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The purpose of this paper is to conceptualize a model for sponsored search advertising by incorporating a number of factors which affect the performance of these ads.

The authors draw upon the professional experience and practitioner as well as academic literature to build and analyze the model. Propositions have been forwarded to delineate the various relationships at work in a sponsored search process.

The extant literature on this topic has so far been unable to provide a holistic overview. The paper offers propositions for explaining the role of various factors like the ad rank, branding, role of ad extensions and how impact of these factors may be sensitive to the device used for search.

This work is derived primarily from practice. It is hope that after due empirical validation, advertisers, users as well as search engines will benefit from this stream of research.

This is one of the first works to analyze a sponsored search ad at a micro level. It brings into focus one of the largely unexplored facets of sponsored search advertising.

The purpose of this paper is to model group advertising decisions, which are the collective decisions of every single advertiser within the set of advertisers who are competing in the same auction or vertical industry, and examine resulting market outcomes, via a proposed simulation framework named Experimental Platform for Search Engine Advertising (EXP-SEA) supporting experimental studies of collective behaviors in the context of search engine advertising.

The authors implement the EXP-SEA to validate the proposed simulation framework, also conduct three experimental studies on the aggregate impact of electronic word-of-mouth (eWOM), the competition level and strategic bidding behaviors. EXP-SEA supports heterogeneous participants, various auction mechanisms and also ranking and pricing algorithms.

Findings from the three experiments show that both the market profit and advertising indexes such as number of impressions and number of clicks are larger when the eWOM effect is present, meaning social media certainly has some effect on search engine advertising outcomes, the competition level has a monotonic increasing effect on the market performance, thus search engines have an incentive to encourage both the eWOM among search users and competition among advertisers, and given the market-level effect of the percentage of advertisers employing a dynamic greedy bidding strategy, there is a cut-off point for strategic bidding behaviors.

This is one of the first research works to explore collective group decisions and resulting phenomena in the complex context of search engine advertising via developing and validating a simulation framework that supports assessments of various advertising strategies and estimations of the impact of mechanisms on the search market.

Consumers are increasingly using search-based advertising in e-Business platforms to seek their desirable products. Platforms will choose a centralized advertising mechanism (CAM) or decentralized advertising mechanism (DAM) to offer a search advertising service to lower consumer search cost, as represented by using search time length. It is important for the platform to decide how to choose advertising mechanisms, and how to determine the optimal advertising price and search time length. To address these issues, this study aims to develop a theoretical approach under each mechanism to examine the platform’s optimal search-based advertising strategy by considering search cost.

In this study, two models are developed to examine the optimal search-based advertising strategy by considering consumer search cost (i.e. search time length). By comparing the platform’s profits under two models, the optimal advertising strategy, search time length and price are explored.

It is found that when the seller’s reserve benefit is sufficiently large, the platform benefits from choosing the DAM; otherwise, the CAM is a better choice. The advertising service is usually offered with a shorter search time length accompanied by a higher charge, and a longer search time length accompanied by a lower charge. Specifically, when the seller’s reserve benefit is substantially high, a DAM that benefits both the platform and seller is a better choice. This can explain why many platforms offer advertising services with a DAM.

This paper is the first theoretical study on addressing the search-based advertising strategy, especially the choice of advertising mechanisms, in the online advertising context. It is also the first piece of analytical research that considers the effect of consumer search cost on product demand, and then examines the optimal advertising price and search cost (i.e. search time length) for online platforms.

Google commands approximately 70 per cent of search market share worldwide, resulting in businesses investing heavily in search engine advertising on Google to target potential customers. Recently, Google changed the way in which content and ads were displayed on the search engine results page. This reshuffling of content and ads is expected to affect the advertisers who advertise on Google and/or use it to drive traffic to their websites. The purpose of this study is to analyze the impact of these changes on various stakeholders.

Data have been collected from various sources on the internet including blogs and discussion forums. Netnography has been used as it allows a detailed evaluation of the consumers’ needs, wants and choices in a virtual space.

The average cost-per-click for ads on the top positions is expected to increase. Advertisers whose ads usually occupy the lower positions would be adversely affected. To counter this, more emphasis should be placed on ad extensions and on product listing ads. In addition, organizations would benefit from increased efforts on search engine optimization.

A variety of coping strategies have been developed that can help marketers to successfully navigate through the change, including the use of ad extensions and the use of product listing ads.

