THE CONTRIBUTION OF UNSTRUCTURED DATA FROM SOCIAL MEDIA FOR PREDICTION IN MARKETING MANAGEMENT

Abstract

ABSTRACT The capacity to obtain market insights is a strategic need for companies to remain competitive. Despite this and the massive volume of data generated by consumers every second, companies rarely have the culture of making marketing decisions based on data and, when they do, rarely use consumer data widely available online, especially on social networks. One reason is that these data (e.g. texts) tend to be “dirty”, disorganized and bulky, a so-called unstructured data. The purpose of this article is to discuss the benefits of new types of data that have become more abundant and accessible in Web 3.0 through popular social networks, as well as new methods of analysis, particularly learning methods for prediction. For this, an extensive literature review was carried out and a topic modeling was conducted to get an overview of the data and methods. At the end, the article suggests six main marketing challenges that unstructured data analytics can contribute to overcome, improving companies’ competitiveness.

Keywords

• Marketing Analytics
• Unstructured Data
• Predictive Models
• Marketing Management
• Social Media