How do you use artificial intelligence and machine learning to improve your Loyalty Program?

To date, most of what has been promoted as AI in Loyalty is closer to machine learning. That's not a bad thing as applying more computing power to run data scans, test offers and improve algorithms will add to the effectiveness of a loyalty program. But, the promise of AI in Customer Loyalty is yet to come. We saw an announcement from Koginitiv this week which we covered in The Wise Marketer. And, Loyalty Juggernaut has AI embedded throughout its platform. There will be more but if you want to gather context of the future, have a look at these two organizations. Since we are consumers first and business people second, it is hard to resist identifying AI with generative AI. The future of AI in Customer loyalty will yield so much more.

The benefits are endless. AI & ML can significantly enhance both customer segmentation and personalization. Although it was (kind of) an automated process in the past, making an accurate decision after looking at the data was time consuming. However, AI and ML allow for more precise and dynamic grouping based on behaviors and preferences, which leads to highly tailored offers, rewards, and experiences while saving time and hassle. The process of optimizing program design and performance by identifying the most effective combinations to boost NPS, retention, and CLV is now fully automated, along with providing accurate data analysis and reports, which leads to increased efficiency.

To avoid sounding generic, I'm sharing applications of AI and ML from my own experience with our Rowad loyalty program. Using advanced clustering and classification, we segmented customers based on lifetime value and purchasing behavior, which is crucial for our soon-to-launch Rowad Tier system. This segmentation will allow us to personalize our home page, offers, and rewards based on each customer's tier. We employ A/B testing (in and off-platform) to refine program features, optimizing for customer satisfaction; it helps us identify exactly what kind of rewards are the customer looking for. We’re also planning to launch an AI-powered chatbot to enhance communication and provide instant, relevant responses within the program.

AI can play a vital role in fraud detection in loyalty programs. By meticulously analyzing extensive data sets, AI swiftly pinpoints anomalies and discerns patterns suggestive of fraudulent activities. Employing advanced behavioral analysis and real-time monitoring, AI significantly bolsters security measures, ensuring the protection of both businesses and customers.

Very useful tips here on AI/ML usage into customer engagement (loyalty, Personalisation, CX). My suggestion here, in addition to the above, would be to fully leverage vendor capabilities- most leading vendors would have market leading functionality for AI/ML already pre-packaged and tested for efficacy. It will require careful strategic planning and execution as there are quite a few difficulties in this area- but well worth the effort to realise it as the benefits can be differentiating in terms of the common metrics of customer engagement eg NPS, retention, stickiness etc.

The first step to an AI/ML effort is to make sure you have clean data. Clean data is data that is well-structured, properly tagged and regularly updated. Some people launch software and then add data analytics at the end. This won't work with an AI effort. It is garbage in, garbage out. So before investing in new functionality make sure a technical resource has confirmed that data required is clean. For instance, say you want to update your loyalty program to use AI/ML to test out perks based on geography. The idea is that it learns over time what offers work in what areas of the country. Great. But what if your customer's location data is stored on 3 different systems and often is out of sync? Not great. The results will be garbage.

So far, AI is in the marketing collateral language of many providers, but few have the substance to back up the claim. I do know of three providers that have legit incorporation of AI into their platforms and most are using it to expedite personalization efforts. One area I would like to see impacted is data protection and fraud. Loyalty data is valued by fraudsters and most LMS platforms have fraud prevention algorithms. These could be enhanced by adding in AI to drive more rapid recognition of fraudulent activity.

Be mindful of how you or your loyalty technology provider are adding AI into your strategy. The past 18 months has seen everyone “adding ChatGPT” into their products, as a way to leverage AI, but one could argue that they might not have been the best use cases to deploy.