Keyword Characteristics and Performance of Paid Search Campaigns

Abstract

Despite its importance for both e-commerce and traditional offline vendors, managing paid search campaigns is often based on trial and error. In particular, neither research nor practice has extensively addressed identifying relevant keywords and setting appropriate matching options. The authors develop a model based on a keyword’s intrinsic and extrinsic information content to shed light on how keyword characteristics affect campaign performance. Intrinsic information includes linguistic aspects and user- and content-related features, which can be indirectly changed through extrinsic information such as matching options. Using an advertiser-level data set from multiple industries, this study evaluates the impact of these criteria on click-through and conversion rates. The authors find that the query variation index, which measures whether a keyword contains sufficient information to identify a user’s information need correctly, is an effective predictor of keyword performance. Moreover, they show that the relationship between two of the main predictors, namely, query variation and advertiser names, and a keyword’s performance is moderated by the advertiser’s choice of matching options.

Keywords: Online advertising, Search engine marketing, Click-through rates, Conversion rates, Search queries, Electronic commerce, Query variation index, Information retrieval, Empirical research