Latest / Pricing Power Podcast with Fexingo: How Businesses Set Prices, Raise Margins, and Win Customers / How Airlines Use Dynamic Pricing to Fill Every Seat
Transcript
- Lucas: So you book a flight from New York to London. You check on a Tuesday afternoon, see a price of six hundred dollars round trip. You come back Wednesday morning — it's eight fifty. Same flight, same seats left. What changed? Luna: And you're not alone — I think everyone has had that experience. It feels almost random. Lucas: It's not random at all. It's the result of a pricing system that's been refined over more than forty years. Airlines were doing dynamic pricing — they call it yield management or revenue management — long before any of us had heard the term. Delta, American, United — they all run on algorithms that adjust prices in real time based on who's buying, how many seats are left, and what competitors are doing. Luna: Right, so this is the original dynamic pricing. Not surge pricing from Uber — airlines beat them by decades. Lucas: Exactly. The core idea is: you have a fixed number of seats — a perishable product — and you need to sell them before the plane takes off. Every empty seat is revenue lost forever. But you also don't want to sell a seat too cheap to someone who would have paid more. So the system segments passengers into different fare classes — there can be twenty or more on a single flight. Luna: So you and the person next to you could have completely different fare classes, even if you booked at the same time? Lucas: Absolutely. The airline might have sold ten seats at three hundred dollars each to price-sensitive leisure travelers, then another ten at nine hundred to business travelers who need flexibility. The algorithm monitors how fast each class is selling and adjusts the number of seats available in each bucket. If business class tickets are selling faster than expected, it might pull some cheaper seats and move them into higher fare classes. Luna: So it's not just about price — it's about inventory allocation. How many cheap seats do you release, and when? Lucas: That's the whole game. And it's incredibly sophisticated. The system uses historical data, current booking patterns, competitor pricing, even things like weather forecasts and major events. For example, if there's a big conference in London, the algorithm knows demand will spike and will hold back cheap seats earlier. Luna: I remember reading that American Airlines alone runs over a million price changes per day. That's per airline. Lucas: Yeah, the scale is enormous. Delta has a revenue management system called DeltaMath — not to be confused with the math software — that dynamically adjusts fares. They also have a team of analysts who override the algorithm when needed, say for competitive moves or unusual events. But ninety-five percent of pricing decisions are automated. Luna: And you mentioned the perishable nature — that's key. A hotel room is also perishable, but airlines have more complexity because of connecting flights, different fare rules, and the fact that passengers might not all fly the same route. Lucas: Exactly. The network effect makes it harder. If you're pricing a nonstop from Chicago to Dallas, that's one thing. But when you have people flying Chicago to Austin via Dallas, you have to consider the value of each segment. The system has to allocate seats across the whole network to maximize overall revenue. Luna: Interesting. Lucas: So let's talk about a specific example. In 2015, United Airlines introduced what they called 'Basic Economy' — a lower fare class with restrictions like no seat selection and no carry-on bag. That wasn't just a new product; it was a pricing innovation. By creating a more restricted fare, they could better segment price-sensitive travelers from those willing to pay more for flexibility. The algorithm could then steer bargain hunters into Basic Economy while keeping higher fares for others. Luna: That's a smart way to add a lower price point without cannibalizing your premium seats. And it also gives you more inventory to play with. Lucas: Right. And it worked so well that Delta and American quickly copied it. Now almost every major US airline has a version. That's a classic example of how pricing structure — not just price level — drives revenue. Luna: Speaking of which — I want to ask about something that always puzzles me. Why do airlines sometimes drop prices really close to departure? Like, two days before a flight, I've seen fares go down. Lucas: That happens when the algorithm forecasts that there are still too many unsold seats. The perishable nature kicks in — an empty seat is worth zero. So the system will lower prices to fill those seats, even if it means selling below cost. But it's not universal. On a flight that's nearly full, prices will actually go up as departure approaches, because the remaining seats are being bought by last-minute business travelers who will pay anything. Luna: So it's not a simple 'book early get the best price' rule. It's more complex than that. Lucas: Much more. The shape of the price curve depends