Short message service campaign taxonomy for an intelligent marketing system
2020 (English)In: Developments of Artificial Intelligence Technologies in Computation and Robotics: Proceedings of the 14th International FLINS Conference (FLINS 2020) / [ed] Zhong Li, Chunrong Yuan, Jie Lu, Etienne E. Kerre, Singapore: World Scientific , 2020, p. 606-613Conference paper, Published paper (Refereed)
Abstract [en]
This study presents a novel taxonomy of short message service campaigns, for the purpose of building an intelligent marketing system. The main issue of mass marketing is that one size does not fit everybody. In other words, it is challenging to meet different consumer needs. With the help of artificial intelligence, marketers can be supported to overcome some of these challenges. This study uses a mixed methods approach where design science and grounded theory is used to produce a short message service campaign taxonomy for a future intelligent marketing system. Data collection consisted of 386 previously active campaigns used over 33 months to build the taxonomy. An experimental study was conducted to test the effectiveness of the proposed taxonomy. The experiments involved automatic generation of campaign messages. The validity of these campaign messages, and hence the proposed taxonomy, was ascertained by analysing the messages within a business context. The study concludes that the system, intertwined with the taxonomy, performs comparably to a regular campaign. Another proof of concept is that the business context deemed the generated campaign texts to be both semantically and syntactically similar to run them in active campaigns as experiments.
Place, publisher, year, edition, pages
Singapore: World Scientific , 2020. p. 606-613
Series
World Scientific Proceedings Series on Computer Engineering and Information Science, ISSN 1793-7868 ; 12
Keywords [en]
fashion industry, artificial intelligence, marketing campaign, taxonomy, campaign builder, intelligent marketing system
National Category
Information Systems
Research subject
Information Systems
Identifiers
URN: urn:nbn:se:hb:diva-24163DOI: 10.1142/9789811223334_0073ISBN: 978-981-122-332-7 (print)ISBN: 978-981-122-333-4 (electronic)ISBN: 978-981-122-334-1 (electronic)OAI: oai:DiVA.org:hb-24163DiVA, id: diva2:1505251
Conference
FLINS/ISKE 2020: The 14th International FLINS Conference on Robotics and Artificial Intelligence and the 15th International Conference on Intelligent Systems and Knowledge Engineering, Cologne, Germany, August 18-21, 2020
2020-08-192020-11-302023-11-24Bibliographically approved