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Tools used in this project
Bank Customer Churn

Power BI Dashboard

About this project

Bank Customer Churn

Account information for 10,000 customers at a European bank, including details on their credit score, balance, products, and whether they have churned.

Analysis and questions realized:

  1. What attributes are more common among churners than non-churners? Can churn be predicted using the variables in the data? Most of them are 40 to 65 years old & categorized as the Oldest or Brand New Clients.
  2. What do the overall demographics of the bank's customers look like? Half of the Customers, Number of Products, Active Members, Total Credit Scores & Credit Cards are French; but in terms of Balance France & Germany has almost the same amount.
  3. Is there a difference between German, French, and Spanish customers in terms of account behavior? Yes, Germans customers have on average more Balance in their Banks.
  4. What types of segments exist within the bank's customers? Most relevant ones analyzed here are the Ternure Group (Antiguity of the Customers), their Age Groups, Genders & Estimated Salaries.

Additional project images

Customer Analysis
Region Analysis
Key Influencers of Churneds
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