Factors that influence the effectiveness of mobile advertising: The case of SMS

Dimitris Drossos, George M. Giaglis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Mobile advertising takes the case of one-to-one marketing one step further, since it allows companies to send personalized offers regardless of time and space boundaries. By employing all the characteristics of one-to-one marketing and augmenting them with features such as location awareness, ubiquitous customer reach, direct response and time independence, mobile advertising is emerging as a promising advertising channel. However, little is known regarding the factors that may influence the effectiveness of a mobile advertising campaign. In this paper we attempt to identify such factors in the field of SMS advertising through an empirical survey of advertisers. Factor analysis is employed for model generation and the outcome provides four main categories that may impact the effectiveness of the SMS advertising communication: campaign strategy, targeting, creative development, and source.

Original languageEnglish
Title of host publicationAdvances in Informatics - 10th Panhellenic Conference on Informatics, PCI 2005, Proceedings
Pages278-285
Number of pages8
Volume3746 LNCS
DOIs
Publication statusPublished - 2005
Event10th Panhellenic Conference on Informatics, PCI 2005 - Volos, Greece
Duration: 11 Nov 200513 Nov 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3746 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th Panhellenic Conference on Informatics, PCI 2005
CountryGreece
CityVolos
Period11/11/0513/11/05

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    Drossos, D., & Giaglis, G. M. (2005). Factors that influence the effectiveness of mobile advertising: The case of SMS. In Advances in Informatics - 10th Panhellenic Conference on Informatics, PCI 2005, Proceedings (Vol. 3746 LNCS, pp. 278-285). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3746 LNCS). https://doi.org/10.1007/11573036_26