This practice-focused paper offers guidelines for digital marketers to use sponsored search more effectively as part of their arsenal in light of some important changes recently made by Google. The potential of netnography as a research methodology has also been expanded by using it in a novel setting and in drawing up actionable insights.

Rob Griffin, senior vice president and U.S. director of search for Media Contacts, a communications consulting firm, is faced with the task of optimizing search engine marketing (SEM) for Air France. At the time of the case, SEM had become an advertising phenomenon, with North American advertisers spending $9.4 billion in the SEM channel, up 62% from 2005. Moving forward, Griffin wants to ensure that the team keeps its leading edge and delivers the results Air France requires for optimal Internet sales growth. The case centers upon Air France's and Media Contacts' efforts to find the ideal SEM campaign to provide an optimal amount of ticket sales in response to advertising dollars spent. This optimal search marketing campaign is based on choosing effective allocation of ad dollars across the various search engines, as well as selecting appropriate keywords and bid strategies for placement on the search result page for Internet users.

In determining the optimal strategy, the case presents background information on the airline industry as well as the Internet search options available at the time, including Google, Microsoft MSN, Yahoo!, and Kayak. Additionally, background information is provided on SEM and its associated costs and means of measuring the successfulness of each marketing effort. The case illustrates how one must first determine the key performance indicators for the project to guide analysis and enable comparison of various SEM campaigns. Cost per click and probability to produce a sale differ among publishers. Therefore, using a portfolio application model's quadrant positions can be used to determine optimal publisher strategies. Additionally, pivot tables help illustrate campaigns and strategies that have historically been most successful in meeting Air France's target Internet sales. Multiple recommendations on how Media Contacts can assist Air France in improving its SEM strategy can be derived from the data provided.

Students learn how to optimally leverage the Internet in generating customer sales in a cost-effective manner. Students will analyze and manipulate a variety of data using pivot tables to determine optimal strategies for obtaining maximum total online bookings through the various online channels available. Using a portfolio application model, students can determine an optimal publisher strategy and complete copy improvement analysis.

This chapter presents a summary of the literature on the influence of the Internet and other digital innovations on markets, consumers, and firms. The review leads to a list of topics in need of research in the general areas of big data, online and mobile advertising, consumer search, online privacy, online reviews, social networks, platforms for online transactions, and the impact of the Internet on retail markets, including multi-channel and omni-channel retailing. We discuss the big data approaches that have been applied to problems of targeting and positioning and suggest areas for further development of these approaches. We also discuss the emerging area of mobile advertising, which can further enhance targeting. On the consumer side, the evidence indicates that the Internet has greatly lowered the costs of search and access to retailers. Much of the consumer data are transmitted to sellers, and much of the online advertising is transmitted to consumers, through platforms, such as Google. We conclude that better models of competition among these platform firms are needed and that they need to be examined for anti-trust violations. While online retailing has grown rapidly, it still has a relatively small share of retail sales. Since sellers can combine the advantages of online and offline channels, it has been common for sellers to branch into multi-channel retailing. Given the increased availability of detailed consumer data, omni-channel selling, which emphasizes strategies for the various touchpoints that lead to a transaction, is an area for further development.

This study aims to address the following research questions: Do the two types of service firms (individual or aggregator) have similar competitiveness on online search ads? How should the two types of service firms select optimal branded keywords to improve search performance? In addition, how do consumers’ search queries influence the service search performance of the two types of service firms?

In this study, the authors conduct an empirical analysis by building a two-stage choice modeling on the process of search engine ranking and consumer click-through decisions. The authors estimate the parameter coefficients and test the hypotheses using maximum likelihood estimation in the logistic regression model.

The empirical findings suggest that consumer response rates are highly dependent upon three aspects (service types, branded keyword strategy and consumer search query). First, the authors found that service aggregators receive greater consumer responses than individual service providers. Second, depending upon the various branded keyword strategies (e.g. generic vs branded, “within-type” vs “cross-type”) implemented by service aggregators or individual firms, the expected consumer responses could be quite different. Finally, customer’s search query, being either generic or branded, also has direct effect and interactive effect with service type on how consumers would response to the sponsored ads in the service search process.

The limitation of the research is twofold. First, conversion rate is not considered in the model estimation due to the nature of the data set. Second, the discussion about the keywords selection strategies is focusing on the hospitality industry. Future research shall further validate the generalizability into other industries.

