Publication result detail

AI in data-driven marketing: Decoding consumer choices and behaviours

KONEČNÁ, Z.; VALLIAPPAN, R.; RAMACHANDRAN, K.; CHENXI, W.; MANAIRKARASI, V.

Original Title

AI in data-driven marketing: Decoding consumer choices and behaviours

English Title

AI in data-driven marketing: Decoding consumer choices and behaviours

Type

Chapter in a book

Original Abstract

The digital marketing sphere is witnessing a transformative era with the integration of artificial intelligence (AI), reshaping the methodologies businesses employ to comprehend and engage their consumer base. Throughout this chapter, the authors have discussed the investigation of diverse roles of AI in data-driven marketing. The authors have also examined its application in analysing and understanding consumer behaviour, delved into the complexities of AI-enabled targeted marketing strategies, and discussed the ethical considerations inherent in the utilization of AI within marketing contexts. This chapter seeks to provide a thorough analysis of both the current influence and the future potential of AI in revolutionizing digital marketing. This embarks on an exploration of AI's pivotal role in augmenting data-driven marketing practices, where the detailed examination of consumer data is leveraged to generate pertinent marketing insights and influence consumer engagement strategies. AI's incorporation into marketing transcends conventional analytical methods, enabling a deeper and more complex understanding of consumer behaviours, preferences, and decisionmaking mechanisms. Furthermore, it considers the forthcoming trends and challenges that AI introduces in this dynamic domain, envisioning a future where marketing strategies are increasingly guided by intelligent data interpretation.

English abstract

The digital marketing sphere is witnessing a transformative era with the integration of artificial intelligence (AI), reshaping the methodologies businesses employ to comprehend and engage their consumer base. Throughout this chapter, the authors have discussed the investigation of diverse roles of AI in data-driven marketing. The authors have also examined its application in analysing and understanding consumer behaviour, delved into the complexities of AI-enabled targeted marketing strategies, and discussed the ethical considerations inherent in the utilization of AI within marketing contexts. This chapter seeks to provide a thorough analysis of both the current influence and the future potential of AI in revolutionizing digital marketing. This embarks on an exploration of AI's pivotal role in augmenting data-driven marketing practices, where the detailed examination of consumer data is leveraged to generate pertinent marketing insights and influence consumer engagement strategies. AI's incorporation into marketing transcends conventional analytical methods, enabling a deeper and more complex understanding of consumer behaviours, preferences, and decisionmaking mechanisms. Furthermore, it considers the forthcoming trends and challenges that AI introduces in this dynamic domain, envisioning a future where marketing strategies are increasingly guided by intelligent data interpretation.

Keywords

rtificial intelligence; Consumer behaviour; Data-driven marketing; Marketing trends; Purchase behaviour

Key words in English

rtificial intelligence; Consumer behaviour; Data-driven marketing; Marketing trends; Purchase behaviour

Authors

KONEČNÁ, Z.; VALLIAPPAN, R.; RAMACHANDRAN, K.; CHENXI, W.; MANAIRKARASI, V.

Released

20.03.2025

Publisher

Emerald Publishing

Location

Leeds, UK

ISBN

9781836623274

Book

Data Engineerign for Data-Driven Marketing

Pages from

33

Pages to

45

Pages count

12

URL

BibTex

@inbook{BUT198772,
  author="Zdeňka {Konečná} and Raju {Valliappan} and K.K. {Ramachandran} and Wang {Chenxi} and V. {Manairkarasi}",
  title="AI in data-driven marketing: Decoding consumer choices and behaviours",
  booktitle="Data Engineerign for Data-Driven Marketing",
  year="2025",
  publisher="Emerald Publishing",
  address="Leeds, UK",
  pages="33--45",
  doi="10.1108/978-1-83662-326-720251005",
  isbn="9781836623274",
  url="https://www.scopus.com/pages/publications/105000778614?origin=recordpage"
}