Introduction.

• In today's competitive business world, customer retention is the new growth strategy. It's far cheaper to keep an existing customer than to acquire a new one -yet many companies struggle to understand why customers leave.
• The project Customer Churn Analysis dives deep into real-world customer data using Power BI to uncover patterns,behaviors and reasons behind churn.

Project Purpose

• The purpose of this project is to analyze customer churn patterns — understanding what drives customers to discontinue a service and how those insights can improve retention.

Primary Objectives.

1. Measure churn rate across various customer segments.
2. Identify major churn reasons (competitor influence, pricing, dissatisfaction, etc.).
3. Visualize churn by demographics — age, seniority, and usage habits.
4. Understand the impact of contracts and data plans on churn.

📊 Key Findings and Visual Insights

1️⃣ Overall Churn Overview

• Total Customers: 6,687
• Churned Customers: 1,796
• Overall Churn Rate: 26.86%

2️⃣ Payment Methods and Churn Behavior

• Customers using digital payments (Direct Debit, Credit Card) show better retention than those paying via paper checks — possibly due to convenience and automation.

3️⃣ Churn by Demographics.

• Seniors are most likely to churn, potentially due to lower tech adoption, cost sensitivity, or customer support difficulties. Younger users (under 30) show more brand loyalty but may still switch for better deal.

4️⃣ Contract Type vs. Churn

• Month-to-month customers make up more than half of all accounts and have the highest churn rate — suggesting that longer-term contracts can improve retention.

🔍 Insights Summary

From the dashboard insights, a few strong patterns emerge:

• Competitor churn dominates — the company must match or beat offers to retain customers.
• Senior customers are most at risk — they need dedicated support and simplified communication.
• Month-to-month contracts are convenient but risky — loyalty incentives are essential.
• Unlimited data doesn’t ensure satisfaction — perceived value and service quality matter more.
• The first 12 months are crucial — early experience determines long-term commitment.
• Customer service performance directly influences retention

Recommendations.

1️⃣ Build Loyalty Programs: Offer discounts or perks for customers renewing after one year.

2️⃣ Target Competitor Leavers: Analyze competitor offerings and develop retention-specific counterplans.

3️⃣ Monitor Early Churn Signals: Use predictive models to flag customers with short tenure or frequent service calls.

4️⃣ Improve Customer Support: Reduce response time, improve agent training, and use follow-up surveys.

5️⃣ Segment by Demographics: Tailor communication and offers to different age groups, especially seniors.

6️⃣ Encourage Long-Term Contracts: Provide bundles, free add-ons, or premium upgrades for multi-year signups.

Conclusion.

• Every bar,pie and map in this dashboard tells a story - of loyalty, competition and opportunity. Customer churn is not just a number - it is a reflection of trust lost.