Elsevier

Decision Support Systems

Volume 70, February 2015, Pages 42-59
Decision Support Systems

The moderating effects of keyword competition on the determinants of ad position in sponsored search advertising

https://doi.org/10.1016/j.dss.2014.11.009Get rights and content

Highlights

  • We empirically examine the moderating effects of keyword competition on ad position.

  • The study provides insights into keyword competition and sponsored ad performance.

  • Competition has a significant moderating effect only for multi-channel retailers.

  • Ad position for web-only retailers is dependent on bid values and relevancy factors.

  • Multi-channel retailers are more reliant on their bid values.

Abstract

This study uses a unique cross-sectional dataset of the top 500 internet retailers in North America and empirically investigates the moderating effects of keyword competition on the relationship between ad position and its determinants in the sponsored search market. The study draws on the literature in keyword auction design, search advertising performance, and consumer search behavior as the theoretical foundation. The study finds a significant variation in the role of keyword competition for web-only versus multi-channel retailers. Specifically, this study finds that keyword competition has a significant moderating effect only for multi-channel retailers. The empirical analysis also indicates that the position of ads for web-only retailers is dependent on bid values and ad relevancy factors, whereas multi-channel retailers are more reliant on their bid values. We discuss the implications of these results in light of the increased popularity of sponsored search advertising in recent years.

Introduction

The internet has enabled the distribution of information to be affordable, convenient, and remarkably fast. Search engines in particular have been shown to be the primary gateway for most internet users seeking information [43]. The growth of users, along with simple, targeted, and customizable advertising, has allowed search engines to be the dominant online marketing channel on the internet. Given the unique challenges advertisers face in this growing and dynamic marketplace (e.g., three-agent interaction,1 mounting competition, and increasing budget allocation), it is evident that they must understand the competitive environment to develop effective campaign strategies and achieve their marketing goals. Not only is the display of an ad directly related to the marketing goal, but so is the position of the ad within the search engine result pages (SERPs). Although advertisers vary in their marketing goals (e.g., brand awareness, revenue maximization, lead generation), the conventional wisdom in the industry is that the top position is the most desirable position, leading to intense competition to secure the top positions in the SERPs [3].

The increasingly competitive keyword market requires advertisers to engage in several challenging activities, which include selecting relevant keywords, crafting compelling ad copies, setting appropriate ad budget, and formulating bidding strategies, among others. For example, firms with poor ad budgets may not attain their desired ad positions simply because their ads may not even be considered for the auctions. To effectively compete in this challenging environment, firms experiment with different strategies or use the services of third parties. However, what works in one competitive circle may not necessarily work in another. One feasible way for firms to improve their search advertising performance is to gain sufficient knowledge of the keyword competition and its impact on achieving their desired ad positions using different pay-per-click (PPC) strategies. Meanwhile, search engines have employed mechanisms that rank ads not only based on bid values, but also attributes related to advertisers' performance [21], [48], [51], [52]. For example, Google uses a measure called Quality Score [35] to determine whether an ad is eligible (relevant) to enter the auction as well as its position on the SERP.2 Thus, the overall search advertising outcome for a firm can be influenced by the profiles as well as number of other firms competing for similar keywords.

Early research in sponsored search advertising has focused on the design of keyword auctions and the equilibrium outcome in these auctions (e.g., [21], [27], [28], [48], [51], [52], [70]). Another stream of research analyzes sponsored search ad performance and the relationship between different sponsored search metrics [32], [33], [34], [60], [61], [65]. Other related empirical studies have investigated consumer search behavior in sponsored search market and the classification of web queries (e.g., [42], [44], [45]). Despite the sheer number of firms competing in the keyword market, there is limited empirical work that examines how competition intensity impacts the sponsored search outcomes for firms. A few researchers have studied different aspects of competition in sponsored search auctions. For example, [46] studied a “position paradox” in a keyword auction market, where a superior firm may bid lower than an inferior firm and obtain a position below it, but still obtains more clicks than the inferior firm. [10] showed that the effect of a firm's ad rank on its ad's click-through rate (CTR) is moderated by the firm's ability to differentiate itself from its adjacent rivals in the SERP. [76] illustrated that the value of search advertising slots should be determined endogenously in price competition. They show that a more prominent slot may or may not be more valuable, even if it is cost-free. Thus, firms in different competitive situations should tailor their advertising strategies accordingly [76].

