Unit 3 · Creating Your Pricing Strategy · Lesson 3.3
Introduction to the pricing strategy
A complete pricing strategy is a small set of decisions written down in one place: how long each of the three steps runs, six price points covering hedge, control and test across midweek and weekend, seasonal rates, variable and seasonal minimum stays, an orphan night policy, cleaning fees, cancellation terms and length of stay discounts. This lesson walks through each element and the market data behind it.
The full lesson text below is an edited transcript of the video, published 2026-08-24. The complete course is free at the playbook.
The three steps and their lengths
The strategy starts by splitting the calendar ahead of you into three windows, measured in nights from today’s date. The hedge period covers the nights closest to check-in, and might run from today out to day seven. The control period picks up from there, perhaps day eight to day 30. The test period takes everything beyond it, day 31 out to day 365. These are lengths of time, not minimum stays, and those day counts are an illustration rather than a default.
Every market sets its own boundaries, because the booking window differs from market to market. Defining the length of each step for your own market is the first decision the strategy asks of you.
Six price points, not one
Each step carries its own price, and each price splits between midweek and weekend. That is six price points in total: a midweek and a weekend hedge price, a midweek and a weekend control price, and a midweek and a weekend test price.
All six come from data rather than instinct, and the check on each one is the same. Is this price defensible against what the market actually charges? A number well below the market gives revenue away. A number well above it takes the listing out of contention. The rest of this unit is about deriving each of the six from evidence instead of guessing at them.
Seasons, stays and the fine print
Seasonal pricing sits on top of the three steps, and high season is where a strategy either earns or loses the year. Charge too little and the best dates sell for less than they were worth. Charge too much and those dates either go unsold or sell late, at weaker prices, once the demand has already moved on.
Minimum stays come in two forms. Variable minimum stays change with distance from check-in, usually longer further out and shorter as the date approaches, set from what the market is actually booking. Seasonal minimum stays cover the periods that book differently from the rest of the year. Over the Christmas period in Australia, a stretch of two to three weeks, tourist markets take seven to fourteen night stays almost across the board. Summer does the same in much of the United States, as does winter in a ski destination. Those guests are not coming for a weekend, so find the periods where that is true and decide the right minimum stay for each.
An orphan night policy closes the hole your minimum stay rules create. Without one, vacant dates sit on the calendar in blocks too short for anyone to book, and the listing disappears from the searches those guests are running. Cleaning fees, cancellation policy and weekly and monthly discounts finish the picture. None of them win a booking on their own, and each of them can quietly cost you one, which is why the strategy sets them deliberately rather than leaving them wherever they happened to land.
Why the numbers belong together
Every element above can be worked out by reading market data chart by chart, or by exporting a file of individual dates and values and trying to make sense of it. Neither is a good use of your week. A strategy sheet exists to compress the same information into one concise table: enough to make the decision, and not one number more.
The final page of that sheet is the strategy itself, on a single page. Every step length, every price, every minimum stay, every fee and policy, sitting where you can see them together. Build one copy per listing and name it after the listing, because a portfolio of properties needs a strategy per property rather than an average across all of them.
Start with the market direction
Before any price is set, one number frames the rest: the 90 day year over year occupancy trend. It takes the 90 days that have just passed, compares them with the same 90 day range a year earlier, and tells you whether occupancy is running higher or lower than it was.
What you are reading is direction, not level. A market gaining occupancy supports a more confident rate strategy. A market that has given up more than 10 to 15 percent of its occupancy against the same period a year earlier calls for a more conservative one, because the demand that would have absorbed those rates is not there to absorb them.
Market occupancy needs the same care about which period you are reading. Occupancy on dates that have already passed is history, and a date range a year old is a weak guide to a decision you are making today. For dates far enough ahead, the useful figure is the occupancy the market is expected to reach, not the occupancy it has reached so far. Read the window that matches the dates you are actually pricing.
Compare naked nightly rates
One correction has to happen before your own rates can be compared with anything. Dynamic pricing tools such as PriceLabs collect booking data from your channel manager or from the booking channels themselves, and that data often carries the cleaning fee, occupancy taxes and service fees inside the booked amount. Divide a reservation total by the seven or nine nights it covered and the nightly figure you get is inflated by everything that was not the nightly rate.
Market booked rates do not carry those extras. Leaving them inside your own numbers makes your listing look far more expensive than it is, and every comparison built on top of it is wrong. Strip the fees and taxes out first, so what you compare is the naked nightly price against the market’s naked nightly price: apples with apples. This only applies to a listing with booking history behind it. A brand new listing has nothing to strip.
Percentiles anchor the prices
The hedge price is anchored on the lower half of the market: the 25th and 50th percentile rates, split midweek and weekend. Those percentiles describe where the price points in your market genuinely sit, which is what makes them a starting position rather than a guess.
The control price leans on different evidence depending on the listing. A listing with booking history should weigh its own booked rates most heavily, because they are the clearest evidence of what this specific property can achieve. A brand new listing has no such history, so market rates carry the decision instead. The test price then sits above the control price, expressed as a percentage increase on it, so you can see exactly how far you are reaching.
A sheet can suggest a price at each of these points, and a suggestion is all it is. Treat it as a hint about the right direction, not as gospel and not as advice. The decision belongs to the person who knows the market occupancy, the market rates and what has worked on this listing before, and that person is you.
How aggressive a season allows
Seasonal prices work from the same kind of evidence. Name the season, Christmas, Thanksgiving, the Fourth of July, summer, set its future date range, and the market data for that range returns the 50th, 75th and 90th percentile rates alongside two occupancy figures: what is on the books for those dates now, and what the same dates had reached a year earlier. From those you set the minimum price for the period, midweek and weekend, which is effectively a seasonal price floor.
How aggressive that price can be depends on two things: how far away the dates are, and how much of the demand has already arrived. A date range far in advance, where occupancy on the books sits well below where the same dates stood a year earlier, still has most of its demand to come, and it can carry an aggressive price. A date three days out whose occupancy already matches the same point a year earlier has almost no demand left to win, so the price has to be conservative to match. That is the aggressiveness factor, and it applies season by season rather than once across the year.