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Analytics & Modeling - Predictive Analytics
Sales & Marketing
The second largest telecom operator in Pakistan, with 40.7 million active subscribers, 27% data users and approximately 1.13 BN USD revenue, was facing challenges in maintaining its customer base and minimizing churn attributed to poor network services. Customer feedback indicated that poor network experience was the key reason for churn and dissatisfaction. The marketing, sales, and network teams were making decisions in silos, using disparate data sets. The company lacked the technical expertise to integrate, build, and manage analytical capability on large data volumes related to network experience. They needed help in deploying analytics in their network to generate actionable insights.
The customer is the second largest telecom operator in Pakistan, boasting a large customer base of 40.7 million active subscribers, 27% of whom are data users. The company generates approximately 1.13 BN USD in revenue and hosts the world’s third largest mobile financial services. Despite its size and success, the company was struggling with customer retention due to poor network services. The company lacked the in-house expertise to deploy analytics in their network to generate actionable insights and improve their services.
Major Telecoms Operator
Think Big Analytics was brought in to address these challenges due to their reputation for deploying advanced analytics and dealing with complex use cases. They delivered the capability to perform analytics on 14+ Key Network Quality Indicators, and 50+ medium & 300+ highly detailed ones consistently across various business situations. This was achieved through specially designed analytical BI dashboards delivering insights on aggregate and individual customer levels, major data use-case delivery, and the utilization of Unified Data Architecture. This pioneering solution of Network Experience Analytics capability was the first of its kind in Pakistan.
The engagement with Think Big Analytics resulted in several operational improvements for the telecom operator. The company was able to gain insights into previously undiscovered fields, revealing a customer base of passive users. This enabled the company to increase churn prediction accuracy, improve complaint handling efficiency, and optimize marketing and sales planning as well as product rollouts. The solution also enabled channel marketing and resulted in increased complaint accuracy, decreased complaints, and efficient Turnaround Times (TATs). Overall, the solution significantly improved the company's network experience analytics capability.