Predicting the intent of sponsored search users: An exploratory user session-level analysis

Abstract Over time, an online user searching for information about an idea or product may enter multiple search engine queries, thus creating a keyword search pattern from which the user's intent may be inferred. Such inferences could lead a merchant to alter the messages or provide offers to push the user toward a purchase decision once the user reaches the advertiser's website. Our research seeks to establish the relationship between these patterns as they occur during a user's search session and the user's purchase behavior. To test our hypotheses, we examine a unique dataset from a large Asian travel agency that includes over two million unique search engine queries and clicks as well as the same users' corresponding on-site behavior over a one-year period. We developed a typology for the coding of search queries used in determining the level of specificity and breadth as well as content type for each of the searches. Our analysis provides important findings regarding the relationship between search patterns and behavior.

[1]  Kalervo Järvelin,et al.  Task complexity affects information seeking and use , 1995 .

[2]  Detmar W. Straub,et al.  Validation in Information Systems Research: A State-of-the-Art Assessment , 2001, MIS Q..

[3]  Il Im,et al.  Deal-Seeking Versus Brand-Seeking: Search Behaviors and Purchase Propensities in Sponsored Search Platforms , 2016, MIS Q..

[4]  Daqing He,et al.  Analysing Web Search Logs to Determine Session Boundaries for User-Oriented Learning , 2000, AH.

[5]  Oliver J. Rutz,et al.  From Generic to Branded: A Model of Spillover in Paid Search Advertising , 2011 .

[6]  Song Yao,et al.  A Dynamic Model of Sponsored Search Advertising , 2010, Mark. Sci..

[7]  Paul Milgrom,et al.  Simplified mechanisms with an application to sponsored-search auctions , 2010, Games Econ. Behav..

[8]  Marshall Scott Poole,et al.  Affect in Web Interfaces: A Study of the Impacts of Web Page Visual Complexity and Order , 2010, MIS Q..

[9]  Gary A. Steiner,et al.  A Model for Predictive Measurements of Advertising Effectiveness , 1961 .

[10]  Greg M. Allenby,et al.  A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules , 2004 .

[11]  Vandana Ramachandran,et al.  Research Note - Quality Uncertainty and the Performance of Online Sponsored Search Markets: An Empirical Investigation , 2010, Inf. Syst. Res..

[12]  Anindya Ghose,et al.  An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets , 2009, Manag. Sci..

[13]  P. Shrivastava Rigor and practical usefulness of research in strategic management , 1987 .

[14]  Ulku Yuksel,et al.  Too many destinations to visit: Tourists’ dilemma? , 2017 .

[15]  Herbert A. Simon,et al.  The new science of management decision , 1960 .

[16]  Robert W. Reeder,et al.  Information scent as a driver of Web behavior graphs: results of a protocol analysis method for Web usability , 2001, CHI.

[17]  Gabriel J. Biehal,et al.  Information Accessibility as a Moderator of Consumer Choice , 1983 .

[18]  Benjamin Edelman,et al.  Strategic bidder behavior in sponsored search auctions , 2007, Decis. Support Syst..

[19]  Blake Ives,et al.  The information system as a competitive weapon , 1984, CACM.

[20]  D. Campbell Task Complexity: A Review and Analysis , 1988 .

[21]  Peter S. Fader,et al.  On the Depth and Dynamics of Online Search Behavior , 2004, Manag. Sci..

[22]  Sucheta Nadkarni,et al.  A Task-Based Model of Perceived Website Complexity , 2007, MIS Q..

[23]  D. Hosmer,et al.  Applied Logistic Regression , 1991 .

[24]  Paul Benjamin Lowry,et al.  Proposing the Multimotive Information Systems Continuance Model (MISC) to Better Explain End-User System Evaluations and Continuance Intentions , 2015, J. Assoc. Inf. Syst..

[25]  Susan M. Broniarczyk,et al.  Decision Difficulty in the Age of Consumer Empowerment , 2014 .

[26]  D. Gensch A Two-Stage Disaggregate Attribute Choice Model , 1987 .

[27]  Rick L. Andrews,et al.  Studying Consideration Effects in Empirical Choice Models Using Scanner Panel Data , 1995 .

[28]  Glenn J. Browne,et al.  Cognitive Stopping Rules for Terminating Information Search in Online Tasks , 2007, MIS Q..

[29]  Terrence O'Brien,et al.  Stages of Consumer Decision Making , 1971 .

[30]  Rajiv Kohli,et al.  Understanding Determinants of Online Consumer Satisfaction: A Decision Process Perspective , 2004, J. Manag. Inf. Syst..