Revenue ManagementRates and pace

Forecasting demand for the months ahead

A day by day view of how full you expect to be, what you expect to charge, and which days are worth defending. It reads your existing bookings forward; you cannot edit anything on it.

Where to find it
Revenue ManagementForecasting
Last checked
August 16, 2026

Demand Forecasting projects your next 30, 60 or 90 days one day at a time: how full you expect to be, what you expect the average room to sell for, and which days are busy enough to be worth protecting. It is a reading screen. There is no field on it you can change and nothing on it writes a rate.

That makes it the screen to open before you go and change something else. A rate change you make on the rate calendar or a boundary you set in Autopilot is a decision about a specific set of dates, and this is where you work out which dates those are.

The Demand Forecasting screen: a 30, 60 and 90 Days control at top right, a row of five tiles, a line chart of occupancy across the horizon, a demand distribution panel beside a revenue forecast by room type chart, and a day by day forecast table beneath.
Five tiles, one chart, two panels and the table that holds the detail. The horizon control at top right changes all of them at once.
  1. The horizon control. Everything below it redraws when you change it.
  2. Five tiles summarising the whole horizon.
  3. One metric plotted across the period, with three metrics to choose from.
  4. The day by day table, which is where the detail is.

What the forecast is, and what it is not

The forecast is built from the reservations you already hold, projected forward. It is not a market prediction and it knows nothing about your competitors, the weather or what is on in town. A day shows as quiet because few people have booked it yet, which is not the same as a day nobody wants.

This matters most at the far end of a 90 day horizon, where almost nothing is on the books yet and almost every day will read Low or Medium. That is the booking window, not the demand. The nearer half of any horizon is the half worth acting on.

Choosing how far ahead to look

The 30 Days, 60 Days and 90 Days buttons at the top right set the horizon, and every tile, chart and table row on the screen is recalculated from it. The period always starts tomorrow: today is in progress and a part-finished day would drag the averages down.

The change indicators under the first three tiles compare against the window immediately before the one you are looking at, of the same length. So a 30 day forecast is compared against the previous 30 days, and a 90 day forecast against the previous 90. Switching the horizon therefore changes what you are comparing against as well as what you are looking at, which is why the percentages move when you press a different button. The forecast has not changed; the yardstick has.

The five tiles

The five forecast tiles: average occupancy 76 percent, average ADR USD 332, average RevPAR USD 252, total revenue USD 908K, and peak demand days 3 of 30 days. The first three carry a red downward change against the last period.
Every tile is an average across the horizon you chose, except Total Revenue, which is a sum, and Peak Demand Days, which is a count.
TileWhat it is, and what it is not
Avg. Occupancy The mean of the daily occupancy forecasts across the horizon. Every day counts equally, so one sold-out weekend does not pull it up the way it would pull up a revenue total.
Avg. ADR The mean of the daily average rates. Note that this is an average of averages, not total revenue divided by total room nights, so a busy day and a quiet day weigh the same in it.
Avg. RevPAR Revenue per available room, averaged the same way. It falls when either occupancy or rate falls, which is why it is the tile that moves most.
Total Revenue A sum, not an average: every day's forecast room revenue added together. It scales with the horizon, so it roughly triples between 30 and 90 days and cannot be compared across horizons.
Peak Demand Days How many days in the horizon reached the Peak level, with the horizon length beside it. This is the tile to read first: it is the count of days worth defending.

A red downward arrow on the first three tiles is not automatically bad. It compares a future window against a past one, and if the past window contained your peak weeks then a fall is the season ending rather than a problem.

The chart, and its three metrics

The chart plots one metric across the whole horizon. Occupancy %, ADR and RevPAR switch which one. The axis relabels itself, so you can tell which metric you are looking at without reading the buttons.

The forecast chart with Occupancy %, ADR and RevPAR buttons above it and Occupancy % selected, showing a blue line running between roughly 65 and 90 percent across thirty days from Aug 16 to Sep 13, with a weekly rise and fall.
The same thirty days drawn three ways. Switching the metric redraws the line and the axis; it does not change the horizon.

What the chart is good for is shape rather than value. The regular sawtooth in the occupancy line is your week: the peaks are Fridays and Saturdays, the troughs are midweek. A dip that breaks the pattern is worth looking up in the table.

