To analyze customer data from Samsung's finance department and identify patterns and trends using clustering techniques.
To segment customers based on their financial behavior, preferences, and spending patterns.
To understand the characteristics of each customer segment and propose personalized marketing strategies based on the segmentation results.
To evaluate the effectiveness of the clustering techniques in improving customer analytics and driving business decisions in the finance department of Samsung.
Collect and clean customer data from Samsung's finance department.
Apply clustering techniques such as K-means, hierarchical clustering, and DBSCAN to segment customers.
Interpret and analyze the results of the clustering algorithms to identify distinct customer segments.
Develop customer profiles for each segment and propose personalized marketing strategies.
Present findings and recommendations to the finance department at Samsung.
