AI in data-driven marketing: Decoding consumer choices and behaviours
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F26%3A0198772" target="_blank" >RIV/00216305:26510/26:0198772 - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/pages/publications/105000778614?origin=recordpage" target="_blank" >https://www.scopus.com/pages/publications/105000778614?origin=recordpage</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1108/978-1-83662-326-720251005" target="_blank" >10.1108/978-1-83662-326-720251005</a>
Alternative languages
Result language
angličtina
Original language name
AI in data-driven marketing: Decoding consumer choices and behaviours
Original language description
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.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
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OECD FORD branch
50204 - Business and management
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Data Engineerign for Data-Driven Marketing
ISBN
9781836623274
Number of pages of the result
12
Pages from-to
33-45
Number of pages of the book
234
Publisher name
Emerald Publishing
Place of publication
Leeds, UK
UT code for WoS chapter
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