Using cognitive systems in marketing analysis

Economic Annals-ХХI: Volume 160, Issue 7-8, Pages: 56-61

Citation information:
Cervenka, P., Hlavaty, I., Miklosik, A., & Lipianska, J. (2016). Using cognitive systems in marketing analysis. Economic Annals-XXI, 160(7-8), 56-61. doi: https://doi.org/10.21003/ea.V160-11

Peter Cervenka
PhD (Economics),
Senior Lecturer,
Faculty of Commerce, Department of Business Informatics,
University of Economics in Bratislava
1 Dolnozemska cesta Str., Bratislava, 85235, Slovakia
peter.cervenka@euba.sk

Andrej Miklosik
PhD (Economics),
Associate Professor,
Faculty of Commerce, Marketing Department,
University of Economics in Bratislava
1 Dolnozemska cesta Str., Bratislava, 85235, Slovakia
miklosik@euba.sk

Ivan Hlavaty
Masters (Economics),
PhD Student at Faculty of Commerce,
Department of Business Informatics,
University of Economics in Bratislava
1 Dolnozemska cesta Str., Bratislava, 85235, Slovakia
ivan.hlavaty@euba.sk

Julia Lipianska
PhD (Economics),
Associate Professor,
Faculty of Commerce, Marketing Department,
University of Economics in Bratislava
1 Dolnozemska cesta Str., Bratislava, 85235, Slovakia
julia.lipianska@euba.sk

Using cognitive systems in marketing analysis

Abstract. Social media resources currently contain vast amount of unstructured data, open for processing with marketing analytics tools. Due to existing cognitive systems, we can uncover and handle interdependencies within unstructured data, turning them in structured ones. Cognitive computer systems are rapidly evolving and have a big potential to change the way information is used in business applications. Evolution of the cognitive information systems is still ongoing, yet they are already used in business and marketing. The goal of our article is to define various ways to apply cognitive systems for unstructured data analysis and management for further use in marketing analytics. We will use IBM Analytics Tools for the example of cognitive computing. We apply these tools to analyse social media as one of the major sources of data on potential customers. Social media is among the fastest growing communication platforms. At the same time, it is the venue for most swift and immediate reactions by customers to various marketing activities. Analysis of such type of data therefore provides interesting and important information on how people perceive different commercial products.

Via IBM Watson we were able to analyse unstructured data found on social media. The advantage of using cognitive system is that system itself collects the relevant data, which we wanted to analyse, based on preset criteria. Analysis of data from the set of social media provided us with information on frequency of references to and individual perceptions of certain brands. Furthermore, from social media we also learned about demographic and geographical spread of awareness about brands and products. For research we analysed the perception of price of a new Samsung product (Samsung Galaxy S7) among students (age group 18-25) during two months from its launch (from 03.01.2016 to 04.30.2016).

Keywords: Cognitive Computing; Hadoop; IBM Watson Analytics; MapReduce; Marketing Analysis; Semantic Web

JEL Classification: M31

Acknowledgement. This paper is the result of research under the grant scheme 2015-PSD-PAV-02 «Increasing the effectiveness of marketing on social media through automation tools».

DOI: https://doi.org/10.21003/ea.V160-11

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Received 3.05.2016