Estimating Customer Lifetime Value Using Machine Learning Techniques

Sien Chen

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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With the rapid development of civil aviation industry, high-quality customer resources have become a significant way to measure the competitiveness of the civil aviation industry. 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 travellers. What is more, the airline company 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 customer life value remain controversial, and how to design a model that applies to airline company still needs to be explored. In the paper, the author proposed the optimised China Eastern Airlines passenger network value assessment model and examined its fitting degree with the TravelSky value score. Besides, the author combines China Eastern Airlines passenger network value assessment model score with loss model score to help airlines find their significant customers.
Original languageEnglish
Title of host publicationData Mining
EditorsCiza Thomas
Place of PublicationUnited Kingdom
Number of pages18
ISBN (Electronic)9781838815677
ISBN (Print)9781789235968
Publication statusPublished - Aug 2018


  • customer lifetime value
  • estimating
  • machine learning


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