In this study, we empirically investigate the impact of competition intensity on the relationship between a firm's key sponsored search variables (i.e., bid value, click-through rate, and ad quality) and its ad position in the keyword market. Using cross-sectional data on the search advertising practices of firms in the retailing industry, we analyze how the level of competition in the keyword market moderates the relationship between a firm's ad position and its key determinants. We draw on insights from the literature in keyword auction design, search advertising performance, and consumer search behavior to develop and test several empirical models that account for differences in merchant type, company size, advertising budget, and search engine optimization (SEO) performance.

The retailing industry is characterized by extensive search advertising practices and high-stakes battle for market share and profitability [39], [40]. Given that internet retailers are at the very end of the supply chain, advances in web technologies have enabled them to develop new marketing strategies in their advertising campaigns. Utilizing this new form of advertising with its growing consumer exposure enables retailers to expand their market share. We believe that our unique, cross-sectional data and the analyses based on the top performing retailers in North America will be important additions to the empirical base of the sponsored search advertising literature and offer practical insights into the keyword market in general and the search advertising practices within the retailing industry in particular.

The rest of this paper is organized as follows. Section 2 presents a review of the literature in search advertising. Section 3 presents the conceptual framework and the theoretical foundations. Section 4 outlines the research model and the hypotheses of this study. Section 5 describes the data collection procedure, the research methodology, and the empirical results. Section 6 presents the discussion of the results and the theoretical and practical implications of the study. Finally, Section 7 provides the conclusions, limitations, and future research directions.

Section snippets

Literature review

Search engines are providing service for over 50% of internet users on a daily basis [56]. Search engine advertising (SEA), also known as search engine marketing (SEM) or sponsored search marketing, has received significant attention from both academia and industry. According to the “State of Search Marketing Report” by SEMPO [26], the North American search engine marketing industry has increased in value from $16.6B in 2010 to $19.3B in 2011, reaching $22.9B by the end of 2012. The proportion

Conceptual model and theoretical foundation

The positioning strategy of a firm in sponsored search marketplace is often reflected by the position of its ads on SERPs. The ad position is an outcome of a strategic mixture of sponsored search auction determinants, which is observable in the form of bidding values and ad relevancy attributes. Furthermore, this relationship takes place in a competitive environment, where there is a high-stakes battle for keywords and ad slots. In the following sections, we explain why the outcome of

Main effects

The variables that affect the ad position in the sponsored search market have evolved along with changes in the search provider' ranking rules. Following the lead by Google, major search engine providers have incorporated several variables in their ad ranking formula. Although our main research objective is to examine the impact of keyword competition on the relationships of these variables with the ad position, these relationships (i.e., the main effects) have not been empirically tested in a

Data and methodology

This section presents the data collection procedure, the research methodology, and the empirical results of the study. Fig. 5 illustrates an overview of the operational variables derived from our research model. The variables in parentheses are the constructed variables corresponding to the research variables.

Discussion and implications

The literature in consumer search behavior indicates that ad position is an important indicator for a firm's positioning strategy. Given that consumers perceive different values depending on the position of the ads on the SERP [10], the locations of the ad on the SERP have significant implications for advertisers in achieving their marketing goals. In addition, the ad position has a significant effect on a firm's revenue [3]. The significance of the ad position for search engine advertisers

Conclusion, limitations, and future research

This study has drawn from the literature in keyword auction design, search advertising performance, and consumer search behavior to examine the effects of keyword competition on the relationship between a firm's sponsored search variables (i.e., bid value, CTR, and ad quality) and its ad position on the search engine result pages. The research model was tested on a unique cross-sectional dataset from the retailing industry. This study is also the first of its kind to investigate the

Anteneh Ayanso is an Associate Professor of Information Systems at Brock University. He received his PhD in information systems from the University of Connecticut and a MBA from Syracuse University. He is also certified in Production and Inventory Management (CPIM) by APICS. His research interests are in data management, business analytics, electronic commerce, and electronic government. His current related studies include topics such as search engine advertising, the role of social media

References (81)

  • Ashish Agarwal et al.

