Measuring improvement in user search performance resulting from optimal search tips

  • Authors:

  • Neema Moraveji;Daniel Russell;Jacob Bien;David Mease

  • Affiliations:

  • Stanford University, Stanford, CA, USA;Google, Mountain View, CA, USA;Stanford University, Stanford, CA, USA;Google, Mountain View, CA, USA

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

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Abstract

Web search performance can be improved by either improving the search engine itself or by educating the user to search more efficiently. There is a large amount of literature describing techniques for measuring the former; whereas, improvements resulting from the latter are more difficult to quantify. In this paper we demonstrate an experimental methodology that proves to successfully quantify improvements from user education. The user education in our study is realized in the form of tactical search feature tips that expand user awareness of task-relevant tools and features of the search application. Initially, these tips are presented in an idealized situation: each tip is shown at the same time as the study participants are given a task that is constructed to benefit from the specific tip. However, we also present a follow-up study roughly one week later in which the search tips are no longer presented but the study participants who previously were shown search tips still demonstrate improved search efficiency compared to the control group. This research has implications for search user interface designers and the study of information retrieval systems.