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Data & Analytics project

Customer Churn Analysis

Find which customers are likely to leave — and why — using SQL and Python.

Intermediate~7 hoursSQLPythonpandasPower BI

System workflow

  1. InputCustomer data
  2. AIChurn signals
  3. AutomationAnalysis
  4. OutputRetention plan

The problem

Businesses notice churn only after revenue drops.

The solution

Cohort and behaviour analysis identifies early churn signals and segments at-risk customers for targeted retention.

Build steps

How you’ll build it

  1. 01

    Prepare

    Join subscription, usage and support data.

  2. 02

    Explore

    Build retention cohorts and compare behaviours.

  3. 03

    Segment

    Identify at-risk groups and their signals.

  4. 04

    Recommend

    Present a prioritised retention plan.

Expected output

  • Cohort retention analysis
  • At-risk customer segments
  • Retention recommendations
  • Dashboard

Tools

  • SQL
  • Python
  • pandas
  • Power BI

Skills you’ll learn

  • Cohort analysis
  • pandas
  • Segmentation
  • Insight communication

Build it in

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  • Most popularLive

    Data Analytics Career Program

    Excel, SQL, Power BI and Python — become a job-ready data analyst.

    • 16 weeks
    • 25+ projects
    • Beginner
    • Certificate

    ₹12,999Original price ₹19,99935% off

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