Bank Marketing Analysis

Check out the project on GitHub

This project presents an interactive dashboard designed to analyze the profile of customers involved in a bank marketing campaign. It also evaluates the campaign's performance across different profiles, supporting strategic decision-making for future actions.

Dashboard

How Was It Done?

The data came in a CSV file with irrelevant columns, unclear column names, and inconsistent entries. Using the Pandas library, the data was cleaned, transformed, and exported to an Excel spreadsheet. With a clean dataset, measures and visualizations were built in Power BI, resulting in a complete and functional dashboard.

Main Insights

• The majority of contacted customers work in administration, hold a college degree, are married, and are on average 40 years old.
• The overall campaign conversion rate was 11%.
• Customers with a college degree had a conversion rate of 15%.
• Retired individuals showed a significant conversion rate of 25%.
• Single customers had a conversion rate of 14%.
• Calls made via mobile phones resulted in a 17% conversion rate, compared to just 4% for landline calls.
• Customers who had converted in previous campaigns had a 65% likelihood of converting again.