Know Your Guests’ Next Move Before it Happens with Predictive Analytics

Understanding a guest’s next move before it happens would completely change a marketer’s strategy, from simply deciding who they should email to determining how rich of an offer to send to a particular segment of guests.  

Once a function of educated guessing and a bit of luck, making predictions like these is now possible through a Paytronix AI to IA feature known as Predictive Analytics.  

Predictive Analytics is a series of AI-driven models built by Paytronix data scientists that make assumptions about the behavior of guests based on their previous actions. Through analyzing the billions of historical data points we’ve collected over the last 20 years, meaningful scores have been developed.  

These scores are, in a sense, akin to a credit score. Using artificial intelligence and data collected through a brand’s loyalty program, Paytronix assigns a score to each guest based on their likelihood to doing something, like visit in the next month, or open an email. The scores are calculated through a complex analysis of each individual’s past behavior and overall patterns and trends seen across a broad population.  

While it’s as simple as clicking a button for the end-user, the AI is making a series of complex and ever-changing calculations. 

While these scores can be used on an individual basis, they’re even more powerful when used in conjunction with one another. For example, the Likelihood to Visit score determines the probability of a guest visiting in the next week or month, while the Likelihood to Open Email score determines the odds a guest will read the messages a brand is sending.  

Combine the two, and the strategy for driving visits and spend while minimizing cannibalization becomes evident:   



Looking for more ways to revolutionize your loyalty strategy with AI? Download Unlocking the Power of Data with Artificial Intelligence: Take the Guesswork Out of Marketing.


A photo of the posts author

The Author

Get links to posts like this in your inbox by signing up below.


Thank you for subscibing to our blog.

Comments are closed.