Telecom Customer Churn Analysis using Python Overview: In this assessment, students will analyse a Telecom Customer Churn dataset using basic Python programming concepts. The objective is

Business Analysis and Programming (ICT917)

Assessment -2 brief

Telecom Customer Churn Analysis using Python

Overview: In this assessment, students will analyse a Telecom Customer Churn dataset using basic Python programming concepts. The objective is to apply simple programming techniques to solve a real-world business problem and provide managerial insights.

Students are expected to demonstrate:

• Understanding of Python basics
• Ability to perform input/output operations
• Basic data processing using loops and dictionaries
• Simple data visualization
• Strong business interpretation and strategic recommendations

Business Scenario:

A telecom company is experiencing increasing customer churn. Management wants to understand:

• What is the overall churn rate?
• Which contract types show higher churn?
• What is the revenue impact of churn?
• What strategic actions can reduce churn?

Students must analyse the provided dataset and generate insights to support managerial decision-making.

Dataset: Telco Customer Churn downloaded from Kaggle is available on Moodle

Task Requirements:

Students must complete the following tasks:

Part A: Data Handling and Python Basics (20 Marks)

• Import the CSV dataset using Python.
• Store data using appropriate data structures (lists/dictionaries).
• Convert numerical fields correctly (e.g., MonthlyCharges, Tenure).
• Display sample records.

Expected concepts:

• Variables
• Lists
• Dictionaries
• Loops
• Conditional statements

Part B: Business Calculations (30 Marks)

Using simple Python logic:

• Calculate total number of customers.
• Calculate churn rate (%).
• Calculate total monthly revenue.
• Calculate revenue lost due to churn.
• Identify churn count by contract type.

Clear printed outputs must be shown.

Part C: Data Visualization (15 Marks)

Using Matplotlib:

• Create at least ONE bar chart (e.g., churn by contract type).
• Properly label:
  • Title
  • X-axis
  • Y-axis

Graphs must be readable and professionally presented.

Part D: Business Analysis & Interpretation (25 Marks)

Students must write a structured business report including:

• Executive Summary
• Problem Statement
• Key Findings
• Revenue Impact Analysis
• Strategic Recommendations
• Conclusion

The analysis must clearly connect Python outputs to business decisions.

Part E: Code Quality & Structure (10 Marks)

• Code is clean and well-organized.
• Proper comments explaining logic.
• Meaningful variable names.
• No unnecessary complexity.
• Runs without errors.

Submission Requirements:

Students must submit:

• Python Script File (.py)
• Business Report (PDF or Word)1500–2500 words
• Graphs included
• Screenshots of code output (if required)

10. Technical Guidelines

Students must:

• Use simple Python
• Use csv module or basic file handling.
• Use Matplotlib for visualization.

The focus is on applying basic programming to business problems.

11. Academic Integrity

• This is an individual assignment.
• Plagiarism will result in penalties as per college policy.
• Code must be original.
• Proper referencing is required for external sources (Harvard as per college guidelines).

12. Assessment Expectations 

To achieve high marks (Distinction level), students should:

• Demonstrate clear linkage between analysis and strategy.
• Provide financially meaningful interpretation (e.g., revenue impact).
• Suggest realistic and implementable recommendations.

13. Suggested Report Structure

• Title Page
• Executive Summary
• Introduction
• Methodology (Python approach)
• Data Analysis & Results
• Visualizations
• Business Insights
• Strategic Recommendations
• Conclusion
• References