Direct versus search engine traffic
Manuel Kaesbauer,
Ralf Hohenstatt and
Richard Reed
International Journal of Housing Markets and Analysis, 2012, vol. 5, issue 4, 392-413
Abstract:
Purpose - The application of “Google” econometrics (Geco) has evolved rapidly in recent years and can be applied in various fields of research. Based on accepted theories in existing economic literature, this paper seeks to contribute to the innovative use of research on Google search query data to provide a new innovative to property research. Design/methodology/approach - In this study, existing data from Google Insights for Search (GI4S) is extended into a new potential source of consumer sentiment data based on visits to a commonly‐used UK online real‐estate agent platform (Rightmove.co.uk). In order to contribute to knowledge about the use of Geco's black box, namely the unknown sampling population and the specific search queries influencing the variables, the GI4S series are compared to direct web navigation. Findings - The main finding from this study is that GI4S data produce immediate real‐time results with a high level of reliability in explaining the future volume of transactions and house prices in comparison to the direct website data. Furthermore, the results reveal that the number of visits to Rightmove.co.uk is driven by GI4S data and vice versa, and indeed without a contemporaneous relationship. Originality/value - This study contributes to the new emerging and innovative field of research involving search engine data. It also contributes to the knowledge base about the increasing use of online consumer data in economic research in property markets.
Keywords: Home buying search process; Search query data; Google Insights for Search; Transaction volume; House price; Sentiment; Search engines; Property marketing; Housing; Prices (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijhmap:v:5:y:2012:i:4:p:392-413
DOI: 10.1108/17538271211268538
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