First, given this competitive advantage, service aggregators should take an aggressive approach to adopting paid search strategy in acquiring new users and enhance its brand salience in the service ecosystem. Second, when considering other competitor’s brand names to include, if a firm is a service provider (e.g. hotel), a strategy that can help it receive higher consumer response would be to use “within-type” rather than “cross-type” branded keyword strategy. If a firm is a service aggregator, a better branded keyword strategy would be to use “across-type” instead of “within-type” approach. In addition, given that consumer’s brand awareness can influence the effectiveness of branded keyword strategy, online service search should target consumers in earlier stages of a decision journey.

The authors believe their theoretical framework can provide actionable solutions to service firms to ease customer’s search process, increase customer’s stickiness using search engines and add value to the customer relationships with all services entities within the digital ecosystem.

This study is the first to expand online search marketing into granule examinations (main and interactive effects of three key factors) in the service search domain. First, the authors differentiate service firms into two categories – online travel aggregators and individual hotels in the model. Second, the authors introduce two sets of new classifications of branded keywords for online service search research (i.e. own versus other brand and “cross-type” versus “within-type” branded keywords). Third, this study integrates service consumers’ search word specificity into the conceptual framework which is often missing in previous online search research.

The study contributes to our understanding of search engine advertising in two main ways. Firstly, we analyze the comparative effectiveness of its campaign parameters. Secondly, we examine the effect of print advertising on search engine advertising

Based on advertising data for a three-year period, we test the hypotheses by means of a path model with the aid of partial least squares.

The advertising budget and the degree of keyword matching yield the greatest effect on the number of signed contracts. The click-through rate and the bid amount contribute, to a lesser extent, to explaining this financial target variance. The number of keywords had no significant effect. The study did not yield significant evidence of print advertising, directly affecting the number of search engine advertisement impressions, but showed an indirect effect of print advertising on the number of conversions, induced directly by search engine advertising.

The multichannel relationship of print and search engine advertising, including its campaign parameters, provides a starting point for future research to provide a coherent methodology for capturing the necessary data, processing the underlying information and evaluating the advertising effects.

The multichannel effect needs to be quantified and taken into account when evaluating print advertising and search advertising campaigns and the future advertising mix is planned.

The study extends the field of search engine advertising in the direction of multichannel effects. In comparison to previous research, empirical evidence on the multichannel usage of print advertising and search engine advertising, related to an overall economic target, is provided.

This paper aims to investigate personalized communications through digital media, which include display, search, social and mobile communications.

Drawing on the literature pertaining to different digital mediums, the authors explore how different factors influence consumers’ responses to personalized communications. The current study integrates and reviews prior literature related to personalization, seeking a richer understanding of when personalized communications improve or hinder customer–firm interactions.

Personalization can both enhance and diminish consumer engagement with the firm: it may heighten privacy concerns because consumers worry about how their data are collected and used, and it can also benefit them in meaningful ways. Thus, firms must use the information that they collect in a strategic manner to balance this personalization-privacy paradox. This paper finds that the benefits of personalization may vary as a function of the medium through which the communication is conveyed. It suggests directions for research in each of these media and strategies firms can implement to mitigate privacy concerns.

This investigation of emerging themes related to search, display, social and mobile communications provides a more comprehensive overview of current research, as well as a foundation for further research into personalization.

This purpose of this article is to solve the problem of bidding on keywords in newly set-up search engine advertising campaigns. Advertisers setting up search engine advertising campaigns for the first time need to place bids on keywords, but typically lack experience and data to determine ranks that maximize a keyword’s profit (generally referred to as a cold-start problem).

The authors suggest that advertisers collect data from the Google Keyword Planner to obtain precise estimates of the percentage increases in prices per click and click-through rates, which are needed to calculate optimal bids (exact approach). Together with the profit contribution per conversion and the conversion rate, the advertiser might then set bids that maximize profit. In case advertisers cannot afford to collect the required data, the authors suggest two proxy approaches and evaluate their performance using the exact approach as a benchmark.

The empirical study shows that both proxy approaches perform reasonably well, the easier approach to implement (Proxy 2) sometimes performs even better than the more sophisticated one (Proxy 1). As a consequence, advertisers might just use this very simple proxy when bidding on keywords in newly set-up search engine advertising campaigns.

This research extends the stream of literature on how to determine optimal bids, which so far focuses on campaigns that are already running and where the required data to calculate bids are already available. This research offers a novel approach of determining bids when advertisers lack the aforementioned information.