Bank Customer Churn Analysis
Cleaned and prepared approximately 10,000 customer records, identifying inconsistent, invalid and duplicate data before analysis. Combined customer and account datasets using Customer ID and XLOOKUP to create a consolidated, analysis-ready dataset. Performed data-quality checks for unmatched records, formula errors and inconsistencies across the joined dataset. Analysed customer churn across geography, gender, age, account balance, credit-card ownership and number of products. Calculated an overall churn rate of 20.38% and identified material differences between customer segments, including a 32.46% churn rate for Germany. Produced a dedicated analysis worksheet summarising KPIs and business-focused insights for clear communication to non-technical stakeholders.