Bringing Generative AI to Loyalty Programs

With artificial intelligence advancing by leaps and bounds, brands need to be fully aware of how it can take their guest engagement practices to the next level.

Fundamentally, AI utilizes machine learning algorithms for predictive modeling and pattern recognition. Although artificial intelligence and machine learning are not exactly one in the same, both aim to enhance decision-making processes, drive technological innovation through automation, and optimize operations through data-driven insights.

Loyalty programs have been leveraging the data science side of artificial intelligence for a while now. For the most part, this has meant using machine learning algorithms for predictive modeling and pattern recognition. Good examples include using AI and customer data to predict future behavior for things like 1-to-1 visits or 1-to-1 win-back campaigns.

Leveraging Gen AI

With the advent of ChatGPT, however, loyalty has moved on to the generative and response sides of AI. Platforms that are incorporating AI assistants are helping loyalty experts access their data faster in a more conversational way. Where before they may have manually pulled data for a report, now they can ask questions, such as, “how many marketable members does my program have?” or “how did my last campaign perform?”

Furthermore, AI is making it easier for marketers to optimize their loyalty platform’s capabilities. Instead of becoming entrenched in analyzing data to find insights, AI users can take full advantage of every capability at their disposal. Integrated AI can show them how to use tools that segment data intelligently or to see which campaigns had the highest retention rate. Or, it might simply help someone who has forgotten how to set up a push or pull message to quickly find that information in the product’s support documents. 

Generative AI has the potential to be a campaign game changer for loyalty professionals, it can blend analytics, run queries on data based on questions for things like redemptions and spend. It can also take best practices from its data set and craft a campaign from scratch. 

With its ability to create many original ideas, generative AI shouldn’t be taken at face value. Rather, it can be amended, adjusted and personalized to meet a brand’s specific needs. It enables people to ask questions so that they can analyze how things went, determine the best next steps and establish brand specific best practices. 

When integrated into a guest engagement platform, generative AI saves time and frustration. It’s ability to access and query data helps brands drive more value from their data. This is how savvy loyalty pros are using it to make their programs better.

Measurement 

Just as we’ve all become accustomed to asking Siri for information, AI eliminates the need for loyalty managers to click around looking for material. It streamlines the process by enabling  the user to simply ask for metrics, such as message open or offer redemption rates. 

Product Support 

By automating responses to the most frequent user questions, AI makes it easier for loyalty managers to get help. An AI assistant can access and read all of a brand’s help articles, then quickly get back to users with answers. It can deliver faster access to the top 20% of questions or give detailed, easy-to-follow directions on something like setting up a text message. At the same time, it frees us the loyalty provider’s support team to focus on more crucial issues.

Guest Support  

An AI assistant can also be deployed to speed up responses to customer feedback. A good example is using the generative capabilities to write email responses to guest questions and reviews. 

Ease of Use

With a more streamlined user interface, AI makes it possible to run more effective campaigns, see what worked in the past, and choose account filters for an easier and faster experience.

While an AI assistant can help run queries, it doesn’t replace human expertise. People will always win when it comes to providing the strategy and analytics necessary to customize campaigns to a specific brand. AI also has yet to transform mobile apps. However, that could change as apps collect and share more data into centralized customer databases. At that point, we may see AI innovations coming to our phones, too.

About the Author

Aubrey Giasson is a Product Manager at Paytronix, a leader in guest engagement for restaurants and convenience stores.