Predicting Buyer Behaviour: A Reconnaissance of Retail Predictive Analytics Model

In the competitive retail sector, enterprises must be able to anticipate their clientele's behaviours. This research aims to enhance the precision of customer behaviour predictions by constructing retail prediction analytics models. This study seeks to improve comprehension of developing and using predictive models capable of anticipating consumer behaviour, preference, and trend adoption by applying advanced data analytics and machine learning techniques. The investigation begins with examining predictive analytics and its potential benefits for the retail sector. This elucidates the reasons businesses cannot accurately predict future customer behaviour based on existing data and analytics. In addition, we analyse the possible advantages of employing more robust prediction models. This study examines several methodologies and algorithms used in customer segmentation, sales forecasting, and churn prediction. This is achieved by conducting an extensive examination of pertinent scholarly works. This study employs a combination of quantitative analysis and case study research as its technique. The effectiveness of various predictive analytics models is evaluated by utilising real-world data obtained from multiple retail settings as a reference point. Scholars investigate the aspects of data quality, feature engineering, and model interpretability to ascertain these models' precision, reliability, and scalability. The findings of this study possess the capacity to enhance predictive analytics within the retail sector by shedding light on the most effective models and tactics for forecasting customer behaviour. The outcomes of this study will provide valuable insights for organisations, researchers, and practitioners seeking to enhance their marketing strategies, product management practices, and overall customer purchasing experiences by leveraging data-driven methodologies. The study concludes by envisioning a retail setting in which retailers actively adapt to customers' constantly evolving preferences, resulting in a more adaptable and customer-centric future.