Case Study: Serving a large and strategically significant area in the Middle East, this major telecom operator connects millions of individuals and businesses through a network that spans over 2,000 locations. Known for its prepaid mobile services and high-speed internet options, the company's relentless focus on customer satisfaction and technological innovation has made it a respected name in the region, fostering strong relationships with its extensive customer base. The need for this transformative project emanated from the operator's pursuit to delve deeper into its vast prepaid consumer landscape. The current customer analytics assets were not adequately capturing the multifaceted nature of customer behaviors, preferences, and potential churn triggers. Faced with the challenge of stagnant traditional methods, the company aimed to enhance its ability to forecast customer movements, personalize interactions, and employ near-real-time indicators. This ambition drove the creation of a more responsive, actionable, and customer-centric approach, heralding a new stage in telecom customer management.

The project kicked off with a detailed examination of the existing customer data and the establishment of a comprehensive data mart after handling data quality-related issues. The team then helped the operator clarify critical definitions such as 'churn' based on previous experiences and global best practices. This groundwork led to the creation of a comprehensive subscriber profile that served as a rich foundation for analytical modeling. Once the data was ready, the team introduced nine different micro-segmentation models, dissecting value, behavior, and demographics with more granular views such as usage time, payment methods, and product subscriptions. Unique micro-segment profiles provided a comprehensive summary view of essential features. For churn prediction, near-real-time indicators like dropped calls and critical complaints were incorporated, enhancing performance beyond traditional methods. Multidimensional profiles of churners were established, improving understanding and allowing for more targeted responses to at-risk customer groups.

Automated data scripts, models, scoring, and health check codes were developed for ease of ongoing maintenance and future revisions. Final deliverables included complete documentation in a standardized way, along with SAS macros to provide end-to-end scoring and performance measurement processes for all models. The revamp of the operator's customer analytics function has set a new standard for understanding and engaging prepaid mobile consumers. The company has taken a pioneering step towards targeted engagement and efficient customer management. This approach transcends traditional methods, equipping the operator with the tools to navigate the complex telecom landscape with agility and precision.