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Development of a Customer-Centric Data Analytics Platform for a Telecommunications Provider

appinventiv.com

Telecommunications

Information technology

Business services

Business Challenges

The client faces challenges in leveraging its vast data assets (50+ million events from multiple sources) to enhance customer experience, improve customer retention (reduce churn), optimize customer lifetime value, and personalize product recommendations. Existing data silos and inconsistencies hinder effective data analysis and decision-making. The company requires a platform to transform customer data into actionable insights for a customer-centric approach.

About the Client

A major telecommunications company offering voice, data, IP, fixed voice, wireless broadband, data transmission, leased lines, mobile telecommunications, cable television, and broadcasting services.

Project Objectives

Develop a centralized data analytics platform to eliminate data silos and improve data quality.
Enable comprehensive customer segmentation and profiling based on historical and current data.
Implement predictive analytics models to forecast customer churn and estimate customer lifetime value.
Provide personalized product and content recommendations to enhance customer engagement.
Improve data accessibility for all relevant departments within the organization.

Functional Requirements

Data ingestion and ETL processes from diverse data sources.
Data cleansing, transformation, and quality management.
Customer segmentation and profiling capabilities.
Churn prediction models.
Customer lifetime value (CLTV) estimation.
Personalized recommendation engine.
Interactive dashboards and reporting tools.
Real-time data analysis capabilities.

Preferred Technologies

Amazon Web Services (AWS)

Hadoop

Spark

Tensorflow

Required Integrations

CRM systems (e.g., Salesforce)
Billing systems
Marketing automation platforms
Data warehouses

Non-Functional Requirements

Scalability to handle large volumes of data (90+ million customers).
High performance for real-time data processing and analysis.
Data security and compliance (e.g., GDPR).
Reliability and availability.
Data quality and consistency.

Expected Business Impact

Successful implementation of this platform is expected to result in improved customer retention (reduced churn), increased customer lifetime value, enhanced customer satisfaction, and optimized marketing campaigns. The platform will enable data-driven decision-making across the organization, leading to improved operational efficiency and revenue growth. The project aims to transform the client into a truly customer-centric enterprise.