Keyword Competition and Determinants of Ad Position in Sponsored Search Advertising

Given the significant growth of the Internet in recent years, marketers have been striving for new techniques and strategies to prosper in the online world. Statistically, search engines have been the most dominant channels of Internet marketing in recent years. However, the mechanics of advertising in such a market place has created a challenging environment for marketers to position their ads among their competitors. This study uses a unique cross-sectional dataset of the top 500 Internet retailers in North America and hierarchical multiple regression analysis to empirically investigate the effect of keyword competition on the relationship between ad position and its determinants in the sponsored search market. To this end, the study utilizes the literature in consumer search behavior, keyword auction mechanism design, and search advertising performance as the theoretical foundation. This study is the first of its kind to examine the sponsored search market characteristics in a cross-sectional setting where the level of keyword competition is explicitly captured in terms of the number of Internet retailers competing for similar keywords. Internet retailing provides an appropriate setting for this study given the high-stake battle for market share and intense competition for keywords in the sponsored search market place. The findings of this study indicate that bid values and ad relevancy metrics as well as their interaction affect the position of ads on the search engine result pages (SERPs). These results confirm some of the findings from previous studies that examined sponsored search advertising performance at a keyword level. Furthermore, the study finds that the position of ads for web-only retailers is dependent on bid values and ad relevancy metrics, whereas, multi-channel retailers are more reliant on their bid values. This difference between web-only and multi-channel retailers is also observed in the moderating effect of keyword competition on the relationships between ad position and its key determinants. Specifically, this study finds that keyword competition has significant moderating effects only for multi-channel retailers

Web crawler research methodology

In economic and social sciences it is crucial to test theoretical models against reliable and big enough databases. The general research challenge is to build up a well-structured database that suits well to the given research question and that is cost efficient at the same time. In this paper we focus on crawler programs that proved to be an effective tool of data base building in very different problem settings. First we explain how crawler programs work and illustrate a complex research process mapping business relationships using social media information sources. In this case we illustrate how search robots can be used to collect data for mapping complex network relationship to characterize business relationships in a well defined environment. After that extend the case and present a framework of three structurally different research models where crawler programs can be applied successfully: exploration, classification and time series analysis. In the case of exploration we present findings about the Hungarian web agency industry when no previous statistical data was available about their operations. For classification we show how the top visited Hungarian web domains can be divided into predefined categories of e-business models. In the third research we used a crawler to gather the values of concrete pre-defined records containing ticket prices of low cost airlines from one single site. Based on the experiences we highlight some conceptual conclusions and opportunities of crawler based research in e-business. --e-business research,web search,web crawler,Hungarian web,social network analyis

The benefits of search engine optimization in Google for businesses

Abstract. This study concentrates on search engine visibility and the benefits of search engine optimization (SEO) in Google for businesses. It seems that search engine visibility has undeniably an important role in business. Most of the people use internet, more than half of Internet traffic begins with search engines and majority of users search for information about goods and services on a regular basis. Google has the largest market share of all search engines. SEO has been studied since 1998 when Google was founded. In earlier studies the topics varied from the basics of SEO to the SEO process in practice and finally to the benefits of SEO. Only a limited number of information systems theory (IS) studies focus on the role of organic listing in search engine visibility. That is why some of the references in this literature review represent also general business research. The research question is “What are the benefits of Search Engine Optimization (SEO) in Google for businesses?” and the sub questions are: “Why search engine visibility is important for businesses?”, “How can business achieve organic search engine visibility in Google?” and “What is the future of Search Engine Optimization (SEO)?” This is a qualitative empirical study which utilizes eight semi-structured interviews on the matter. The goal of this study is to create a comprehensive understanding about SEO and the benefits businesses can get from it. Another ambitious attempt is to try to forecast the future role of search engines and SEO for business operations. The main benefits of SEO for businesses are better search engine visibility, more visitors and better-quality visitors on website and more conversions. It has been noted in many articles, that SEO alone will not provide us the desired return on investment (ROI). In the empirical results of this study, the interviewees also mentioned better understanding of search engine users, website programming and business as one of the benefits

In Google we trust?

In a micro-founded model, we derive novel incentives for a monopoly search engine to distort its organic and its sponsored results on searches for online content and offline products. Distorting organic results towards content publishers with less effective display advertising and/or distorting sponsored results towards higher margin merchants (by underweighting consumer relevance in search auctions) increase per capita revenues but lower participation. The interplay of these incentives determines search bias and welfare. We also characterize how the welfare consequences of integration into display advertising, as intermediary or publisher, depend on asymmetries, monopolization and targeting

Term-driven E-Commerce

Die Arbeit nimmt sich der textuellen Dimension des E-Commerce an. Grundlegende Hypothese ist die textuelle Gebundenheit von Information und Transaktion im Bereich des elektronischen Handels. Überall dort, wo Produkte und Dienstleistungen angeboten, nachgefragt, wahrgenommen und bewertet werden, kommen natürlichsprachige Ausdrücke zum Einsatz. Daraus resultiert ist zum einen, wie bedeutsam es ist, die Varianz textueller Beschreibungen im E-Commerce zu erfassen, zum anderen können die umfangreichen textuellen Ressourcen, die bei E-Commerce-Interaktionen anfallen, im Hinblick auf ein besseres Verständnis natürlicher Sprache herangezogen werden

Network failure: digital technology in sponsored search advertising

The current study advances understanding of sponsored search advertising (SSA) by exploring failures in networks of SSA tools and human actors. SSA represents a novel form of information technology-bound marketing practice that has rapidly proliferated marketing over the last 25 years. The confluence of search technology and advertising has redefined how contemporary marketing is practiced, causing significant redistribution in marketing spent, advertising activity and the emergence of new actors. These shifts have attracted significant interest with rapidly growing number of studies addressing matters around SSA strategy, including various SSA features and functions. In radical departure from mainstream SSA literature, the current study adopts a practice-based view to provide a more nuanced understanding of how the networks of human and technological actors emerge, are stabilised and fail in SSA. By casting SSA as networked practice, the study highlights social construction and the dynamic, multiple and fluid nature of SSA. Actor network theory (ANT) theoretically frames failure in SSA and the networked nature of human and nonhuman actors that contribute to it. The study adopts a qualitative research design, where the data was collected through a 7-month ethnography and the data set includes semi-structured and insitu interviews, day-to day (participant) observations, images, field notes, secondary data and a detailed research diary. The data is anchored on events made up of relations – the principal units of analysis. The findings are presented as a set of ethnographic stories from problematised events. They show how SSA dynamism, fluidity and multiplicity can only be acknowledged accurately enough if human and nonhuman actors in networks are followed in their attempts to build heterogeneous relations. This enables enactment of several new actors, intentions and roles from the Google advertising practice in a specialised SSA agency. The findings provide novel insights that address several gaps in the marketing literature