapting strategies to individual behaviors and preferences, loyalty programs transform simple transactions into meaningful interactions, reimagining potential at every touchpoint. This adaptability opens up new opportunities for engagement, from gamification that makes the experience fun and interactive to anticipated offers that land just when the user needs them, encouraging a desired action.

    Introducing predictive offers

    It's all about good timing. Like personalized thresholds, predictive offers are based on a nuanced understanding of customer behaviors and can rely on artificial intelligence to not only aim well but also anticipate the ideal moment for each offer. This strategic foresight ensures that each recommendation meets the immediate and future needs of the customer.


    For example, consider how Hilton cleverly tailors its promotions for its Hilton Honors members. By analyzing both the habits and physical location of their customers within the hotel, Hilton creates personalized promotions for its various services with impressive relevance and timing.

    nventive's approach

    The possibilities for improvements based on artificial intelligence in loyalty programs go well beyond predictive offers and personalized rewards. Imagine offering your customers interfaces that adapt to each user's preferences, chatbots that provide instant personalized customer service, and generative AI that creates content so tailored it gives the user the impression it was written just for them. These innovations represent the next frontier of loyalty programs.

    However, the question arises: does your loyalty program really need all these options offered by artificial intelligence, from personalized thresholds to tailor-made content?

    Everything that artificial intelligence can promise must be studied with caution. After all, according to Harvard Business, an astonishing 80% of AI projects do not meet their objectives, often due to a gap between the technology implemented and the real problems it aims to solve.

    The allure of artificial intelligence can be tempting, but the risk is adopting advanced solutions without a clear alignment with your business needs or the expectations of your customers. Our tailor-made approach carefully assesses your reality and aligns it with our technological choices for your digital experience, particularly for the integration of AI features. This is what allows us to guarantee a loyalty application that concretely improves the customer experience and represents a real solution to your business challenges.