Performed analysis and customer segmentation of banking clients.
This is a online project based on real-world business problems, offered through Qureos
You are expected to explore and preprocess the banking dataset provided by Deloitte. You should cleanse the data, handle missing values, and prepare it for customer segmentation analysis. Additionally, perform descriptive statistics and visualizations to gain initial insights into the dataset.
After the data cleaning and processing, you should now be able to apply clustering algorithms, such as k-means, hierarchical clustering, or DBSCAN, to segment banking customers based on their financial behavior, transaction patterns, and demographic attributes. Evaluate different clustering techniques and select the most appropriate one for the dataset. By identifying homogeneous customer groups, you will enable more targeted marketing strategies and personalized customer experiences.
By interpreting the results, you will be able to uncover valuable information about each customer segment's preferences, needs, and behaviors. Your task is to analyze the characteristics and behavior of each customer segment to derive actionable insights. You should then identify key attributes that distinguish each segment and develop targeted marketing strategies to enhance customer engagement and satisfaction.