A study of the method using search traffic to analyze new technology adoption

Various types of indices have been developed and applied for the purpose of identifying emergent technologies and forecasting their adoption. Recently, researchers have proposed search traffic analysis as a new method for tracking changes among consumers and utilizing this information to conduct further market research. Now with the onset of big data era, various attempts are being made to analyze the immense body of information made available by hidden traces left behind by consumers. In the same vein, our present study seeks to draw attention to the analytical advantages of utilizing search traffic. In this study, we use search traffic to analyze the adoption process of a new technology, in this case the technology of hybrid cars, for the purpose of verifying the potential value of conducting adoption analysis based on search traffic and we also propose a more refined method of analysis. First, we undertook to examine the keyword unit used in the searches, in order to refine our analysis of search traffic and thereby obtain greater practical utility. This was accomplished by comparing technology searches that specified the technology name with searches that specified the brand name. For each respective case, we also performed comparative analyses examining instances in which consumers simultaneously included the representative attributes of a product in their search.Our research found that the traffic of searches that specify a product's brand name was significant for explaining sales. Therefore, in the conclusion of this paper we argue that if the unit of search is properly refined, search traffic can indeed serve as an extremely useful method for analyzing or forecasting sales volume. Notably, brand-focused search traffic exhibited a superior ability to forecast sales volume compared to macro-indicators such as GDP growth or WTI prices that had been used to forecast car demand in preceding studies. Forecasting based on search traffic was even superior to forecasts using other bibliometric indices such as patent applications or news coverage.