Customers purchase products online everyday, whether they be daily necessities or various luxury items! Companies are focused on turning the back-end purchase data into actionable insights for functions like targeted sales and marketing to specific avatar groups. 

In this competition, we are focused in on better understanding why a certain subset of customers return products and the various reasons for their returns. Given the multitude of data enclosed in the data file, we want to know what specific indicators within the customer dataset can help carve out interesting patterns or trends to help answer the return reason question.

Based on the size of the data, analyzing this manually, row by row, simply isn't feasible. Which is why you will be tasked with using the most appropriate machine learning algorithm(s) that you feel will help answer our high-level question. 

Good luck!