How AI-Driven Loyalty Programs Drive Better Business Outcomes
As CTO of Engage People Inc. Len Covello helps companies differentiate loyalty programs to deliver a better experience for their customers.
gettyAI enhances a loyalty program’s key features and helps guide customer decisions through an interactive experience. Customers not only see the number of points and rewards options but also get advice about how best to spend points, combine points with other deals or achieve a larger goal. They get a better experience, and the retailer sees stronger sales and conversion rates.
AI in loyalty is still emerging, but it’s growing quickly. By 2030, AI is expected to handle 80% of customer interactions. Now is the time to learn how it is transforming customer loyalty and delivering real-time value to customers and brands.
Through all of its iterations, the purpose of a loyalty program is to increase customer retention, repeat sales and build brand recognition. With AI in play, loyalty programs are evolving beyond a tool for retention. The program can define customer intent, create personalized value, provide a real-time understanding of point and reward offerings, and trigger immediate action. With these benefits, AI connects a customer’s entire value ecosystem and creates a new value layer that hasn’t previously existed in loyalty.
Traditional loyalty works through customer segmentation, and pushes tailored campaigns to those customer segments to engage with the customer. AI in loyalty can achieve a higher level of personalized customer engagement. The AI loyalty model is understand-recommend-decide-execute-learn. It is more than a conversational interface or chatbot; it provides real-time intelligence to customers and provides individualized recommendations based on their points and rewards availability. The program can suggest the best way to spend points to maximize financial value. This form of hyper-personalization encourages engagement and ultimately increases conversion rates.
With these added features, the loyalty program can serve as a customer management tool. It effectively responds to customer complaints or questions and manages returns. Research from McKinsey found that AI-powered customer experience, which includes loyalty as part of the tool kit, can increase customer satisfaction by 15% to 20% while reducing the cost to serve customers by 20% to 30%. This benefit happens when brands builds the right data foundation with integrated models, advanced analytics, decision orchestration and delivery infrastructure—not a prepackaged chatbot.
The robust list of benefits stems from a high-quality interactive system that communicates directly with customers. Some people might imagine a chatbot, but the AI programming is capable of much more than a script-driven question-and-answer tool. It is a new type of loyalty interaction model that can answer complex financial questions and provide direction.
For customers, the model will become a trusted guide that can offer thoughtful, accurate guidance about the financial value of loyalty points and how to best earn and spend points to maximize value. Customers can ask direct questions as well, to better understand their options. For example, a customer can ask for the stronger value: using points toward upcoming travel plans versus using the points to make a daily purchase, as well as how best to earn those points in specific categories to achieve that goal.
This level of flexibility is the goal of the pay-with-points system: giving customers the opportunity to utilize points when and where is best for them. Now, the AI helps customers make those decisions with their financial well-being in mind. That feature builds a deeper loyalty connection to the brand, motivates action and increases sales and conversion. McKinsey found that a specific case of AI-driven personalization at a U.S. airline led to 210% improvement in targeting at-risk customers, 800% improvement in customer satisfaction and a 59% reduction in churn.
Data collection is one of the major benefits of a loyalty program. Brands use them to track behaviors and habits, gaining feedback on campaigns. While traditional programs measure membership growth and redemptions, AI shifts this model. It analyzes specific nuances to understand customer behavior and predict outcomes.
The AI system uses more effective metrics to track these behaviors, including activity metrics and real business outcomes. The list of nuanced metrics in these categories is endless, and the AI will inherently analyze ultra-specific datasets. Some of the types of metrics on that list are the experiences that drive incremental revenue growth, the reward types that create behavior change and the reward offers that improve profitability for the brand.
Fraud protection in loyalty is vital against misuse. AI strengthens defenses by identifying unusual purchase patterns, account take-over attempts and abuse of promotions. Systems can also make recommendations to close loopholes to prevent future fraudulent activity.
Fraudulent use of a loyalty program can lead to significant losses for a brand. Between 2016 and 2017, for example, American Express faced widespread reports of customers exploiting generous introductory bonus-point offers, prompting the company to freeze accounts, claw back rewards and tighten its terms. This is exactly the type of incident that AI in loyalty can prevent by creating a real-time risk and decisioning layer that prevents bad actors from taking advantage of the program.
The future of loyalty has arrived, but it doesn’t look like more rewards or more options or more offers. AI is helping customers make better decisions in real time when spending points and extract the most value from the program. Pay-with-points has become an essential part of loyalty, and now, AI is optimizing the experience to transform loyalty into a value engine.
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