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Sunday, November 29, 2009
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ReplyDeleteHere you can find useful insights about how much the trust matters and about ROI, return on Influence.
ReplyDeletehttp://www.changethis.com/44.04.TrustEconomy
Abstract:
Julien Smith and Chris Brogan “If You Build It, They Won't Come What happened to the early days? You built a baseball stadium, a store, a web app, and people flocked to it... now what? We are suspicious of marketing. We don't trust strangers as willingly. Buzz is suspect. It can be bought. Instead, consumers and business people alike are looking towards trust. We want our friends to tell us it's good. We want someone we know to say we should look into it. Marketing spend might start at awareness, but in the Trust Economy, communities are king, and ROI stands for Return on Influence.”
THE ARTICLE "Ontological analysis of web surf history to maximize the click-through probability of web advertisements" BY Deane, Jason AND Pathak, Praveen
ReplyDeleteVERY RECENT INFORMATION ON TARGETING TECHNIQUES AND THEIR TESTING.
HERE YOU GO THE ABSTRACT:
Due to an enormous in lux of capital over the past decade, the online advertising industry has become extremely robust and competitive. The difference between success and failure in such a competitive market often rests in the ability to deliver advertisements that are closely in line with a user's interests. In this work, we propose and test a new online advertisement targeting technique which adapts and utilizes several powerful and well tested information retrieval and lexical techniques to develop an estimate of a user's affinity for particular products and services based on an analysis of a user's web surfing behavior. This new online ad targeting technique performs extremely well in Our empirical tests.
SOURCE: DECISION SUPPORT SYSTEMS Volume: 47 Issue: 4 Special Issue: Sp. Iss. SI Pages: 364-373 Published: NOV 2009
SEARCH ON Elsevier B.V.
YET ANOTHER USEFUL ARTICLE ABOUT ON LINE ADVERTISING: "Audience Selection for On-line Brand Advertising: Privacy-friendly Social Network Targeting" BY Provost, Foster; Dalessandro, Brian; Hook, Rod; Zhang, Xiaohan; Murray, Alan.
ReplyDeleteHERE YOU MAY FIND THE ABSTRACT:
This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behaviour on user-generated content sites, for the purpose of finding good audiences for brand advertising (as opposed to click maximizing, for example). Targeting social-network neighbours resonates well with advertisers, and on-line browsing behaviour data counter intuitively can allow the identification of good audiences anonymously. Besides being one of the first papers to our knowledge on data mining for on-line brand advertising, this paper makes several important contributions. We introduce a framework for evaluating brand audiences, in analogy to predictive-modeling holdout evaluation. We introduce methods for extracting quasi-social networks from data on visitations to social networking pages, without collecting any information on the identities of the browsers or the content of the social-network pages. We introduce measures of brand proximity in the network, and show that audiences with high brand proximity indeed show substantially higher brand affinity. Finally, we provide evidence that the quasi-social network embeds a true social network, which along with results from social theory offers one explanation for the increase in brand affinity of the selected audiences.
SOURCE: KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING Pages: 707-715 Published: 2009; Conference Information: 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Paris, FRANCE, JUN 28-JUL 01, 2009
ANOTHER USEFUL ARTICLE MIGHT INTEREST YOU. IT APPLIES THE ELABORATION LIKELIHOOD MODEL (ELM) TO WEB: "Influence of Web Advertising Strategies, Consumer Goal-Directedness, and Consumer Involvement on Web Advertising Effectiveness"
ReplyDeleteBY: Wang, Kai; Wang, Eric T. G.; Farn, Cheng-Kiang
ABSTRACT: Determining the best way to utilize on-line media for advertising purposes is a critical question. This research, based on the Elaboration Likelihood Model (ELM), incorporates consumer goal-directedness and involvement as moderators influencing when a particular advertising strategy (i.e., variation strategy vs. appeal strategy) will be appropriate for Web advertisements. The results of a laboratory experiment supported the use of ELM in the Web environment and showed how advertising strategies should be designed and implemented in accordance with consumer goal-directedness and involvement to achieve Web advertising effectiveness. The results demonstrated the uniqueness of the Web media and the importance of goal-directedness and consumer involvement in the Web advertising context.
SOURCE: INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE Volume: 13 Issue: 4 Pages: 67-95 Published: SUM 2009