Ireckonu research makes hospitality breakthrough

AI that can pinpoint the exact moment a guest will disengage

New research by Ireckonu has uncovered a breakthrough in hospitality churn management, allowing hotels to act at the precise moment a guest is about to disengage.

The study, led by Dr Rik van Leeuwen, Ireckonu’s Head of Data Solutions and Customer Success, concludes that when a guest reaches a 75% churn risk, sending a 20% discount email can significantly increase the likelihood of rebooking.

This finding comes from a multi-week study conducted in collaboration with a major North American hotel chain, and it marks a major step forward in data-driven guest retention.

AI not only identifies guests at risk of leaving, but it also optimises when and how to intervene - maximising the return on retention efforts.

This new framework, which combines the BG/NBD model for churn probability with reinforcement learning for proactive engagement, is tailored specifically to the hospitality sector.

The BG/NBD model predicts customer behaviour by estimating how likely they are to make repeat purchases over time in non-subscription settings.

Unlike traditional “black box” models, Dr. van Leeuwen’s approach emphasises interpretability and adaptability, making it both transparent and actionable for hotel operations.

His PhD research, titled Data-Driven Strategies in Hospitality, explores how predictive and prescriptive AI models can be adapted to real business contexts, prioritising transparency and applicability.

It underscores the importance of white box approaches in building trust and usability within hotel operations.

“This is not just about predicting customer behaviour - it’s about turning that prediction into timely, effective action,” said Dr van Leeuwen. “Knowing who is at risk is no longer enough. The real value lies in knowing when to act and how to respond. That’s where AI can truly transform hospitality strategy”.

The implications of the study go beyond a single use case. Ireckonu is actively working to integrate these insights into its broader middleware and customer data platform offerings, helping hotel groups operationalise AI models that are proven to work in real-world settings.

“Rik’s research brings scientific validation to something hotels have long struggled with guest loyalty,” said Jan Jaap van Roon, CEO of Ireckonu. “This isn’t theory—it’s tested, actionable insight. And it’s a perfect example of the kind of innovation we champion at Ireckonu.”

The study also opens the door to future enhancements, such as adjusting dynamic pricing levels based on individual churn risk, incorporating qualitative feedback like sentiment analysis, and expanding the model to industries where customer relationships rely on frequent, non-contractual interactions.

By investing in both cutting-edge research and practical application, Ireckonu reaffirms its commitment to helping hotels deliver smarter, more personalised guest experiences - powered by clean guest data.