Three steps for airlines to enhance yield management

Yield management refers to an airline’s effort to effectively manage supply and demand mismatches using scientific pricing strategies. It’s a practice that can be fine-tuned with the help of personalized marketing.

NB: This is a guest viewpoint by Subra Krishnan of Vizury.

A quick example: On some airline routes and during certain times of the year, there is more demand than supply for weekend tickets and vice versa on weekdays. So while there are the same 100 seats available on a flight on both Saturdays and Tuesdays, Saturdays could have demand for 150 seats, while Tuesdays could have demand for only 50.

The airline can react to this situation in multiple ways. For example, keep prices low on Tuesday flights relative to Saturdays. Alternatively, keep prices competitive on Saturdays but offer flat discounts on Tuesday flights. (The operative word being ‘flat’, or a standard discount applicable to everyone who travels on Tuesdays)

Both of these approaches have one basic limitation. They are not ‘user-centric’. The pricing strategy is aligned around an aggregated view of demand and supply.

This is understandable. Even if yield optimization teams do create user-centric pricing (make no mistake: the people and systems are capable enough to do so), how would this even get executed from a marketing standpoint?

Users search for a flight, look at prices, and drop off without giving away any information on where/how they can be reached. Retargeting is one way to reach them. But most retargeting companies mainly focus on route-based personalization.

Here is a three-step strategy that can help airlines achieve user-centric yield management.

Step 1: Centralize user data and generate a “One View” of users

Being able to recognize your user — whether she is on your website, your app, or browsing a website — is the first and most basic step needed. In creating a “one view”, it is also important to bring in your customer relationship management data about every user so that historical transactions as well as loyalty data are also available for decision-making.

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