Latest / Pricing Power Podcast with Fexingo: How Businesses Set Prices, Raise Margins, and Win Customers / How Dynamic Pricing Won the Stadium Concession War
Transcript
- Lucas: So you go to a basketball game in 2026, you walk up to the concession stand, and the price of a hot dog on the digital menu board isn't the same as it was when you walked in. If the home team is on a run, that hot dog costs more. If it's a blowout in the third quarter, it might cost less. Luna: Wait — you're saying the price actually changes during the game? Lucas: Yes, and it's not a test. It's been rolling out across major venues since about 2024. The company leading this is Delaware North — they operate concessions at places like TD Garden in Boston, Madison Square Garden, and a bunch of NFL stadiums. And they've been quietly switching from static pricing to what they call 'event-based dynamic pricing.' Luna: So it's like Uber surge pricing, but for nachos. Lucas: Exactly. But the interesting part is that the data so far suggests it works — not just for the operator, but in a weird way for the fan too. Let me give you the number that caught my attention. In the first full year of dynamic pricing at TD Garden, Delaware North reported that per-transaction spending at concessions rose by roughly 18 percent, while total attendance didn't drop. That's the holy grail: higher revenue without losing customers. Luna: But how do they change prices in real time? Is someone standing behind the counter with a tablet watching the score? Lucas: Pretty close. The system is built on a software platform that ingests a bunch of data feeds: the live score, time remaining, how many people are in the building — which they know from ticket scans — even weather data for outdoor venues. It runs a demand forecast model and pushes new prices to digital menu boards every few minutes. The algorithm is basically saying: 'Right now, demand is spiking because it's halftime, supply of hot dogs is fixed, so price goes up.' Or 'It's the fourth quarter and the game is a blowout, people are leaving early, so discount a bit to clear inventory.' Luna: And fans haven't revolted? Because memory serves, when Coca-Cola tried something similar with vending machines that raised prices in hot weather back in the late 90s, people were furious. Lucas: Right — that was the Coke machine that would raise the price when the temperature went up. It was a PR disaster. But this is different in two ways. First, the price moves are smaller and more frequent. We're not talking about a $5 hot dog jumping to $15. Usually the range is maybe $1 to $2 either direction. Second, the context matters: at a stadium, people already expect to pay a premium. It's a captive market. The question is whether the algorithm respects a ceiling — a psychological price above which people feel ripped off. Luna: That ceiling seems to be around $9 for a hot dog, based on what I've seen at games. Once it hits $10, people start tweeting complaints. Lucas: Exactly. And the smart operators know that. Delaware North isn't trying to maximize every single transaction to the moon. They're trying to capture more of the consumer surplus that already exists. Think about it: at a sold-out playoff game, a fan might be willing to pay $12 for a beer because they're excited and they've been waiting in line for ten minutes. But the same fan on a Tuesday night against a last-place team would balk at $10. Static pricing leaves money on the table in the first case, and chases away customers in the second. Luna: So you're smoothing demand. You charge more when demand is high and less when it's low, and overall you sell roughly the same volume but at a higher average price. Lucas: Exactly. And there's a second-order effect that's even more interesting. When prices drop in the fourth quarter of a blowout, you actually get people who were on the fence about buying a second beer or a snack to go for it. So you increase volume during low-demand periods. The net result is both higher revenue and less waste — because perishable inventory like prepared food doesn't get thrown away as often. Luna: But there's a trust issue here, right? If fans feel like the algorithm is gouging them, they might stop buying altogether, or worse, stop coming to games. How do you manage that? Lucas: That's the biggest risk. And it's why Delaware North has been very careful about transparency. At TD Garden, they actually display a message on some of the digital boards that says something like 'Prices adjust based on demand to offer you the best value.' Which is a bit of a corporate spin, but the point is they're not hiding it. They want fans to understand that the same hot dog could be cheaper in the fourth quarter than it was at tip-off. That 'deal' feeling can actually build goodwill. Luna: Interesting. So it's almost