Efficient Machine Leaning Algorithms for Sentiment Analysis In Car Rental Service

Opportunities in both business and vacation travel spell good news for the future of the global vehicle rental sector. The global car rental market is projected to grow from its current value of $90 billion in 2020 to an estimated $120 billion in 2025, a CAGR of 6.1%. A growing international tourist sector, more international air passengers, and rising worldwide incomes are the primary forces propelling this market. Enhancing the user experience through digitization, increasing the number of environmentally friendly rental cars, and the idea of self-driving cars as an alternative to traditional chauffeur services are all examples of emerging trends that are having a significant impact on the industry as a whole. Companies may better cater to client needs by offering vehicles that are a good fit based on real-time data analysis. In this work, the proposed algorithm facilitates the renting of cars according to the requirements of individual clients, such as pick-up time, car type, location, and even more specialized need, such as infant car seats and various sports equipment carrying racks. Changing customer-service practices at car rental agencies are helping them attract and retain regulars. However, AI is the most important component in developing trust with customers through individualized service and suggestions.