Discount Optimisation in Food Delivery Using Machine Learning

This chapter delves into the transformative impact of machine learning on discount optimization within the food delivery industry. It explores the evolution of discount strategies from simplistic approaches to sophisticated, data-driven models that leverage customer behavior patterns and demographic insights. The analysis reveals distinct seasonal trends, such as the surge in dessert orders during festive seasons and the consistent popularity of items like sushi and pizza. Demographic segmentation highlights generational preferences, with younger consumers favoring fast food and older demographics opting for healthier choices. The chapter also examines the weak correlation between discounts and order value, challenging conventional assumptions and suggesting that factors like food quality and convenience play a more significant role in consumer decisions. Practical applications of machine learning, including customer segmentation and dynamic pricing, are discussed, along with ethical considerations and potential biases in data usage. The findings underscore the importance of aligning seasonal menu planning, discount strategies, and operational planning with identified demand patterns to enhance customer satisfaction and operational efficiency.