![]() ![]() “So the pandemic, which brings a lot of unexpected outlier events, also affects the input data of models like this and makes it a more challenging environment.” “Machine learning likes to learn from old and past repeatable patterns, and make predictions based on the likelihood of those patterns working again,” Zacharia says. That means that, at some low points, waiting or buying when the website told you to was less likely to have led to the lowest possible price-and could have led, instead, to some light fist-shaking toward the sky. He says that the accuracy of the prediction tools, which is generally around 85 percent, may have periodically dipped in the last few years-maybe closer to 83 percent. While the prediction algorithm, first launched in 2013, usually needs adjusting every few years, he says, the past two have seen “serious retraining” every few months, and sometimes every few weeks. Giorgos Zacharia, president of online travel agency and search engine Kayak, says he has a team of MIT PhDs who spend their working lives tending to the website’s price-prediction tool. Automated systems play their part here too: If one airline reduces prices on one route, another airline might pick up on the shift and immediately reduce its prices. Once those go, another bucket opens up at a different price. This is often due to a system called “fare buckets,” where a group of seats will sell at one price. Even after an airline prices out its schedule, the passenger sitting in seat 18A may have paid hundreds more for their trip than the passenger in 18B. An entire class of airline-employed data analysts, who work in a field called “revenue management,” work to anticipate who will want to go where when, and they set schedules, routes, and prices accordingly. ![]() For passengers, buying a plane ticket can feel like a mix of magic and luck, and the current unpredictability could add a touch more confusion-and frustration-when planning a trip.Īirlines establish airfares through art and science. That means that even the most tech-savvy buyers could be paying a little more than is optimal to take to the skies. And the more sophisticated ones will make a recommendation: Buy now, or wait.īut some unprecedented strangeness in air travel has led to unprecedented strangeness in price prediction, some executives say. Generally, these tools will tell a prospective air traveler whether prices for their targeted route are high or low, or somewhere in between. The platforms are trained on the arcane rules of airfare, plus reams of historical data, and use that to hazard when customers should buy to get the best ticket price. These are one of the original Big Data projects. These tools-built by companies like Hopper, Kayak, Google Flights, Skyscanner, and others-are machine learning algorithms. In normal times, people often turn to airfare prediction products to tame the madness. Factor in a waterfall of flight cancellations and schedule rearrangements, due to weather plus all of the above, and you’ve got a weird moment in air travel. Another is a shortage of air-travel-industry workers. Another is high fuel prices, spurred upward by the war in Ukraine. Part of that is pent-up demand from people sick of their homes after a still-not-over pandemic. ![]() The average round-trip ticket price in the US was $408 this week, up $100 from the same time in 2019, according to the airfare sales app Hopper. ![]()
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