Retail Customer and Market Proclivity Assessment using Historical data and Social Media Analytics

Our research focuses on gaining insights into the retail market by introducing an integrated proclivity assessment model to examine the consumer-market relationships. First, we perform a qualitative study to investigate the potential sales of the grocery market by utilizing the consumer's transactional history data released by Instacart. Second, we proficiently interpret the user propensity towards grocery products by scrutinizing consumer tweets based on the user location. Finally, we propose an extended framework to detect the category of purchase intentions reflected by the consumers in their online reviews. Amalgamating the three distinct models, we present a web application as the use case that allows retailers to mine consumer behavior and market tendencies. The integrated approach can assist retailers to foresee the demand and adjust the supply chain of their business which further can help in generating better schemes and effective promotional campaigns to maximize the revenues.