Teradata > Case Studies > Improving Network Experience Analytics for a Major Telecom Operator in Pakistan

Improving Network Experience Analytics for a Major Telecom Operator in Pakistan

Technology Category

Analytics & Modeling - Predictive Analytics

Applicable Industries

Telecommunications

Applicable Functions

Sales & Marketing

Use Cases

Movement Prediction

Services

System Integration

The Challenge

The major telecom operator in Pakistan had a growing customer base but lacked expertise in deploying analytics in their network to generate actionable insights. They also faced challenges in achieving continual subscriber growth and minimizing churn attributed to poor network services. Customer feedback scores mentioned poor network experience as the key reason for churn and dissatisfaction. The marketing, sales, and network teams were using siloed decision-making using disparate data sets. There was also a lack of technical expertise to integrate, build, and manage analytical capability on a large data volume related to network experience.

The Customer

Major Telecoms Operator

About The Customer

The customer is the second largest telecom operator in Pakistan with 40.7 million active subscribers (2017), 27% data users (2017), and approximately 1.13 BN USD revenue (2016). They also host the world's third largest mobile financial services. The customer lacked expertise in deploying analytics in their network and needed help to generate actionable insights.

The Solution

Think Big Analytics was assigned to help the telecom operator address these challenges. 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. They designed analytical BI dashboards that provided insights on aggregate and individual customer levels. They also utilized a unified data architecture and provided a pioneer solution of Network Experience Analytics capability in Pakistan.

Quantitative Benefit

The engagement with Think Big Analytics resulted in an approximate 16% increase in churn prediction accuracy, an identification of approximately 8 million passive subscribers, and optimized product, sales, and network rollouts. The customer was also able to gain insights into previously undiscovered fields. However, the exact quantitative benefits in terms of revenue or cost savings are not mentioned in the case study.