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Google trends as complementary tool for new car sales forecasting : a cross-country comparison along the customer journey

Kinski, Alexander (2016) Google trends as complementary tool for new car sales forecasting : a cross-country comparison along the customer journey.

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Abstract:Purpose: The automotive industry is faced with increased demand volatility but still relies on outdated forecasting approaches. The thesis aims to investigate differences in the explanatory power of internet searches to predict new car sales in Germany and the United States with the tool Google Trends. The car buying process is examined and the effect of implementing a time lag within the dataset is assessed to increase the value of internet data. The customer decision journey towards buying a new car illustrates the time lag as the time between the online search for information and the final car purchase decision. Methodology: Several linear regression models were estimated to investigate the relationship between Google Search queries and new car sales data. Findings: The study found a significant and positive relationship between internet searches for car models and the car model sales data in both countries with an accuracy of up to 68.5%. The implementation of a time lag highly improved the validity and the accuracy of prediction models that include internet data and opens up new research possibilities. The thesis stresses the value and the necessity to adjust search query data to predict economic variables but raises the awareness of researchers and practitioners not to rely blindly on internet data. The outcomes suggest that the length of the customer journey depends on the car model, the price and is influenced by the national culture. Academic Contributions: The thesis contributes to the Google Trends literature by examining differences in the prediction accuracy of search queries across countries for the first time and by improving prediction models that include internet data. Practical Contributions: The results encourage decision-makers in the automotive industry to use tailored search engine data as a possibility to observe people´s interests for particular car models and to enhance new car sales forecasting and demand planning across countries.
Item Type:Essay (Master)
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:85 business administration, organizational science
Programme:Business Administration MSc (60644)
Link to this item:http://purl.utwente.nl/essays/70462
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