How can the airline industry use data mining in order to develop a better one-on-one relationship with their customers?

“In the current time most of the airline industries are using frequency-marketing programs as a strategy for retaining customer loyalty in the form of points or miles. Frequent Flyer Program presents an invaluable opportunity to gather customer information. It helps to understand the behavioral patterns, unveil new opportunities, customer acquisition and retention opportunities. This helps Airlines to identify the most valuable and the appropriate strategies to use in developing one-to-one relationships with these customers” (UkEssays, 2015).

Evolutionary computation (EC) is one of the data-mining techniques. With EC one can divide the population into groups and it can then be determined to which group each individual member belongs: the group of continuing buyers, or the dropouts? One can also ask questions such as: Who is about to change from a light to a heavy user? Who is likely to multiply (bring along new customers through word-of-mouth)?

Frequent flyer programs can be used as the base for using data mining. Airline industries can analyze the travelling behavior of their customers. Furthermore, they can analyze in what period they make bookings and also the reasons for their booking. Are they booking business class or first class? When are they booking for business or first class is for short flight or long flights? From what region are they coming from? All these types of information can be analyzed using the data mining techniques.

After doing the analysis airline companies can use this information to create a more engaging one-on-one relationship with customers. An example could be that an airline company sees that a customer is travelling a lot for business purposes. As such, perhaps they can send the customer an email stating what flights might be of interest to them or other services.

This information could be really helpful for an airline as they can try to make a strategy in order to gain the customers of other airlines based on assumptions from their analysis. The only limitation is that they are using data mining on the frequent flyer programs. There are for sure many other customers that don’t have a frequent flyer program with their own flying patterns. Therefore, they are limited in the information they have acquired and in a way excluding a large part of their customers needs. However, what they manage to find from data mining can be used as a basis with additional research to meet the needs of customers that don’t have frequent flyer programs.

References

(2015). Retrieved 3 October 2016, from           https://www.ukessays.com/essays/tourism/applications-of-data-mining-techniques-in-airline-industry-tourism-essay.php

Peelen, E. (2005). Customer relationship management. Harlow, England: FT Prentice Hall.

Pritscher, L. & Feyen, H. Data Mining And Strategic Marketing In The Airline Industry. Retrieved 3 October 2016, from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.124.7062&rep=rep1&type=pdf

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