Abstract—Market expansion is a business growth strategy. The methods for expanding a market include channel expansion, new product development, new market identification, and sales expansion. With growing social media usage, consumers have changed their shopping behavior from internet surfing to social media referral. Therefore, transaction data is not the only data source to be analyzed for identifying an effective distribution channel, a new market, a new product, or a marketing strategy in market opportunity research. Big data, by, combining numerical information, textual information, image, and video together for analysis, has become the new data source. However, the challenge in performing big data analysis is the way in which the data being gathered, integrated, filtered, organized, analyzed, and presented. This paper aims to present a novel big data analytics framework with ubiquitous and self-learning capabilities able to handle the dynamical change of the market environment for market opportunity analysis. To evaluate the effectiveness of the framework, the conceptual framework was implemented in a market research project. The outcomes of the project and the lessons learned are discussed.
Index Terms—Big data analytics, market opportunities, ExporTech Detroit, knowledge engineering.
Adela SM Lau is with the Center for Business Development, School of Business, Madonna University, USA (e-mail: slau@madonna.edu). Nidhal Bouazizi is with DePaul University, USA (e-mail: nbouaziz@mail.depaul.edu).
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Cite: Adela SM Lau and Nidhal Bouazizi, "Using Big Data Analytics for Market Opportunities: A Case Study of ExporTechTM Detroit," International Journal of Knowledge Engineering vol. 5, no. 2, pp. 40-46, 2019.
