Web-Based Machine Learning System for Assessing Consumer Behavior

This paper introduces a new web-based system to automate the use of machine learning techniques to support decision-makers in identifying and assessing consumer's behavior. Customer retention is one of the main pillars of business development in the competitive market, and the timely identification of factors that influence customer opinions is a topic of real interest for both business and academia. Seven machine learning classification methods were applied and evaluated on an established dataset aimed at understanding the behavior of the consumer of banking services. A new web application was developed to automatize the assessment of implemented techniques and reveal the optimum one, in terms of performance, by fine-tuning the parameters of the selected models. This solution can be successfully applied on other datasets gathered to better target the marketing campaign and prioritize the promotion to customers who have a high potential to hire a new service or purchase a particular product.