Why searchers switch: understanding and predicting engine switching rationales

  • Authors:

  • Qi Guo;Ryen W. White;Yunqiao Zhang;Blake Anderson;Susan T. Dumais

  • Affiliations:

  • Emory University, Atlanta, GA, USA;Microsoft Corporation, Redmond, WA, USA;Microsoft Corporation, Redmond, WA, USA;Microsoft Corporation, Redmond, WA, USA;Microsoft Corporation, Redmond, WA, USA

  • Venue:
  • Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
  • Year:
  • 2011

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Abstract

Search engine switching is the voluntary transition between Web search engines. Engine switching can occur for a number of reasons, including user dissatisfaction with search results, a desire for broader topic coverage or verification, user preferences, or even unintentionally. An improved understanding of switching rationales allows search providers to tailor the search experience according to the different causes. In this paper we study the reasons behind search engine switching within a session. We address the challenge of identifying switching rationales by designing and implementing client-side instrumentation to acquire in-situ feedbacks from users. Using this feedback, we investigate in detail the reasons that users switch engines within a session. We also study the relationship between implicit behavioral signals and the switching causes, and develop and evaluate models to predict the reasons for switching. In addition, we collect editorial judgments of switching rationales by third-party judges and show that we can recover switching causes a posteriori. Our findings provide valuable insights into why users switch search engines in a session and demonstrate the relationship between search behavior and switching motivations. The findings also reveal sufficient behavioral consistency to afford accurate prediction of switching rationale, which can be used to dynamically adapt the search experience and derive more accurate competitive metrics.