Understanding Airline Passenger Behavior through PNR, SOW and Webtrends Data Analysis

This study investigates airline passenger behavior by analyzing three types of travel data: passenger name record (PNR), share of wallet (SOW) and webtrends. First, PNR archives the airline travel itinerary for individual passenger and a group of passengers traveling together. Usually, passengers and their accompaniers are close to each other, such as families, friends, lovers, colleagues and so on. Therefore, the social network between passengers and their accompaniers can be constructed through exploring the PNR history data. The PNR data analysis will help the airline company to identify who are influential passengers in their social circles. Second, SOW is a marketing term representing traveler´s value and contribution to a company, which refers to the amount of the customer´s total spending that a business captures in the products and services that it offers. This study measures SOW as a ratio of tickets purchase amount from an airline company to passenger´s total travel times. With SOW data analysis, this study identifies who are potential high-value travelers, and suggest corresponding marketing segmentation and promotion strategies based on different SOW level. This study also analyzes webtrends data to explore passenger behavior of websites and mobile usage. Passenger´s webtrends information includes mobile number, membership number, identity number, and other web browsing records. Connecting these webtrends data with other information sources, this study provides an overview and insights on individual passenger´s website and mobile usage. Furthermore, this study configures the accessing event flow on WebTrends, and incorporates it into the sequence analysis of passenger events. All data sources are provided by a Chinese Airline company. This study demonstrates how to develop comprehensive understanding on passenger travel behavior and social network using PNR, SOW and Webtrends data. The findings shed new light on airline precision marketing and cust- mer relationship management.