In business today, generation of leads could help save resources like time and money and increase the revenue. Moreover, if the business is able to correctly identify the customers of different segments and cross sell their products, it would obviously improve the business revenue, customer satisfaction, customer life time value through a deeper integration in a customer’s business.
Thus, generating leads for cross selling becomes a great strategy for both the business and the customer, creating a Win-Win.
Problem Statement:
The client is a happy bank with different kinds of bank accounts such as investment account, savings account, NRI accounts, fixed deposit account and so on. The idea is to find if the bank can do cross sales of the credit products among the customers of a different account.
Thus, the problem statement is to classify the customers and find if they will be interested to buy a credit card or not and their probability of getting the credit card.
- The Notebook file is
Credit Card Lead Prediction.ipynb. - The output file is
output_cxl.csv.
To know how to solve the problem statement Approach
We have obtained a good roc_auc_score score for test data. The thresholds for each of the model has helped in decent split and we have successfully achieved the objective
The models can be tuned for hyperparameter optimization, but because the training data is large, it takes time for parametrs to get tuned.
This dataset was part of May 2021 Job-a-thon conducted my Analytics Vidhya, for more info check:Link to Competition
Reference: https://datahack.analyticsvidhya.com/contest/job-a-thon-2/#MySubmissions