like a gamified pricing experience — you can 'win' by buying at the right time. Lucas: Exactly. And there's precedent for this in other industries. Airlines and hotels have been doing yield management for decades. But the difference is those are purchases you make in advance. This is in-the-moment, with a captive audience. The psychology is more delicate. If a hotel room costs more tonight than last night, you don't find out until you book. But if a beer costs more in the third quarter than it did in the first, you might notice because you just bought one an hour ago. Luna: So the recency effect makes price changes more salient. That's a real challenge. Lucas: Right. And that's why the algorithms are tuned to avoid large jumps within a short window. You don't want a fan to see the price go up while they're standing in line. So the system updates at natural break points — between quarters, at halftime — and tries to keep changes within a band that feels reasonable. Luna: I wonder how far this goes. Could we see dynamic pricing for everything — merchandise, parking, even ticket prices themselves? Lucas: We already do, to some extent. Ticket prices have been dynamically priced for years — the big platforms like Ticketmaster use it. But for merchandise and parking, it's coming. In fact, some NFL teams are already testing dynamic pricing for parking based on how many cars are in the lot and how much time is left before kickoff. The logic is the same: perishable inventory, time-sensitive demand. Luna: It does make me wonder where the line is. I mean, at some point, the fan experience could start to feel like being in a financial market, where you're constantly checking prices and timing your purchases. Lucas: And that's the tension. On one hand, dynamic pricing can actually benefit consumers who are price-sensitive — they can wait for a discount. On the other hand, it can feel manipulative. The key variable seems to be transparency. If people understand the rules, they're more accepting. If they feel like they're being tricked, they rebel. Luna: And the companies that get that balance right could build a real competitive advantage. Especially as more venues adopt the technology. Lucas: Absolutely. And this is actually a great moment to mention something about this show. We keep these conversations ad-free because we think that makes them more useful and honest. If you've gotten value from episodes like this one — maybe it's helped you think about pricing in your own work — and you'd like to support that approach, there's a link at buy me a coffee dot com slash fexingo. No pressure, just a way to keep it going. Luna: Yeah, it's a small way to keep the show independent. We appreciate those who do. Lucas: So back to the stadium. One thing I think is underappreciated is how much data the venues now collect. Every digital transaction, every scan, every time a fan lingers in front of a menu board — that's all feeding the model. Over time, the system gets better at predicting demand not just by game, but by opponent, by day of the week, by weather, even by which player is having a hot streak. Luna: So you could have a scenario where LeBron James is playing in your arena, and the algorithm knows that beer sales spike 30 percent during his minutes — so it raises prices during his shifts. Lucas: Exactly. And that's not science fiction. That level of granularity is already being tested in a few venues. The question becomes: does the fan notice? And if they do, does it change their behavior in a way that hurts the overall experience? Luna: I think the answer might depend on how the savings get passed back. If a fan can get a cheaper hot dog in a blowout, they might feel like they won. But if the only message is 'prices are up because LeBron is on the court,' that feels like a tax on excitement. Lucas: Right. And that's where pricing strategy meets brand strategy. The best operators will use dynamic pricing not just to extract revenue, but to create moments of value that build loyalty. For example, if you have a loyalty app, you could send a push notification in the fourth quarter: 'Hot dogs are now $2 off for the next 10 minutes.' That's a win-win. Luna: That's actually a great way to turn a potential negative into a positive. You're using the price signal as a tool to engage fans. Lucas: Exactly. And that's the frontier. The companies that figure out how to make dynamic pricing feel like a service rather than a toll will own the next decade of concession revenue. I think we're going to see a lot of experimentation over the next two or three seasons, and by 2028 or so, it'll be the norm. Luna: So next time I'm at a game and the hot dog costs less in the fourth quarter, I'll know who to thank — or blame. Lucas: Blame the algorithm. But keep the receipt. It might be worth more later.