AI-Driven Marketing Strategies: Understanding and Predicting Consumer Behaviour

DOI

10.2991/978-94-6463-898-1_23How to use a DOI?

Keywords

Supervised learning; AI-based Marketing; Consumer behavior prediction; Machine Learning; Personalization; Ethical AI

Abstract

The marketing field has been positively confused by AI (Artificial Intelligence) technology that allows enterprises to characterize better not only their consumer interactions, but to also project their reactions. Marketing has advanced beyond micro and macro demographics as AI provides real-time and precise data insights. Marketing professionals that strap predictive analytics within machine learning systems along with deep learning models, can craft immediate responsive multi-dimensional circumstantial marketing strategies that are accomplished across several channels. This research provides a unique understanding into contemporary trends in AI marketing development, which focuses on supervised learning and reinforcement learning, as well as natural language processing techniques for predicting consumer behavior. The research assesses notable case studies as well as experimental results that show how AI-based models have enhanced consumer engagement, retention, and conversion rates. The research currently assesses emerging issues resulting from the deployment of AI technology through a critical evaluation of algorithmic opacity, privacy and ethical concerns, and the risk of consumer administration. AI systems must allow businesses to maximize profits, while at the same time protecting consumers and their social well-being. This ongoing research sums up a range of literature in a way that would provide a broad resource for researchers and practitioners alike who wish to promote responsible advances in AI marketing.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - T. S. Saranya
AU  - Sandeep Kumar Gupta
AU  - Gayathri Raj
AU  - Preeti Sharma
AU  - Rijo S. John
PY  - 2025
DA  - 2025/11/18
TI  - AI-Driven Marketing Strategies: Understanding and Predicting Consumer Behaviour
BT  - Proceedings of the International Conference on Artificial Intelligence in Management for Business and Industrial Growth (AIMBIG 2025)
PB  - Atlantis Press
SP  - 324
EP  - 354
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-898-1_23
DO  - 10.2991/978-94-6463-898-1_23
ID  - Saranya2025
ER  -