Using Machine Learning Algorithms to Personalize Customer Experience in Ghost Kitchens: Hyper-Personalized Marketing and Promotion
- Title
- Using Machine Learning Algorithms to Personalize Customer Experience in Ghost Kitchens: Hyper-Personalized Marketing and Promotion
- Creator
- Solar, Tanvir Singh
- Description
- The emergence of ghost kitchens has revolutionized the food delivery industry by leveraging machine learning algorithms to enhance customer satisfaction and personalized experiences. This chapter, examines how predictive analytics identifies customer preferences, helping ghost kitchens create effective marketing strategies aligned with tastes and behaviours. It highlights real-time personalization, where offers are tailored based on past orders, location, and time, fostering relevance and loyalty. AI-driven customer segmentation is explored as a vital tool for precise targeting. At the same time, the chapter also addresses how AI assesses campaign performance to refine marketing tactics and adapt to changing demands. This research adds new fresh knowledge to the established body of knowledge in the context of restaurant food consumption behavior (Maziriri, E. T., Rukuni, T. F., & Chuchu, T. (2021)). This chapter is going to explore how AI advancements revolutionize resource utilization, evolving customer preferences, sustainable growth. 2025 by IGI Global Scientific Publishing. All rights reserved.
- Source
- Impact of AI and the Evolution of Future Ghost Kitchens;pp.311-358
- Date
- 01-01-2025
- Publisher
- IGI Global
- Coverage
- Solar T.S., Christ University, Delhi, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833730434-2; 979-833730432-8;
- Format
- online
- Language
- English
- Type
- Book chapter
Collection
Citation
Solar, Tanvir Singh, “Using Machine Learning Algorithms to Personalize Customer Experience in Ghost Kitchens: Hyper-Personalized Marketing and Promotion,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/24550.
