Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

Application of Artificial Intelligence to Cross-Screen Marketing: A Case Study of AI Technology Company

Authors
Te Fu Chen, Tsai-Fong Tan, Chieh-Heng Ko
Corresponding Author
Te Fu Chen
Available Online November 2016.
DOI
10.2991/aiie-16.2016.120How to use a DOI?
Keywords
application; artificial intelligence; cross-screen; marketing; ai
Abstract

The study constructs a framework for a multi-screen marketing platform through comprehensive analysis of theory and practice, the model provides practical insights and strategies to help marketers successfully deliver against business goals, while they implement the application of artificial intelligence (AI) to cross-screen marketing. Also, the model can help companies effectively leverage the multi-screen advertising opportunity. Finally, the study adopts a case study of AI technology company to examine how they make it easy for businesses to use AI to grow and succeed in a cross screen era.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-271-8
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.120How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Te Fu Chen
AU  - Tsai-Fong Tan
AU  - Chieh-Heng Ko
PY  - 2016/11
DA  - 2016/11
TI  - Application of Artificial Intelligence to Cross-Screen Marketing: A Case Study of AI Technology Company
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 517
EP  - 519
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.120
DO  - 10.2991/aiie-16.2016.120
ID  - Chen2016/11
ER  -