When I think about booking flights, a feeling of panic and dread usually hits me. I’m worried that I might be booking too late, booking too early, or otherwise somehow not finding the best deal I could get. Suffice it to say that the process of booking flights is not something I look forward to.
That’s why I was very interested to look at two organizations who are using data to approach pricing in the airline industry in very different (and conflicting) ways.
In most of the examples we saw in class, companies met resistance to using big data from within their own organizations. Interestingly, here companies are more likely to meet resistance externally rather than from themselves.
Traditional airlines start to roll out dynamic pricing
With traditional static pricing, prices for a flight might go up and down, but these prices are consistent for anyone looking to buy [1,2,3]. In other words, person A and person B will see the same price, and if that price fluctuates, it does so for both of them equally.
With dynamic pricing, the price changes based on the person who’s trying to book the flight [1,2,3]. So for example, if the system determines that a particular user is a business traveler, the airline might hike up the fare knowing that the customer’s ability to pay is high . Traditional airlines like Air France and British Airways , with help from organizations like ATPCO and PROS, are starting to use this dynamic pricing methodology [1,2,3].
The value generation to the airlines themselves is pretty significant: airlines who’ve already started to implement these features have seen “increased conversion rates of up to 50%, and it has enabled airlines to achieve incremental revenue in the 7% to 10% range” . And the claim is that passengers would see benefits too: “Experts say such technology is most likely to be used to offer discounts to customers with loyalty status and to generate bundled fare offerings that fit the customer’s profile.” . Yet, it’s not really clear if the system would be primarily used to decrease fares or increase them , but my money’s on the latter.
In addition to the consumer downsides to potentially increased prices, there are meaningful ethical concerns at play here as well. If a user doesn’t realize that they’re getting prices that are different from everyone else, it seems deceptive and unfair. And in the UK, the Office of Fair Trading has expressed concerns about these sorts of practices, indicating that there may be legal issues to consider as well . Even if there are no legal problems, users may be angered enough to avoid or boycott airlines that employ dynamic pricing practices, so that’s a risk the airlines need to factor in too.
Skiplagged helps customers find “hidden city fares” and angers the airline industry in the process
On the other side, companies like Skiplagged are trying to help customers find the cheapest fares possible. One of the most controversial methods involves so-called “hidden city fares” . Let’s say a user is trying to fly from city A to city B . The site might find a cheaper flight that goes from city A to city C, but with a layover in city B . The user just purchases this cheaper flight and gets off at city B, ditching the connecting flight to city C .
The value generation for customers is pretty significant here. There’s no way I’d be able to search every possible combination of hidden city flights to find the cheapest, but if Skiplagged’s algorithm can sort through all the flight data for me, it saves a ton of time and money.
Yet, airlines were not happy about the service, with United Airlines going so far as to sue Skiplagged . An article in USA Today made the points that hidden city fares are against most airlines contracts of carriage and that if people are booking flight legs they don’t intend to use, they’re taking seats away from other potential fliers . I understand their argument, but it seems somewhat hypocritical for an airline to call foul about a website using publicly available data to find cheap fares, when airlines themselves are using opaque dynamic pricing methods to extract as much value as possible from customers.
It reminds me of big Las Vegas casinos banning card counters who are using nothing more than their brains and memory to gain an advantage.