    Location, location, location: an analysis of profitability of position in online advertising markets

    Journal of Marketing Research

    (2011)
  • Gagan Aggarwal et al.

    Sponsored search auctions with Markovian users

    Internet Network Economics

    (2008)
  • Gagan Aggarwal et al.

    Truthful auctions for pricing search keywords

  • Narendra Agrawal et al.

    Supply chain planning processes for two major retailers

    Retail Supply Chain Management

    (2009)
  • Animesh Animesh et al.

    An empirical investigation of the performance of online sponsored search markets

  • Animesh Animesh et al.

    Research note quality uncertainty and the performance of online sponsored search markets: an empirical investigation

    Information Systems Research

    (2010)
  • Animesh Animesh et al.

    Competing creatively in sponsored search markets: the effect of rank, differentiation strategy, and competition on performance

    Information Systems Research

    (2011)
  • Kursad Asdemir

    Bidding patterns in search engine auctions

  • Jason Auerbach et al.

    An empirical analysis of return on investment maximization in sponsored search auctions

  • Anteneh Ayanso et al.

    Technology-enabled retail services and online sales performance

    The Journal of Computer Information Systems

    (2010)
  • Roger J. Bowden et al.

    Instrumental Variables

    (1990)
  • Lance Brannman et al.

    The price effects of increased competition in auction markets

    The Review of Economics and Statistics

    (1987)
  • T.S. Breusch et al.

    A simple test for heteroscedasticity and random coefficient variation

    Econometrica

    (1979)
  • Roger Brooksbank

    The anatomy of marketing positioning strategy

    Marketing Intelligence & Planning

    (1994)
  • Tom J. Brown et al.

    Reassessing the impact of television advertising clutter

    The Journal of Consumer Research

    (1993)
  • Frederic F. Brunel et al.

    Message order effects and gender differences in advertising persuasion

    Journal of Advertising Research

    (2003)
  • Ray M. Chang et al.

    A network perspective of digital competition in online advertising industries: a simulation-based approach

    Information Systems Research

    (2010)
  • Jianqing Chen et al.

    Keyword auctions, unit-price contracts, and the role of commitment

    Production and Operations Management

    (2010)
  • Chang-Hoan Cho et al.

    Why do people avoid advertising on the internet?

    Journal of Advertising

    (2004)
  • R. Dennis Cook

    Influential observations in linear regression

    Journal of the American Statistical Association

    (1979)
  • R. Dennis Cook

    Detection of influential observation in linear regression

    Technometrics

    (2000)
  • Wenyu Dou et al.

    Brand positioning strategy using search engine marketing

    MIS Quarterly

    (2010)
  • Econsultancy

    State of Search Engine Marketing Report 2012

    (2012)
  • Benjamin Edelman et al.

    Internet advertising and the generalized second price auction: selling billions of dollars worth of keywords

    American Economic Review

    (2007)
  • Edelman, Benjamin, Michael Schwarz. 2006. Optimal auction design in a multi-unit environment: the case of sponsored...
  • Juan Feng et al.

    Implementing sponsored search in web search engines: computational evaluation of alternative mechanisms

    INFORMS Journal on Computing

    (2007)
  • Kuzman Ganchev et al.

    Empirical price modeling for sponsored search 541–548

  • Anindya Ghose et al.

    Analyzing search engine advertising: firm behavior and cross-selling in electronic markets

  • Anindya Ghose et al.

    Modeling Cross-category Purchases in Sponsored Search Advertising

    (2008)
  • Anindya Ghose et al.

