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@article{174921,
        author = {Mr. Nibin mathew and H.Vaseemajerina and Mr.A.TamilArasan},
        title = {MACHINE LEARNING METHODS FOR ANTICIPATING CONSUMER BEHAVIOUR},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {1943-1945},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174921},
        abstract = {Machine Learning for Anticipating Consumer Behavior Pattern Understanding and predicting consumer behavior is crucial for businesses aiming to remain competitive in a rapidly evolving market. As consumer preferences become more diverse and dynamic, companies need robust tools to anticipate and adapt to these changes. Machine learning (ML) provides an invaluable set of techniques for analyzing vast amounts of data, uncovering hidden patterns, and making accurate predictions about future consumer actions. Machine learning methods allow businesses to go beyond traditional analytics by leveraging advanced algorithms that can automatically learn from data, adapt to new information, and provide actionable insights. These insights can guide product development, marketing strategies, customer service improvements, and overall business decision-making. In the context of consumer behavior, ML models can be applied to predict a purchasing decision, brand loyalty, churn rates, and responses to marketing campaigns. These predictions can then be used to personalize customer interactions, optimize pricing strategies, and enhance product recommendations—leading to improved customer satisfaction and higher sales. This introduction to machine learning for anticipating consumer behavior will explore the most commonly used techniques, how they work, and their applications in the business world. The goal is to illustrate how ML can turn data into a powerful tool for predicting and shaping consume behavior in real-time.},
        keywords = {Artificial Intelligence (AI Big Data. Data Mining Specific ML Techniques Clustering (K-Means, Hierarchical Clustering) Classification (Logistic Regression, Decision},
        month = {April},
        }