7,096 research outputs found

    Inefficiencies in Digital Advertising Markets

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    Digital advertising markets are growing and attracting increased scrutiny. This article explores four market inefficiencies that remain poorly understood: ad effect measurement, frictions between and within advertising channel members, ad blocking, and ad fraud. Although these topics are not unique to digital advertising, each manifests in unique ways in markets for digital ads. The authors identify relevant findings in the academic literature, recent developments in practice, and promising topics for future research

    Multi-keyword multi-click advertisement option contracts for sponsored search

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    In sponsored search, advertisement (abbreviated ad) slots are usually sold by a search engine to an advertiser through an auction mechanism in which advertisers bid on keywords. In theory, auction mechanisms have many desirable economic properties. However, keyword auctions have a number of limitations including: the uncertainty in payment prices for advertisers; the volatility in the search engine's revenue; and the weak loyalty between advertiser and search engine. In this paper we propose a special ad option that alleviates these problems. In our proposal, an advertiser can purchase an option from a search engine in advance by paying an upfront fee, known as the option price. He then has the right, but no obligation, to purchase among the pre-specified set of keywords at the fixed cost-per-clicks (CPCs) for a specified number of clicks in a specified period of time. The proposed option is closely related to a special exotic option in finance that contains multiple underlying assets (multi-keyword) and is also multi-exercisable (multi-click). This novel structure has many benefits: advertisers can have reduced uncertainty in advertising; the search engine can improve the advertisers' loyalty as well as obtain a stable and increased expected revenue over time. Since the proposed ad option can be implemented in conjunction with the existing keyword auctions, the option price and corresponding fixed CPCs must be set such that there is no arbitrage between the two markets. Option pricing methods are discussed and our experimental results validate the development. Compared to keyword auctions, a search engine can have an increased expected revenue by selling an ad option.Comment: Chen, Bowei and Wang, Jun and Cox, Ingemar J. and Kankanhalli, Mohan S. (2015) Multi-keyword multi-click advertisement option contracts for sponsored search. ACM Transactions on Intelligent Systems and Technology, 7 (1). pp. 1-29. ISSN: 2157-690

    Google online marketing challenge and research opportunities

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    The Google Online Marketing Challenge is an ongoing collaboration between Google and academics, to give students experiential learning. The Challenge gives student teams US$200 in AdWords, Google’s flagship advertising product, to develop online marketing campaigns for actual businesses. The end result is an engaging in-class exercise that provides students and professors with an exciting and pedagogically rigorous competition. Results from surveys at the end of the Challenge reveal positive appraisals from the three—students, businesses, and professors—main constituents; general agreement between students and instructors regarding learning outcomes; and a few points of difference between students and instructors. In addition to describing the Challenge and its outcomes, this article reviews the postparticipation questionnaires and subsequent datasets. The questionnaires and results are publicly available, and this article invites educators to mine the datasets, share their results, and offer suggestions for future iterations of the Challenge

    Branding vs perfomance-based advertising : opposing business models?

