Scandinavian Airlines loyalty program EuroBonus and American Express issue co-brand payment cards, a loyalty solution enabling EuroBonus members to earn points on everyday spending outside airline transactions. The loyalty solution is a popular feature among active members. However, the customer lifecycle needed constant monitoring. Customers are all people driven by their desires and unique behaviors. Together with the American Express Customer retention team, we have developed a data-driven initiative to identify such behaviors and re-engage at-risk customers early in their journey.
Photo by Nicolas Nezzo on Unsplash
Objective:
- create a series of targeted retention activities based on predictive analytics
- enable early identification of customers likely to churn
- implement tailored communication strategies to retain them
Mixed Methods:
- Customer survey indicating the most common reasons to end the Payment Card plan (American Express)
- Computational predictive analytics of Scandinavian Airlines EuroBonus transactional data sources
The churn prediction model was developed using the most essential signals identified with Decision Tree modeling. We used synthesized behavioral flags as early indicators, which predicted churn up to 6 months in advance. We employed MS SQL to analyze customer transactions, Azure Machine Learning for model training, and Adobe Campaign for executing retention campaigns.
Interestingly, the upcoming yearly service fee was a major driver behind the churn decision.
Outcomes:
- Early identification of at-risk customers enabled timely campaign interventions
- Enhanced customer lifetime value through personalized engagement
- The project established a scalable framework for using predictive analytics to tailor individual experiences based on their needs.
