shreyas-singhal / lead-scoring-case-study

X Education Organization wants to identify if a customer registered on their website for enquiry is a potential customer or not. Using past data to build a machine learning algorithm

Problem Statement: X Education is an organization which provides online courses to industry professionals. The company marks it's courses on many popular websites like Google. X Education wants to select most promising leads that can be converted to paying customers. Although the company generates a lot of Leads, only a few are converted into paying customers, wherein the company wants a higher lead conversion rate. Leads come through numerous modes like email, advertisements on websites, google searches etc. The company has had 30% conversion rate through the whole process of turning Leads into customers by approaching those Leads which are to be found having interest in taking the course. The implementation process of lead generating attributes are not efficient in helping conversations.

Strategy: Importing Data and Libraries Checking the Dataframe Preparation the Data Exploratory Data Analysis Outlier Detection and Treatment Creating Dummy Variables Train - Test Split Feature Scaling Model Building and Feature Selection using RFE Creating Confusion Matrix Plotting the ROC Curve and finding optimal cutoff point Precision and Recall and F1 Score Making predictions on the test set Assigning Lead Score with respect to Lead_Num_ID