Repository files navigation

The project is about the reduction of churn rate of credit card customers of a 150-year-old bank called Wells Fargo.According to Gary W. Class, senior vice president for Wells Fargo, it pays to know the customer’s channel preferences, and to predict which products they might need.The bank was able to reduce the customer churn rate with a lead analysis program that took both of those variables and more into account. The bank started out by studying data about the customer’s behaviors and their interests, patterns, etc.

The desired business impact is to reduce customer loss and reduce the monetary loss of the bank.

The data was taken from Kaggle-https://www.kaggle.com/datasets/sakshigoyal7/credit-card-customers

It has information about 10,000 customers and 22 attributes.

•The process included data cleaning and analysis.

•Simple correlation study was done among two or three different features.

•Determine which category of customers have churned.

•Introducing promotions like low interest rate and high cash back deals on shopping, etc.

•Considering other issues like cyber security and fraud.

•Google Sheets –link -https://docs.google.com/spreadsheets/d/1M9Xt0ju4m2csnk5z0Sb3UDeE0viBTRsXgmRulhObzJk/edit?usp=sharing

•Tableau for interactive visualizationsTableau dashboard links –https://public.tableau.com/app/profile/sameera.bellary/viz/Wells_Fargo_creditCard_1/Dashboard1https://public.tableau.com/app/profile/sameera.bellary/viz/Wells_Fargo_creditCard_2/Dashboard2https://public.tableau.com/app/profile/sameera.bellary/viz/Wells_Fargo_creditCard_3/Dashboard3