Analyzing Customers Buying Behavior Before and After COVID-19 Using Association Rule Mining and Machine Learning

India got affected by COVID-19 in March 2020. Many super stores and online marts have seen a sudden decline in the sales of many items and increase in the demand and sales of some new items amid this. To effectively manage with such kind of changing economy, variety of products, their layout on shelves, and promoting special promotions, a quick and efficient customer purchasing pattern analysis is required which can help in increasing the revenue. In this paper, customer behavioral analysis for their buying patterns is done before and after COVID-19 using association rule mining algorithms. The 4-year dataset is collected from an online mart from January 2018 to January 2022 containing more than 5 lakhs entities for 38 countries. To validate the results of these algorithms, two machine learning algorithms are also used.