Churn Prediction in Telecom Industry: Identifying High-Risk Customers and Key Indicators

Local Chapter Accra, Ghana Chapter

Coordinated by Ghana ,

Status: Completed

Project Duration: 05 Jun 2023 - 05 Aug 2023

Open Source resources available from this project

Project background.

The telecom industry faces significant challenges related to customer churn, where customers switch between service providers. It can cost 5-10 times more to acquire a new customer than to retain an existing one, and the telecom industry experiences an average churn rate of 15-22% per year. In Africa market, approximately 80% of revenue comes from the top 20% of customers, making it crucial to reduce churn among high-value customers. In this project, we will use customer-level data to build predictive models for identifying high-churn-risk customers and the main indicators of churn, ultimately aiming to reduce churn and retain valuable customers.

Project plan.

  • Week 1

    Problem Research and Data Collection

  • Week 2

    Exploratory Data Analysis

  • Week 3

    Feature Engineering

  • Week 4

    Model Development and Training

  • Week 5

    Feature Engineering

  • Week 6


Learning outcomes.

Data Analysis, Machine Learning, Teamwork, Problem Solving, Industrial Experience

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