Cross- and upselling usually terms that have a negative connotation to it. They are thought of annoying selling strategies that consists of selling something more expensive to the customer to increase revenues, but they don’t have to be annoying. In fact, these strategies can be used to enhance the customer experience for flight passengers. Through cross-selling and upselling the trip can be of more value to the customer by making their whole trip coherent and most of all seamless. It is about knowing how and when to apply these strategies and to whom, for example offering car rental to that family that will spend two weeks in France or a comfort seat to that business traveler that has a long flight ahead. Cross- and upselling should be looked at as ways to offer personalized offers at all the stages of the travel process. To achieve this it is essential to assess the big data that is available and select what to include.
By applying cross-sell analysis it helps to determine the customers with the highest probability to penetrate cross-and upselling. This model includes the variables relating to the customer profile, relationship client-supplier and product history, of which all combinations are being calculated e.g. passenger A from city x, is y many years old, has booked multiple flights to city z, with product a, for this reason the probability is n for them to purchase product category m. Even though, it is a fairly thorough analysis to use because of the numerous business rules that are taken into consideration, airlines should still be careful with their interpretation of the data, as the outcomes can produce an over- or underestimation of the probabilities (Peelen & Beltman, 2013).
The calculations of cross-sell probabilities alone does not seem to be enough and targeting could be more specific. For example by also segmenting the type of travelers into business traveler, leisure traveler, families and so on. This allows in-depth analysis on these segments separately. Not only would it uncover the customers with a higher value to your airline, but also would help to get to know these certain type of customers throughout their entire end-to-end journey experience and the most significant touchpoints by connecting data across all channels (Dent, 2013). Databases have grown over the years that we now have access to demographics, psychographics, transactional, behavioural and many more data. By applying connected data analysis of all the characteristic data, it helps to understand the passenger experience from beginning to end, therefore it would allow an airline to cross- and upsell the correct products at the right time to the designated passengers (Matthews, 2016). Qantas airlines is one of the pioneers when it comes to cross-selling. It uses these types of data mining techniques to optimize and personalize its content e.g. it attempts to cross-sell by sending out emails with offers that differ per segment (Reddy, 2015).
Datamining contributes to identifying segments, probabilities and patterns, which creates an overall clear view of the passenger experience. This allows airlines to cross- and upsell their way to profits, because of knowing when and how to be of importance to their passenger that would make their journey personal and seamless.
Dent, J. (n.d.). Customer Journey Mapping: A Walk In Customers’ Shoes. Ascend Contributor.
Matthews, D. (2016, September 1). How connected data is targeting consumers. Retrieved October 1, 2016, from Raconteur: http://raconteur.net/business/how-connected-data-is-targeting-consumers
Peelen, E., & Beltman, R. (2013). Customer Relationship Management. United Kingdom: Pearon Education Limited.
Reddy, T. (2015, June 16). 5 Ways That Qantas is Using Data to Delight Customers & Build Loyalty. Retrieved october 9, 2016, from Umbel: https://www.umbel.com/blog/big-data/5-ways-qantas-using-data-delight-customers-build-loyalty/