Customer Retention & Churn Analysis
🔍 About the Task
In this real-world analytics task, you will work with customer and subscription data to understand why customers leave and what keeps them engaged.
This type of analysis is core to SaaS companies, startups, and subscription-based businesses, where reducing customer churn directly improves revenue and growth.
Your goal is to help business teams answer questions such as:
- Why are customers leaving the platform?
- Which customer segments are most likely to churn?
- How long do customers typically stay active?
- What actions can improve customer retention?
This task reflects actual work done by data analysts in product, growth, and retention teams.
✅ What You’ll Do
As part of this task, you will:
- Clean and organize customer or subscription data
- Analyze:
- Churn rates and retention trends
- Customer cohorts (by signup month, plan, or region)
- Customer lifetime patterns
- Identify key retention drivers and churn reasons
- Present insights as if you were advising a real SaaS or subscription business
🛠️ Tools You Can Use
Choose the tools that best fit your analysis approach:
- Microsoft Excel – for data cleaning, cohort tables, and basic analysis
- Python (optional) – for advanced churn metrics and cohort calculations
- Power BI – for retention dashboards and business storytelling
You may use one tool or a combination of tools, just like in real-world data analyst roles.
🎯 Skills You’ll Gain
By completing this task, you will develop highly in-demand skills such as:
- Customer retention & churn analysis
- Cohort analysis and segmentation
- Customer lifetime metrics
- Business-focused insight generation
- Data-driven decision making
These skills are especially valuable in SaaS, fintech, edtech, and subscription businesses.
📁 Dataset Guidance
You may use any dataset that represents customer or subscription behavior and aligns with a real business retention problem.
Recommended Datasets (Optional)
- 📊 Telco Customer Churn Dataset (Kaggle)
https://www.kaggle.com/datasets/blastchar/telco-customer-churn
Widely used dataset with customer demographics, services, and churn status. - 📦 SaaS Subscription Churn Dataset (Kaggle)
https://www.kaggle.com/datasets/andrewmvd/churn-dataset-for-telecom-companies
Useful for cohort analysis, retention metrics, and churn prediction. - 📈 Customer Analytics Dataset
https://www.kaggle.com/datasets/mkechinov/ecommerce-behavior-data-from-multi-category-store
Good for analyzing user behavior and engagement patterns.
⚠️ You are not limited to these datasets.
You may also use your own, simulated, anonymized, or business-specific data as long as it reflects a real customer retention or churn scenario.
💼 Real-World Tip (Important)
To get maximum value from this task, think beyond datasets:
- Imagine you are advising a subscription app, online course platform, or software tool
- Ask: “If I were the founder, what would I want to know from this analysis?”
- Focus on actionable insights, not just charts
This mindset helps you move from student-level analysis to job-ready analytics thinking.
📤 Final Deliverable
You are required to submit:
- A retention analysis dashboard or report
- Clear insights on:
- Churn patterns
- Retention drivers
- Customer lifetime trends
- Practical recommendations to help reduce customer churn
Your submission should look like something you could confidently present to:
- A product manager
- A startup founder
- A business stakeholder
🚀 Why This Task Matters
This is not a practice exercise.
Customer retention analytics is:
- One of the highest-impact areas in data science
- Widely used in real SaaS and tech companies
- A skill that directly connects analytics to revenue
Completing this task prepares you for real analytics roles and freelance opportunities.
📢 Showcase Your Work
Once you complete this task:
- Upload your project to a public GitHub repository with proper documentation (README, files, dashboard links).
- Share a professional post on LinkedIn highlighting:
- What problem you worked on
- Key insights or outcomes
- Tools used and learnings
Please tag and follow Future Interns on LinkedIn so your work can be recognized and shared:
👉 https://www.linkedin.com/company/future-interns/
Sharing your work publicly helps build a verifiable portfolio, increases professional visibility, and reflects real-world industry practice.