As airlines and frequent flyer programs gather more intelligence on your day to day lifestyle, flying and financial position - they begin to build a data profile on your interests, goals, psychometric assessment, your motivations to engage with a brand at any given every point throughout the day, what has driven you to purchase in the past – and most importantly – where your thresholds are.
To illustrate how data is playing a growing role in todays flight booking engines I've broken down play by play how each individual piece of data collected about you can be used, analysed and overlaid with other data sets to paint a picture of who you are, what motivates and drives you to purchase a specific product.
Every day – trillions of calculations are being number crunched to transform this goldmine of data opportunity into real, tangible high revenue opportunities for the airlines and their frequent flyer programs.
When armed with key insights , a holistic overview of yours, and other customers’ detailed profiled information can be applied to direct booking channels which are designed to customize pricing for your personal situation at that very given moment.
Here is how it’s done through Individual, customized pricing.
Consider the following scenario – the airline already has access to all of the information and examples given below.
Airline knows that when you fly LAX-JFK it's always a business trip. They also know or have access the following data points:
How much you have historically paid for a ticket (what you’re willing to pay)
When prices have been higher then you typically purchase for; when you drop out of the sales funnel and abandon a purchase (what you’re not willing to pay)
How many times you research a flight (if any) before making a purchase and how far through the booking process you get each time (from other data they can guess when you’re most likely to continue to the payment screen)
Where your cursor (if PC) hovers during the search process (does it gravitate towards first class pricing or the insurance info-graphic on the left?)
The colours of specific action points on the page people like you most respond to (everyone is different and has attractions to different colours. Are you colour-blind? Airline can figure this out from it’s own data and display appropriate alternatives that are customized to you)
The average amount that people like you pay for the same flight (also factoring in time/day, seasons, flight loads, aircraft type etc..)
If there is a specific event on in your destination city related to your line of work and the likelihood you need to be there on a specific day/time
Are you obsessed with specific seats? (If your favourite seats are taken and you’re less likely to fly on that flight – this can be factored into the equation to move the price needle up and down)
The likelihood of you booking the fare on the airlines own website based on all this, past and similar data on people that match your micro-demographical profile
How motivated you (and your family/friends) are to reach the next level of status/retain your current status
Share of wallet/loyalty that airline has over your spend on that specific route (readily available information for airlines)
Your typical payment method and data on other users of this payment method (e.g.: Tracking the first 8 digits of your credit card number tell the airline what bank and type of credit card you are using for transactions. It’s also possible to figure out who is paying for your flights)
If you have a family, how big it is and how you value time spent with them (easy to obtain from airlines own data sources when overlaid with outside metrics)
How often you have been upgraded for free, used miles/certs to upgrade and calculating if you’re likely to go for an upgrade or pay the extra based on this and many more above factors.
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