A knowledge engineering framework for intelligent targeting of online video advertisements. (11th September 2019)

• Record Type: Journal Article
• Authors: Stalidis, George
• Is Part Of: International journal of technology marketing. Volume 13:Number 2(2019)
• Page Start: 165
• Page End: 177
• Publication Date: 2019-09-11
• Subjects: video advertisement -- knowledge engineering -- correspondence analysis -- knowledge modelling -- advertisement effectiveness -- intelligent marketing; Technology -- Marketing -- Periodicals; 338.476
• Languages: English
• ISSNs: 1741-878X

Abstract

One of the newest and most promising media employed by digital marketing is the distribution of advertising video spots through social media and popular websites. This paper addresses the problem of optimising the effectiveness of such video ads by using intelligent technologies which improve the matching between ads and targeted audience. Multidimensional data analysis methods are applied to discover relations among video ad characteristics, audience characteristics and the resulting effectiveness of the ads, thus extracting knowledge on how certain design features, such as music, scenario and humour may affect aspects of the ad effectiveness. The analysis findings are introduced in a knowledge-based tool so that an inference engine can automatically match selected ads to target audiences for which high prospects of success are predicted. The paper presents the analysis and knowledge engineering methods, as well as results of a small-scale application.