This chapter analyses potentials of including online search volume data in modeling the demand series of consumer products. Forecasting future demand for products of a company represents one of the important parts of planning and conducting business in general. Thus, the purpose of this chapter is twofold. The first purpose is to give a critical overview of the existing research on the topic of forecasting and nowcasting demand and consumption. The other purpose is to fill the gap in the literature by empirically comparing several approaches of modeling and forecasting demand and consumption on real data. Results of the empirical analysis show that including online search volume data can enhance modeling and forecasting of demand series, especially in times of economic downturns. Thus, it is advised to use such an approach in modeling of consumer demand in a business so that better business performance in terms of profits could be obtained.
Škrinjarić, T. (2020), "Using Google Trends in Modeling Product Demand and Consumption: Case of UK Apparel and Footwear Demand", Kumari, S., Tripathy, K.K. and Kumbhar, V. (Ed.) Application of Big Data and Business Analytics, Emerald Publishing Limited, Leeds, pp. 59-78. https://doi.org/10.1108/978-1-80043-884-220211005
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