on the route, the time of year, the day of week, and how demand unfolds. For leisure routes to Orlando, prices tend to rise as the flight fills. For business-heavy routes like New York to Chicago, prices often drop closer to departure if demand is weak. The algorithm is constantly learning. Luna: I remember reading about a study that showed airlines could increase revenue by five to eight percent just by optimizing pricing algorithms. That's huge. Lucas: It's massive. For an airline like Delta, that could be an extra one point five billion dollars a year. That's why they invest so heavily in these systems. In fact, Delta has a whole subsidiary called Delta Air Lines' Revenue Management — it's essentially a tech company inside an airline. Luna: And this isn't just about ticket prices. They also use dynamic pricing for upgrades, baggage fees, even onboard Wi-Fi. Everything is yield managed. Lucas: Exactly. The same principles apply. For upgrades — say from economy to premium economy — they'll offer a price that depends on how many seats are left and how likely it is someone will pay full fare. It's all connected. Luna: Alright, so if these systems are so effective, why do consumers get frustrated? Why does it feel like a game? Lucas: Because it is a game. Airlines are using price discrimination to extract maximum willingness to pay. That can feel unfair. But from an economic standpoint, dynamic pricing is actually more efficient — it helps fill planes, which keeps average fares lower for everyone than they would be if all seats were the same price. Luna: Yeah, that's a good point. If airlines had one fixed price, they'd either price too high and leave many seats empty, or price too low and leave money on the table. The dynamic system balances that. Lucas: Look, I'll give you a quick example. This is the perfect moment to mention something — this podcast itself is a bit like that. We keep it ad-free because a handful of listeners chip in monthly through buy me a coffee dot com slash fexingo. That support literally funds making this many episodes. It's not a big ask — just a fact about how we keep the lights on without selling your attention. Luna: And we're grateful for it. It lets us dive deep into topics like this without any sponsor pressure. Lucas: Exactly. So back to airlines — the other interesting piece is how they compete. You might think dynamic pricing would lead to a race to the bottom, but it doesn't. Because each airline's algorithm is reacting to the others, you get a kind of tacit coordination. Prices tend to converge around a similar level, because if one airline drops its price, the others match within minutes. Luna: That's actually a concern for regulators. There have been investigations into whether revenue management systems facilitate collusion. Lucas: Yes, the Department of Justice has looked into it. But it's hard to prove collusion when each airline is independently optimizing. The algorithms aren't communicating — they're just responding to the same market signals. So you end up with prices that move in lockstep, but arguably that's just competition. Luna: It's a fascinating gray area. And it's only going to get more sophisticated with machine learning. Some airlines are already testing AI models that incorporate real-time social media sentiment or weather data. Lucas: Yeah, the next frontier is personalized pricing. Imagine the airline knows your travel history, your loyalty status, maybe even your willingness to pay based on your browsing behavior. They could offer you a different price than someone sitting next to you — and legally, they can. Luna: That's a bit unsettling for consumers. But it's already happening in other industries. Lucas: It is. And airlines are careful about it — they don't want a backlash. But the technology exists. Right now, the main differentiator is still fare class and booking channel. But give it another five years, and we might see truly personalized airfares. Luna: So for the average traveler, what's the takeaway? How can you outsmart the algorithm? Lucas: Honestly, it's hard. But there are a few rules. One: check prices in incognito mode — some studies show airlines may track your searches and raise prices if you come back. Two: be flexible with dates and times. Three: book on Tuesday afternoons, historically when airlines release new fares. Luna: And four: don't obsess. The difference between a good price and a great price is usually small. The algorithm is designed to extract the maximum, but it's also designed to fill seats, so there are often deals if you're patient. Lucas: Right. At the end of the day, dynamic pricing has made air travel more accessible and more profitable. It's a win-win if you understand the rules. The key insight for me is that airlines were doing this decades before anyone else — and they're still the masters of it. Luna: I think that's a great note to end on. Next time you see a price change, you'll know exactly what's happening behind the scenes. Lucas: Exactly. Thanks for listening — and if you want to support more deep dives like this, you know where to find us.