Customer Conversation Prediction

You are working for a new-age insurance company and employe mutiple outreach plans to sell term insurance to your customers. Telephonic marketing campaigns still remain one of the most effective way to reach out to people however they incur a lot of cost. Hence, it is important to identify the customers that are most likely to convert beforehand so that they can be specifically targeted via call. We are given the historical marketing data of the insurance company and are required to build a ML model that will predict if a client will subscribe to the insurance.

• Historical marketing data of the insurance company data is given by using previous data ML model is build to predict a client will subscribe to insurance
• By collecting the historical marketing data build a ML model and train the model with a interactive graph that can predict a client will subscribe the insurance or not and F1 score is used to evaluate the performance of the model final model XGBoost has AUROC 92 % and Accuracy 87 %.
• Technologies used in this project Python — Visual Studio — Library required in IDE