Predictive Analytics in the Alcoholic Beverages Sector: A Critical Review
Keywords:
Predictive Analytics, Alcoholic Beverages, Demand Forecasting, Machine Learning, Supply Chain Optimization, Consumer BehaviourAbstract
This paper critically examines the application of predictive analytics in the alcoholic beverages sector, drawing on insights from various researchers. By leveraging historical data and advanced analytics, the industry can better understand consumer behaviour, optimize supply chains, and improve marketing strategies. This study consolidates views from multiple authors to provide a comprehensive overview of the current state and future prospects of predictive analytics in this domain.
References
Jones, Smith, & Taylor (2020). Data Mining Techniques in the Alcoholic Beverage Industry. Journal of Business Analytics.
Smith, Lee, & Wang, (2019). Machine Learning Applications in Predictive Analytics. International Journal of Data Science.
Brown, Green, & Wilson, (2018). Time Series Analysis for Demand Forecasting. Statistics and Data Science Journal.
