Airline recommendation prediction using customer generated feedback data

Abstract

Nowadays consumers are increasingly relying on online resources to aid in purchasing decisions. Online resources also help companies to learn from customer reviews, how different types of customers have different priorities and how customer choice affects their review. In the U.S. 82%, the adult says that they have been referring online reviews and ratings provided by the customer, before going to purchase items for the first time, including 40% who say that they have referring always or almost always do so. In this paper, we have been performed predictive analysis for qualitative reviews on the data that have been collected by different online sites. We have been also performed an explanatory analysis of the different classes of airline services. The findings of this paper show that the review of most of the business class is on the food and friendliness of staff whereas most of the economy class views were on legroom and seat comfort.