Development of a forecasting model for the prediction of product sales using search engine query data

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Forecasting delivery dates and quantity of sales is a big challenge concerning the logistical planning. In most cases the logistical planning is aggravated by fluctuations concerning sales. Sales fluctuations may arise due to advertising or promotion events. This uncertainty may cause delayed deliveries or quality issues regarding the material. As a consequence the logistical performance decreases such as the service level diminishes. Giving the growing importance of effective sales planning many companies rely on quantitative methods of sales forecasting. The shortcomings of these conventional forecasting approaches are in particular a low timeliness of data, a low level of detail and a high forecasting effort. The objective of this research proposal is to develop and evaluate an innovative approach for product specified sales forecasting. The forecasting model shall be based on internet search engine query data. Search engine query data contains keyword information (e. g. time, quantity) which are related with a consumption intention. Thus, it is expected to decrease forecasting errors and increase the forecast horizon compared to existing forecasting models. These potentials of search engine query data for sales forecasting shall be analyzed and revealed. Also knowledge shall be generated concerning the limitations of the achieved approach. The research forms the basis for the development of industrial-suited forecasting models which are based on search engine query data.