

We were able to execute highly targeted marketing campaigns powered by predictive models built on InfiniteInsight® ![]()
Pradeep Kumar
GM, Customer Analytics
XL Doubles Marketing Campaign Take-Up Rate with InfiniteInsight®
Challenges
- PT XL Axiata (XL), one of the biggest telecommunications services operators in Indonesia with over 40 million subscribers, was grappling with a competitive market that is approaching saturation and has seen a reduction in rates to their lowest levels in years
- Nearly all of XL’s customers are in pre-paid programs as opposed to longer-term contracts, making switching costs to a competitive carrier low
- Customer retention and loyalty are major challenges
Solutions
- Standardized on InfiniteInsight® after examining other vendors because of its rapid deployment, ease of use, and the agility it contributed to marketing operations
- Instead of using traditional reactive retention and loyalty management strategies, XL took the initiative to target customers using predictive analytics
- The XL analytics team created predictive models to analyze subscriber characteristics such as product propensity and churn propensity from records of its over 40 million subscribers
- Using InfiniteInsight®, XL proactively identifies and targets customers that are at risk to churn, long before the actual damage occurs
- The models were tested and revised and the predictive scores were deployed directly in-database to XL’s data warehouse
- By building propensity models for various products and offers, XL has been able to match customer eligibility, inventory availability and profitability to prioritize which offer to present
Results
- Doubled the marketing campaign take-up rate with InfiniteInsight®
- Leveraging predictive analytics, XL is now able to deliver next best actions to its customers – delivering the right offer to the right customer at the right time
- Optimized campaigns for retention, cross-sell and up-sell across multiple marketing channels using predictive scores
- Company gains the agility to build and deploy predictive models in days

