This project involves building a dashboard for a bank's customer churn analysis. The dataset used is for ABC bank, and it consists of various input variables such as credit score, country, gender, age, tenure, balance, products number, credit card, active member. The target variable for this dataset is Exited, which is either 1 or 0, indicating whether the client has left the bank during some period or not.
The aim of this project is to identify the factors that contribute to customer churn and provide insights into how the bank can improve customer retention. The dashboard is designed to provide an exploratory data analysis of the dataset, allowing users to interact with the data and gain a deeper understanding of the underlying trends and patterns.
The dashboard includes various visualizations such as bar charts, line charts, that enable users to analyze the data from different angles. For example, the dashboard provides a visualization of the distribution of customer churn by gender and salary band, enabling the bank to identify the salary band and gender groups with the highest churn rates.
Overall, this project demonstrates the use of Power BI for exploratory data analysis and how it can be used to gain insights into customer churn and improve customer retention.