Towards automated advertising strategy definition based on analytics

Abstract

In today’s world, advertising has become one of the most important aspects of modern life and has impacted society in many ways. We could say, that it has become embedded (even surreptitiously) into the human symbolic universe. On the other hand, social networks play an almost ubiquitous role both in message production and transmission, as well as providing unique insights not readily available through other channels. It is only natural then, to develop strategies capable of automating information retrieval and processing. Our main goal is the construction of an automated process for the constitution of an advertising strategy based on the use of social network data and user provided information. The underlying model considers text mining algorithms along with an innovative content-based decision process constructed in terms of theoretic-semiotic assumptions of pragmatism of Charles Sanders Peirce. We describe a practical application of the proposed methodology in order to obtain the required insights for the future construction of the advertising strategy of an academic institution in Colombia based on Facebook, Twitter and student-surveys as a first step in the development of an automated solution.