Leveraging Machine Learning for Personalization in Ghost Kitchens
Sukhpreet Singh, Jaspreet Kaur · Advances in computational intelligence and robotics book series · 2025
The rise of ghost kitchens, or delivery-only restaurants, has revolutionized the food industry by providing scalable, cost-efficient, and flexible solutions to meet the growing demand for online food delivery. However, the absence of physical customer interactions poses challenges in delivering personalized customer experiences. This chapter explores how machine learning (ML) can bridge this gap by leveraging data-driven personalization to transform customer experiences in ghost kitchens. From analyzing customer preferences to dynamic menu optimization, ML algorithms enable hyper-targeted marketing, enhanced order accuracy, and operational efficiency. Case studies and success stories are discussed to illustrate practical applications. This chapter also addresses potential challenges such as data privacy and algorithmic biases while providing actionable insights for implementing ML solutions in the ghost kitchen ecosystem.