Predictive Marketing Analytics for Social Travel Platform Adoption and Customer Engagement in the Indian Market

Abstract

India’s aviation industry is witnessing rapid growth, with millions of first time and infrequent passengers entering airports each year, many of whom experience social discomfort and uncertainty when traveling alone. While conventional travel applications emphasize booking, navigation, and itinerary management, they overlook the social dimension of air travel. This study explores the development and marketing of an intelligent social travel companion solution designed to connect solo travelers with socially compatible companions before boarding. The proposed system employs artificial intelligence for compatibility prediction, multilingual communication, and cultural affinity mapping, while the marketing strategy focuses on trust, inclusivity, and digital integration tailored to the Indian market. The aviation industry of India is currently witnessing an unprecedented growth with an influx of millions of first-time and occasional flyers each year. Such individuals often suffer from uncertainties, social isolation, and discomfort during travel, which are not alleviated by conventional mobile apps. In fact, conventional travel apps only pay attention to the operational aspect of travel, including booking, navigation, and itinerary management, whereas their social potential can be used to improve user experience in aviation significantly. In order to fill in this gap, this paper analyzes the problem of designing and marketing of an intelligent social travel companion application suitable for Indian aviation sector. As a result, solo flyers will get the opportunity to find socially compatible companions before taking off. The approach to marketing of this innovative product will emphasize the importance of trust building, inclusiveness, and seamless integration into the digital environment. An empirical evaluation of the framework demonstrates that it provides an overall accuracy of 96.83%.