CallCore

This dataset collection represents these interconnected telecommunications business operations, allowing learners to analyze realistic customer and financial data commonly used by mobile operators, broadband providers, internet service providers, cable television companies, and telecommunications enterprises.

What\'s Included

• Customer Churn Data
• Revenue Performance
• Service Quality Surveys
• Customer Satisfaction Metrics
• Customer Segmentation
• Customer Retention Analytics

Learning Objectives

After working with this dataset you will be able to:

• Analyze customer churn across service types
• Identify major drivers of customer attrition
• Evaluate revenue performance across customer segments
• Calculate and analyze Average Revenue Per User (ARPU)
• Measure customer satisfaction and service quality
• Build executive telecommunications dashboards
• Support customer retention strategies using data
• Segment customers based on profitability and behavior
• Develop telecommunications business intelligence reports

Skills You\'ll Practice

• SQL
• Python
• Pandas
• Excel
• Data Cleaning
• Exploratory Data Analysis (EDA)
• Customer Analytics
• Revenue Analytics
• Business Intelligence
• Power BI
• Tableau

Business Questions

• Which customer segments experience the highest churn rates?
• What are the most common reasons customers leave?
• Which telecom services generate the highest revenue?
• How does contract type influence customer retention?
• Which customer segments produce the highest ARPU?
• How do satisfaction scores relate to churn behavior?
• Does technical support quality influence customer loyalty?
• Which service improvements could reduce churn?
• Which customer segments provide the greatest long-term profitability?
• Which insights support customer retention and revenue growth strategies?

Suggested Portfolio Projects

• Customer Churn Dashboard
• Telecommunications Revenue Dashboard
• Customer Satisfaction Analytics
• Customer Retention Dashboard
• ARPU Performance Dashboard
• Telecom Customer Segmentation
• Customer Experience Intelligence Report
• Telecommunications Business Analytics Project

Difficulty

Intermediate

Recommended for learners interested in telecommunications, customer analytics, marketing analytics, customer success, revenue management, and business intelligence.

Industry

• Telecommunications
• Internet Service Providers
• Mobile Networks
• Customer Experience
• Revenue Management
• Business Intelligence

Recommended Tools

• Excel
• SQL
• Python
• Pandas
• Power BI
• Tableau
• Jupyter Notebook

Dataset Highlights

• 3 integrated telecommunications datasets
• 3,000 total records
• Excel and CSV formats included
• Customer churn records, revenue metrics, customer satisfaction surveys, technical support ratings, and customer segmentation
• Covers customer acquisition, retention, revenue optimization, and service quality within a unified telecommunications analytics collection
• Ideal for churn prediction, retention dashboards, customer experience analysis, revenue reporting, telecommunications KPIs, and portfolio projects