Predictive Analytics in Consumer Buying Behaviour Using Machine Learning
Keywords:
Big data analytics, Consumer buying behaviour, Customer segmentation, Data mining, Machine learning, Predictive analytics, Purchase predictionAbstract
Businesses that want to stay competitive in the digital age need to know how consumers buy things. As more data becomes available from the online world, it is now possible to look more closely at what customers like. Using machine learning and predictive analytics together is a good way to predict what people will do based on past and present data. This study looks at how classification, clustering, and regression machine learning models can be used to predict how people will buy things. It also looks at important factors that affect buying decisions and reviews research that has already been done in this area. The results show that predictive analytics can help businesses better target their customers, personalize their marketing, and make their marketing more effective. Nevertheless, issues like data security, ethics, and model bias should be taken seriously into consideration. Overall, this study has emphasized the significance of predictive analytics as a powerful method to comprehend consumer behaviour and make decisions based on data.
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