Given the research interest on Big Data in Marketing, we present a research literature
analysis based on a text mining semi-automated approach with the goal of identifying the …

Direct marketing strategies in the banking sector have undergone evolution with the
integration of predictive analytics and machine learning techniques. The focus of this study …

This study presents a research approach using data mining for predicting the performance
metrics of posts published in brands' Facebook pages. Twelve posts' performance metrics …

This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore
the internal B2B data to improve supply chain finance and the efficiency of marketing tactics …

Banks cannot afford to be complacent in their operations. Due to the dramatic changes
brought about by improvements in computer technology (IT) as well as competitive intensity …

Despite the relentless growth of online retail, e-commerce platforms still suffer from a low
purchase conversion rate. Researchers and practitioners have attempted to understand …

Digital corporations are creating new paths of business driven by consumers empowered by
social media. Understanding the role that each feature drawn from online platforms has on …

Feature selection is a highly relevant task in any data-driven knowledge discovery project.
The present research focuses on analysing the advantages and disadvantages of using …

In an increasingly globalized market, the relationship between the customer and the brand
goes beyond the purchasing process. It is very important to understand the customer, to …

We propose a novel methodology for improving financial Decision Support Systems (DSS)
through automatic feature weighting. Using this methodology, we show that automatic …