Taylor Swift announced concert dates. One operator didn't react. $200/night. Everyone around them: $1,000.
This actually happened. Not with a hotel. With a vacation rental operator who had the right properties, in the right location, at exactly the wrong price.
By the time they noticed the spike, their calendar was already full. Booked solid at a rate that made sense on a normal weekend. This wasn't a normal weekend. And the revenue they left behind could have covered an entire slow season.
Spikes are visible before they hit your calendar
Concert announcements. Sporting events. Festivals. Conference bookings. These don't appear out of nowhere. They show up in search traffic weeks before the first reservation lands. They show up in booking lead times. They show up in the behavior of people looking at your market from cities they don't usually come from.
"People from Seattle will come to the Super Bowl."
— Conrad, revenue management consultant
That's demand that's visible, trackable, and worth acting on before a single booking request comes in. But only if you're looking.
Most operators aren't. Not because they're lazy or careless. Because nothing in their current stack tells them to look. Their pricing tool adjusts based on comp sets and historical data. Their PMS shows what's already booked. Their channel manager distributes rates they've already decided on.
None of those tools say: "Hey, something unusual is happening in your market right now. Traffic from Austin just tripled. Search volume for your dates is up 400%. You might want to take a look."
The math on missed spikes
Let's say you have five properties in a market that gets hit by a demand spike twice a year. Maybe it's a marathon, a music festival, a graduation weekend at the nearby university.
On a normal weekend, you're getting $250/night across those five properties. On a spike weekend, the market can absorb $600, $800, sometimes over $1,000. That's not price gouging. That's the rate guests are actively willing to pay because supply is constrained and they need to be there.
Miss two spike weekends a year on five properties, and the difference between $250/night and $750/night across those weekends adds up to $20,000 in revenue you earned on paper and never collected.
And here's the part that stings: your neighbors did. The operator two blocks over adjusted their rates three weeks before the event. They captured the full spike. Same market, same properties, same guests. Different outcome.
Last year's data is not this year's demand
Most pricing tools anchor to historical performance. What did this weekend look like last year? What's the comp set doing right now? That's useful. It's a reasonable baseline.
It's also backward-looking by design.
A new festival gets announced. A team makes the playoffs for the first time in a decade. A conference that was always in Chicago moves to your city. None of that shows up in last year's data. Your pricing tool doesn't know. Your comp set might not have reacted yet. And by the time Airbnb's algorithm catches up, half your spike nights are already booked at your default rate.
"PriceLabs is my baseline, the rest just comes from intuition of knowing my market."
— Top-performing host, Reddit
That's honest. And for a single operator with two or three listings in a market they've lived in for years, intuition works. Sometimes.
It doesn't scale. You can't intuit demand spikes across 20 properties in three markets. You can't intuit that a K-pop group just announced a tour date in your city and fans from across the country are already searching for accommodation. That's not a gut feeling. That's a signal. And signals need to be captured in real time.
Reactive vs. real-time
The difference between operators who capture demand spikes and operators who miss them is not intelligence or effort. It's timing.
Reactive operators see the spike when their calendar fills up. They realize the market moved, but their rates didn't. The bookings look good on the surface. Occupancy is high. But the revenue per night tells a different story.
Real-time operators see the spike when the search traffic shifts. Before the bookings. Before the comp set reacts. Before the OTA algorithm adjusts. They have a window, sometimes days, sometimes weeks, where they can position their rates to capture the full value of what's coming.
That window is worth 3x to 5x on the right nights. And it's invisible to anyone who's only looking at their booking calendar.
The operator who booked at $200 while the market paid $1,000 wasn't doing anything wrong. They were doing what most operators do. Setting rates based on what they knew, which was what happened last year and what their tool suggested.
The problem wasn't their process. The problem was their visibility. They couldn't see what was already happening in their market until it was too late to act on it.