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.
Step 2: Identify niche segments and create relevant discounts
Having a "one view" ensures you are able to understand user behavior effectively and start segregating those users you really want to make an offer to.
In a way, discounts should not be offered just based on routes or RBD. But should also factor in user’s characteristics and browsing intent. One could end up with micro segments like these:
- User has visited your website at least three times and has researched a non-competitive long-haul route
- Loyal app user who has traveled on business in the past is now booking a family trip (2 adults, 1 child)
- User who has booked higher economy class in the past has selected “flexible dates”, but ultimately homed into a weekend date, then dropped off without buying
For each of these user segments, there can be an associated offer. If this cannot be done, at the least, the best available offer can be mapped against each segment
Step 3: Integrate one view with your marketing channels
Integrating one view with marketing channels ensures a highly efficient execution of the offers. And it also ensures a delightful customer experience.
Take the first segment we created above: A user has visited your website at least three times and has researched a non-competitive long haul route.
In this case, when the user is on the website, the marketing system needs to recognize in real-time that the user has satisfied the segment criteria. And then accordingly create and display an ad to the user.
Or in the case of the loyal user, a personalized push notification needs to be sent to the user with the relevant discount.
The three-step approach is a simplistic framework. Of course, in reality, this is not as easy to implement because it requires a concerted approach on the part of airline companies. Marketing and commercial teams need to align at a strategy level, at a data level, and at an execution level to become user-centric.
Based on what we have seen, strategy level alignment is probably the hardest part. Assuming this alignment is reached, the technical integration generally follows a standard path described below.
Data aggregation basically requires a Data Management Platform (DMP) to be in place.
In effect, clickstream data from your desktop and mobile sites, your app behavior data, second- and third-party data from various sources, and your offline CRM/loyalty data comes together in your DMP. The DMP, in turn, can be connected to the existing in-house marketing and advertising stack.
NB: This is a guest viewpoint by Subra Krishnan, the Bengaluru-based SVP of products at Vizury, a Big Data marketing company.