Context

All Life Bank is aiming to strengthen its focus on credit card customers in the upcoming financial year. According to insights from the marketing research team, there is significant potential to improve market penetration. In response, the marketing team plans to launch personalized campaigns—both to attract new customers and to offer more value to existing ones.

The research also revealed that customer satisfaction with the bank’s support services is relatively low. As a result, the operations team is looking to enhance the service delivery model to ensure quicker and more efficient resolution of customer queries. To support these initiatives, both the heads of marketing and operations have turned to the Data Science team for assistance. Objective

Segment the existing credit card customer base by analyzing their spending behaviors and interaction history with the bank, with the goal of enabling more targeted marketing and improved customer service. Data Description

The dataset includes information about the bank’s credit card customers, covering their credit limits, number of cards held, and how they typically engage with the bank—whether through in-person visits, online platforms, or the call center.

Here are the variables:

Sl_no – Serial number of the customer

Customer Key – Unique customer identifier

Avg_Credit_Limit – Average credit limit (currency unspecified; assume a standard unit)

Total_Credit_Cards – Number of credit cards held

Total_visits_bank – Number of visits to a physical bank branch

Total_visits_online – Number of online interactions

Total_calls_made – Number of calls made to the support center