Unit 3 · Creating Your Pricing Strategy · Lesson 3.11
Seasonal pricing
Seasonal pricing is the mirror image of the three-step strategy: instead of protecting your low season, it sets prices for the stretches and single dates where demand runs above the market average. You find those dates on the occupancy and pricing graphs, split them into periods, and price each one aggressively against your comp set in proportion to the demand still to come.
The full lesson text below is an edited transcript of the video, published 2026-08-24. The complete course is free at the playbook.
What seasonal pricing covers
The three-step pricing strategy exists to address your low season, which is why that whole process began by hunting for the lowest occupancy period in the year. Seasonal pricing is the opposite exercise. Here you are setting prices for the periods with higher than average demand in the market: long stretches such as summer, or specific dates such as the holidays and the special events that run in your area.
The reason those periods are treated separately is to capitalise on the increased demand. That means pricing more aggressively than the three steps ever asked of you, at higher price positions relative to your comp set, because the demand exists to support it.
Finding the seasonal dates
The dates come off the same graph that produced your low season: future occupancy, bookings and cancellations for your comp set on the market dashboard in PriceLabs. The line that matters for this job is the final occupancy each date reached a year earlier, rather than the occupancy booked so far or the pace the market was running at the same point a year earlier. Plotted across the coming year, that line shows where the market actually ended up filling.
Scan it for stretches and single dates sitting above the rest of the year, and read the pricing graph alongside it. In a strongly seasonal market the elevated periods are obvious and there are many of them. Prices matter as much as occupancy at this stage, because a visible difference in prices inside one elevated stretch is the signal to split that stretch into separate periods rather than price it as a single block.
Keep your seasonal dates in the future. The strategy sheet reports both the current occupancy and the prior year’s occupancy for each set of dates, and the seasonal strategy is built off your comp set’s future prices, so a date that has already passed leaves you nothing to price against.
Splitting a December peak
In one sample market, occupancy is already elevated as early as December 15, and it stays elevated through Christmas and past New Year. Occupancy levels vary inside that run and so do the prices, so it is split into three periods rather than priced as one: the shoulder dates before the holidays, December 15 to 21; the holidays themselves, December 22 to January 1; and the shoulder dates after, January 2 to 6.
The next block runs from the start of January into February, where occupancy again sits above the rest of the year. That whole stretch, January 7 to February 13, goes in as a single period, with the week of February 14 to 21 isolated as its own, because the pricing graph shows that week running higher than the dates around it. The rest of the year is worked through the same way, and each set of dates is labelled as it goes in.
Once the dates are entered, the pricing and occupancy fields populate for every set, which is the confirmation that the input landed. The minimum price columns are the only thing still blank, and filling them is the next job.
What the graphs miss
The selection described so far runs purely on occupancy graphs and historical data. You know your own market better than any chart does, so note down the dates you already know to be high demand before you review the graphs at all.
Then research the demand that history hides. Concerts, school calendars and sporting events move a market and may not have run on the same dates before. Holidays whose dates shift, Easter above all, are the clearest case: historical data will not show them cleanly, because the dates they fall on differ year over year.
Lead time and aggressiveness
Defining the seasonal prices is the same exercise as the three steps: a weekday minimum and a weekend minimum for each set of dates, recorded in the strategy sheet. What you weigh for each set is the occupancy those dates finished at a year earlier, the occupancy already on the books, and your comp set’s prices, along with any shift in event or holiday dates that could move the demand.
Two columns guide the call. The first is days before check-in, the lead time or booking window for that set of dates. The second is the aggressiveness factor, which combines the current occupancy with the prior year’s final occupancy to show how aggressive you can be relative to the expected occupancy. A high factor means significant demand is still to come, and you can price close to the percentile equivalent of that expected occupancy. Where much of the expected occupancy has already materialised, less is left to win and the position comes down.
Three sets of worked prices
Take the pre-holiday shoulder first. Its weekdays finished at around 62% occupancy a year earlier. If nothing had booked yet, the percentile equivalent would be the 62nd, the midpoint between the 50th and the 75th percentile. But 18% of that expected occupancy has already materialised, so the position moves closer to the 50th percentile instead, putting the weekday minimum at $700. The weekends sit in a similar position with around 38% already materialised, and they still price between the 50th and 75th percentile with a bias toward the 75th, because decent occupancy remains to be won: around $900.
The holidays themselves, Christmas through New Year, are dates the market will nearly fully book, so the positions go higher. A weekday minimum of $1,500 lands between the 75th and 90th percentile with a bias toward the 75th, with the market already at 40% occupancy. On weekends, $1,800 sits closer to the 90th percentile, which makes sense against a higher expected occupancy of 92%.
The post-holiday shoulder is expected to finish closer to 80% on weekdays with 35% already booked, so its weekday minimum goes underneath the 75th percentile at $1,050. Its weekends carry a final expected occupancy of 93%, and $1,400 puts them slightly underneath the 90th percentile.
When demand runs thinner
Not every seasonal date is a peak. Some seasonal weekdays never go over 50% occupancy, and for those the right position sits underneath the 50th percentile. Whenever you drop below the median, check the pricing graphs in PriceLabs before committing to a number, so that going low is gauged against what the rest of the market is doing on those dates rather than guessed at.
Across a full year of nominated seasonal dates the occupancy ranges vary widely, and the price positions should vary with them. That variety is the point of doing the exercise date by date instead of applying one seasonal uplift across the whole calendar.