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    Dissertação de Mestrado, Ciências Económicas e Empresariais, especialização em Marketing, 21 de março de 2019, Universidade dos Açores.O E-marketing – processo de marketing efetuado através da utilização de canais de media digitais – tomou o mundo dos media de assalto na última década. As empresas tiveram de mudar drasticamente para sobreviver, e reinventar-se para permanecerem competitivas no mercado global. Algumas encararam a mudança como uma oportunidade de crescimento e de extensão da marca nos canais online, infiltrando-se no quotidiano dos consumidores. Outras não se adaptaram à constante mutação do ecossistema empresarial. As que prevaleceram consolidaram a consciencialização da marca e nutriram relacionamentos com os consumidores mais facilmente que nunca. Aproveitaram ainda os meios digitais para aumentar rapidamente as suas vendas através de campanhas de publicidade baseadas no desempenho (performance). Campanhas unicamente focadas na otimização do ROI através do rastreamento da atividade online dos utilizadores. Adotaram uma mentalidade smart, tirando partido da tecnologia, para disfrutar de um relacionamento mais próximo com os consumidores. Dois tipos de publicidade paga prosperaram em redes sociais e motores de busca: branding e performance. Contudo, serão estes modelos verdadeiramente opostos? Esta tese procura responder a esta questão de um ponto de vista complementar, que é consolidado com a análise de um caso de estudo, onde a performance está ao serviço de uma típica campanha de branding.ABSTRACT: E-marketing – marketing through the usage of digital media channels – has taken the world of media by storm in the past decade. Companies have had to change drastically to survive and reinvent themselves to remain competitive in a global market. Some saw an opportunity to thrive and extend their branding to online channels, infiltrating the everyday life of consumers. Others failed to adapt to the everchanging business ecosystem. The ones that prevailed have built brand awareness and nurtured brand relationships more easily than ever before. They also leveraged digital media to rapidly grow their sales through performance-based advertising campaigns. Campaigns solely focused on the optimization of ROI via the tracking of online user activity. They have adopted a smart mindset, taking advantage of technology to enjoy a closer relationship with consumers. Two types of advertising have flourished in paid social networks and search engines: branding and performance. However, are they truly opposite models? This thesis seeks to answer this question from a complementary point of view, which is consolidated by the analysis of a case study where performance is at the service of a typical branding campaign

    A Novel Method to Calculate Click Through Rate for Sponsored Search

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    Sponsored search adopts generalized second price (GSP) auction mechanism which works on the concept of pay per click which is most commonly used for the allocation of slots in the searched page. Two main aspects associated with GSP are the bidding amount and the click through rate (CTR). The CTR learning algorithms currently being used works on the basic principle of (#clicks_i/ #impressions_i) under a fixed window of clicks or impressions or time. CTR are prone to fraudulent clicks, resulting in sudden increase of CTR. The current algorithms are unable to find the solutions to stop this, although with the use of machine learning algorithms it can be detected that fraudulent clicks are being generated. In our paper, we have used the concept of relative ranking which works on the basic principle of (#clicks_i /#clicks_t). In this algorithm, both the numerator and the denominator are linked. As #clicks_t is higher than previous algorithms and is linked to the #clicks_i, the small change in the clicks which occurs in the normal scenario have a very small change in the result but in case of fraudulent clicks the number of clicks increases or decreases rapidly which will add up with the normal clicks to increase the denominator, thereby decreasing the CTR.Comment: 10 pages, 1 figur

    Stochastic Budget Optimization in Internet Advertising

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    Internet advertising is a sophisticated game in which the many advertisers "play" to optimize their return on investment. There are many "targets" for the advertisements, and each "target" has a collection of games with a potentially different set of players involved. In this paper, we study the problem of how advertisers allocate their budget across these "targets". In particular, we focus on formulating their best response strategy as an optimization problem. Advertisers have a set of keywords ("targets") and some stochastic information about the future, namely a probability distribution over scenarios of cost vs click combinations. This summarizes the potential states of the world assuming that the strategies of other players are fixed. Then, the best response can be abstracted as stochastic budget optimization problems to figure out how to spread a given budget across these keywords to maximize the expected number of clicks. We present the first known non-trivial poly-logarithmic approximation for these problems as well as the first known hardness results of getting better than logarithmic approximation ratios in the various parameters involved. We also identify several special cases of these problems of practical interest, such as with fixed number of scenarios or with polynomial-sized parameters related to cost, which are solvable either in polynomial time or with improved approximation ratios. Stochastic budget optimization with scenarios has sophisticated technical structure. Our approximation and hardness results come from relating these problems to a special type of (0/1, bipartite) quadratic programs inherent in them. Our research answers some open problems raised by the authors in (Stochastic Models for Budget Optimization in Search-Based Advertising, Algorithmica, 58 (4), 1022-1044, 2010).Comment: FINAL versio
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