Consumer online search behavior: A cross-industry analysis based on user-level data

Abstract

Understanding consumer online search behavior is crucial to optimize companies’ paid search advertising campaigns. Standard measures such as the click-through rate do not account for this search behavior over time, which may favor a certain group of search type and, therefore, may mislead managers in allocating their financial spending efficiently. We analyzed a large query log for the occurrence of userspecific interaction patterns within and across three different industries and were able to show that consumers’ online search behavior is indeed a multi-stage process that heavily depends on industry-specific characteristics. For example, whereas a product search within the clothing industry typically begins with general keywords (“sneakers”) and that search process becomes narrowed as it proceeds by including more specific, e.g. brand-related (“sneakers adidas”), keywords, this behavior is a relatively rare event in other industries (e.g., the healthcare industry). Our method to analyze consumer search processes helps companies to identify the role of specific activities within a respective industry and to allocate their financial spending in paid search advertising accordingly.