As loyalty programs become ubiquitous, brands need to find technologies that help their programs stand out to consumers. While generative AI (genAI) is still relatively new, predictive AI (also known as AI and machine learning) has been used to support and improve loyalty strategies and programs for decades. Predictive AI algorithms recognize and learn from patterns in data and can then be used to perform complex tasks without marketer input.

You’ll find predictive AI used in loyalty in three primary categories:

  1. Propensity analysis. Marketers can hone offer and campaign targeting by understanding how likely it is that a particular customer or segment will accept an offer such as a refer-a-friend. This analysis can also help deliver personalized rewards based on customer preferences and behavior patterns. For example, a consumer who buys size-1T clothes could be targeted with a communication about size-2T clothes after a defined period of time, or consumers may receive automated communications reminding them that they are only 50 points away from rising to the next tier, along with a personalized offer to earn those points.
  2. Proactive insights for marketers. Predictive AI can analyze customer behaviors and prod the marketer to consider certain actions. Examples include adding or removing a loyalty tier, decreasing the number of points needed for a specific reward, or modifying a specific campaign because the customer uptake is different from what was expected.
  3. Fraud identification and mitigation. Brands don’t talk much about loyalty fraud, but it is becoming a significant problem. Loyalty programs defend against hackers that try to steal points, and AI can help identify consumers trying to game the system to receive more rewards than they deserve. But loyalty fraud is actually greatest among employees of a brand who give loyalty rewards to customers, friends, and themselves when they haven’t been earned. Predictive AI tracks behavior patterns and can identify the fraud. It can also automatically halt redemptions when a specified criteria is reached.

GenAI is beginning to be used in loyalty for capabilities leveraged across marketing, including dynamic content generation, contextual offers during real-time customer journeys, improving search in apps, and anticipatory communications. Last year, Instacart debuted a ChatGPT plug-in called Ask Instacart that enables consumers to ask natural language questions such as “What’s the best seasoning for steak?” and get creative answers and recommendations. And brands such as Amazon are making customers’ experiences easier by using genAI to summarize customer reviews. On a personal note, I recently received a video from my bank summarizing the benefits that I earned by being a rewards program member over the past year, with dynamic elements that were generated just for me.

Learn more about how AI can improve your loyalty program.

I will be hosting a panel of loyalty industry experts and executives managing brand loyalty programs at Forrester’s CX Summit North America in Nashville (and as a digital experience) this June 17–20. Join us to explore how these brands are using AI to engender deeper loyalty. You will hear about:

  • How AI is being used in loyalty analytics to better understand customers.
  • Examples of AI use in loyalty initiatives today.
  • Where AI can take loyalty in the next five years.

I will also be available for one-to-one meetings throughout the event to answer your questions and discuss consumer loyalty. Hope to see you there!