posted: September 17, 2023
tl;dr: Dynamic pricing algorithms are determining a growing percentage of the prices we pay...
I walked into a trap on a recent trip to Seattle, to visit a relative. We wanted to attend a Seattle Mariners game, and a Saturday afternoon game was the most convenient option. The Mariners play most of their Saturday home games in the evening, but there was one Saturday game in mid-July where they had scheduled an early afternoon start. Perfect: that was the weekend I chose for my trip. In retrospect, that was also the decision I made to wander into the trap. I never bothered to research why the Mariners had scheduled an afternoon game on that particular day.
The first thing I booked was my airline tickets. The price was the highest I have ever paid for roundtrip tickets between Phoenix and Seattle, and about three times the price of the tickets for my last trip, which was in early February. I thought that was strange, but I also knew that my February trip had been a bargain, as few people travel right after the Christmas and New Year’s holidays. The summer of 2023 was a banner year for travel in the United States, as people were catching up on trips delayed by the COVID-19 endemic. So I didn’t think it was too unusual.
Weeks later I booked my hotel room. The hotel that I had stayed at in February was more than twice the price, and there were only a handful of rooms available. I ended up booking a room at a nearby, slightly cheaper hotel that was also much higher than normal for that weekend. I looked at a graph of average hotel room prices in Seattle for the month of July, and the weekend I had chosen was significantly higher than all the other days. I bought tickets to the baseball game, and those prices were also much higher than normal, with very little availability even on the secondary market.
Clearly something was going on in Seattle that weekend. It was mid-summer, so it wasn’t the Super Bowl: the NFL and college football seasons hadn’t even started yet. I did some online searching, and could find no major festivals going on in Seattle that weekend. I gave up trying to figure out what else was going on that weekend.
It wasn’t until I had flown on a completely full plane to Seattle and gotten to the lobby of the hotel that I finally got my answer, after asking the desk clerk: Taylor Swift was in town. She was giving nighttime concerts in the huge football stadium immediately adjacent to the Mariners’ ballpark. That was probably why the Mariners scheduled a day game on Saturday, to avoid having two events at exactly the same time in nearly the same place.
To make matters worse, the Mariners were playing the Toronto Blue Jays, who are MLB’s only Canadian team and therefore function as Canada’s national team. There are Canadians who live on Canada’s west coast who root for the Blue Jays, even though their home stadium is three time zones away. The series with the Mariners was the sole opportunity for these fans to see their team that year, and they turned out in force at the sold out game. Furthermore, at that point in time Taylor Swift had not scheduled any concerts in Canada for her tour. Thus this was also the best opportunity for west Canadian Taylor Swift fans to see their idol.
It was a Canadian invasion. I have never seen so many Canadians in one city outside of Canada. I daresay that if a similar number of Russians turned up in a single city in the United States, it would be a national security incident and the military would get involved.
Huge demand from Swifties and Canadians (and especially Canadian Swifties) ran headlong into a limited supply of flights, hotel rooms, and tickets. As per Economics 101, that led to a dramatic rise in prices, to discourage some people from attending. Thanks to software-based dynamic pricing algorithms, this all could and likely did happen automatically.
Companies closely guard their pricing algorithms, so I can’t say for certain whether or not someone informed the algorithms well in advance that Taylor Swift was coming to town. But all they would have to do is measure the initial demand. As soon as they notice an uptick in demand for particular dates, either through searches or actual purchases or both, they can raise the prices that others see in the future for those dates. If prices go too high and demand starts to slack off, they can adjust the prices downwards. The goal is to sell all the available products (every ticket and hotel room) for the maximum overall amount of money. The algorithms have gotten quite good at doing this.
Dynamic pricing algorithms are why prices change day to day and even hour to hour. It’s why airline tickets for the same pair of cities on the same day usually are different for many of the flight options, and seat options. There is more demand for certain times of day, certain seats, and for non-stop flights, although lower prices for more indirect routes need to be balanced against the higher operational costs of flying someone on multiple flights. So cost, and opportunity cost, also figures into some of the algorithms.
The days of teams of human beings setting prices are fading into history. It used to be that tickets prices to MLB games were set before the start of the season, and the only price difference was for the location of the seat. Then teams realized they could charge higher prices for certain opponents. Then they realized that certain days of the week had higher demand than others. Then the algorithms took over, and it became hard for fans to know what the price for any given game would be except by checking. I’ve seen teams charge more tickets on giveaway days: that free bobblehead is not exactly free, as you may have paid for it in the price of your ticket.
The old days of pricing were simpler, but dynamic pricing algorithms do a much better job of charging whatever price the market will bear.
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