Estimating Customer Lifetime Value Using Machine Learning Techniques
With the rapid development of the civil aviation industry, high-quality customer resources have become a significant way to measure the competitiveness of the participating airlines. It is well known that the competition for high-value customers has become the core of airline profits. The research of airline customer lifetime value can help airlines identify high-value, medium-value and low-value travelers. What is more, an airline can make resource allocation more rational, with the least resource investment for maximum profit return. However, the models that are used to calculate the value of a customer throughout his or her life cycle remain controversial, and how to design a model that applies to this industry still needs to be explored. In the paper, the author proposed utilizing the optimized China Eastern Airlines passenger network value assessment model and examined how it corresponds to the TravelSky value score. In addition, the author combines the China Eastern Airlines passenger network value assessment model score with a loss model score to help airlines find their customers with the highest probable profitabliity over the long term.