    An empirical analysis of search engine advertising: sponsored search in electronic markets

    Management Science

    (2009)
  • Cited by (25)

    • Broad or exact? Search Ad matching decisions with keyword specificity and position

      2021, Decision Support Systems
      Citation Excerpt :

      This suggests that relative to generic keywords, branded keywords in general are associated with better performance but competitor keywords are mostly associated with worser performance. Competition intensity in a specific paid search advertising market has been found to have a role on keyword performance [23,47,48]. Most relationships in our findings may have different outcomes depending on the level of competition intensity in the market.

    • Optimal display-ad allocation with guaranteed contracts and supply side platforms

      2019, Computers and Industrial Engineering
      Citation Excerpt :

      Some studies also study the effectiveness of certain design choices of advertisements on websites (see e.g. Lin & Chen, 2009). We also mention that there is literature that focusses on optimal design of auctions (Ding, Liu, Kang, & Zhao, 2019; He, Chen, Wang, & Liu, 2013; Kamijo, 2013), the relation between ad auction design and strategies for publishers and advertisers (Balseiro, Besbes, & Weintraub, 2015; Chen, 2017), the relation between reserve prices and revenues from ad auctions (Cesa-Bianchi, Gentile, & Mansour, 2015; Chahuara, Grislain, Jauvion, & Renders, 2017; Mohri & Medina, 2016; Ostrovsky & Schwarz, 2011; Refaei Afshar, Zhang, Firat, & Kaymak, 2019a,b; Rhuggenaath, Akcay, Zhang, & Kaymak, 2019a,b,c), and revenue management and optimization in sponsored search advertising (Ayanso & Karimi, 2015; Gopal, Li, & Sankaranarayanan, 2011; Karuga, Khraban, Nair, & Rice, 2001; Zhao, Qiu, Guan, Zhao, & He, 2018). Finally, in the market, a relatively newer approach, called header bidding, has been proposed to eliminate waterfalling Sluis (2015).

    • Sponsored search advertising and dynamic pricing for perishable products under inventory-linked customer willingness to pay

      2019, European Journal of Operational Research
      Citation Excerpt :

      They suggest an alternative bidding mechanism that could reduce the amount of strategizing by bidders, raise search engine revenues and increase efficiency of the market. Ayanso and Karimi (2015) show that the position of advertisements for web-only retailers is dependent on bid values and advertisement relevancy factors whereas multi-channel retailers are more reliant on the bid values. Varian (2007) discusses the Vickrey auction (second price auction) mechanism employed by search engines to rank websites.

    View all citing articles on Scopus

    Anteneh Ayanso is an Associate Professor of Information Systems at Brock University. He received his PhD in information systems from the University of Connecticut and a MBA from Syracuse University. He is also certified in Production and Inventory Management (CPIM) by APICS. His research interests are in data management, business analytics, electronic commerce, and electronic government. His current related studies include topics such as search engine advertising, the role of social media technologies and applications in the commercial as well as public sector, and methods for profiling and measuring ICT positions and e-government readiness of world nations. He has published many articles in leading journals such as European Journal of Operational Research, Decision Sciences, Decision Support Systems, Journal of Database Management, Communications of the AIS, International Journal of Electronic Commerce, Journal of Computer Information Systems, Government Information Quarterly, AIS Transactions on Human–Computer Interaction, and Information Technology for Development, and in proceedings of major international conferences in information systems and related fields. He currently serves as an editorial review board member of the Journal of Database Management, International Journal of Convergence Computing, and International Journal of Electronic Commerce and regularly reviews articles for many leading journals in information systems and related fields.

    Armin Karimi received a MSc Degree in Information Systems from the Goodman School of Business, Brock University, Canada in 2012 and a MSc Degree in Computer Science from Royal Institute of Technology (KTH), Sweden in 2010. His research interests are in online marketing, particularly, in the areas of search engine advertising and social media marketing. He is currently an information systems development specialist at a financial corporation in Toronto, Canada. He is also involved with a startup online marketing company focusing on delivering online marketing solutions to real estate agents.

    View full text