The same forecast chart with ADR selected instead of Occupancy %, showing a green line between roughly USD 290 and USD 390 across the same thirty days, on an axis running USD 0 to USD 400 rather than 0 to 100 percent.
ADR on the same thirty days. The axis relabels itself to the metric, which is how you tell at a glance which one you are looking at.

Comparing the occupancy line against the ADR line is the most useful thing on this chart. Where both rise together you are pricing into demand correctly. Where occupancy rises and ADR stays flat, you are filling those days at your ordinary rate and leaving money on the table.

Demand distribution and room type revenue

The Demand Distribution panel listing Peak 3 days at 10 percent, High 22 days at 73 percent, Medium 5 days at 17 percent and Low 0 days at 0 percent, each with a coloured bar, beside a Revenue Forecast By Room Type bar chart with a bar for each of the six room types.
How the horizon breaks down by demand level, and which room types the forecast revenue is expected to come from.

Demand Distribution counts the horizon into four demand levels, with the number of days and the share of the period. It answers a question the chart cannot: not how full you will be on average, but how lumpy the period is. Twenty-two High days and three Peak days is a steady month. Three Peak days and twenty-two Low days is the same average and a completely different problem.

Revenue Forecast By Room Type splits the forecast revenue across your six accommodation types. The bars are driven by how many of each type you have as much as by what they charge, so your largest inventory usually leads even when it is not your most expensive room.

The day by day table

The first ten rows of the day by day forecast table, with columns for date, day, demand, occupancy forecast, ADR, RevPAR, room nights and revenue. Each demand cell carries a coloured badge reading Peak, High or Medium with an icon.
One row per day. The demand badge is derived from the occupancy forecast in the next column, so the two always agree.

One row per day, and this is where the decisions get made. The demand badge is derived from the occupancy forecast in the very next column, using fixed thresholds:

Demand levelForecast occupancy
Peak85% and above
High70% to 84.9%
Medium50% to 69.9%
LowBelow 50%

Because the badge is only ever a restatement of the occupancy column, the two can never disagree. If you find yourself reading both, read the occupancy figure: it tells you how close to a threshold a day is, and a day at 84.8% is a Peak day that has not been rounded up rather than a High day.

Room Nights and Revenue are the same forecast expressed as volume and money. Revenue is rounded to the nearest thousand in the column, so adding the visible figures will not match Total Revenue exactly.

Why a day reads the way it does

Clicking any row expands it and shows the drivers behind that day. Nothing on a closed row indicates this, so it is easy to use the screen for months without finding it.

A forecast row expanded to show its demand drivers as small grey tags beneath the date: Peak season, Weekend premium and High demand.
Clicking a row shows why the forecast reads the way it does for that day. Nothing on the closed row hints at this.
DriverWhen it appears
Peak seasonThe date falls in July, August or December.
Weekend premiumThe date is a Friday, Saturday or Sunday. Friday counts because it sells like a weekend night, not because it is one.
High demandForecast occupancy is above 80%. This overlaps the Peak badge deliberately: a day can be busy without being a Peak day.
Holiday periodThe date falls in December, so it appears alongside Peak season for that month.
Baseline demandNone of the above applied. It means there is no particular reason for this day to be busy, which is itself worth knowing.

The drivers explain the shape of the forecast rather than producing it. The occupancy figure comes from your bookings; the tags tell you which of the predictable patterns that day sits in. A Peak day carrying only Baseline demand is the interesting case: it is full for a reason the system cannot see, which usually means something is on locally and your rate is too low.

Using the forecast to set rates

The forecast does not change prices. Everything you decide here is carried out on another screen:

  1. Read Peak Demand Days and the distribution panel to see how many days are worth acting on. If the answer is two, this is a ten minute job rather than a rate strategy.
  2. Find those days in the table and expand them. A Peak day with no seasonal or weekend driver is the one to look at hardest.
  3. Raise the rate on individual nights on the rate calendar, which is covered in Overriding a night's rate, and reading pickup and pace.
  4. For a pattern rather than a handful of nights, set the boundaries and let the engine work, which is covered in Automated pricing with Autopilot.

Common questions

  • Why do the percentage changes on the tiles move when I switch the horizon?

    Because the comparison window changes with the horizon. A 30 day forecast is compared against the previous 30 days and a 90 day forecast against the previous 90, so pressing a different button changes both the period you are looking at and the period it is measured against. The forecast itself has not moved.

  • Why does almost every day at the end of a 90 day horizon read Low?

    Because the forecast is built from bookings you already hold, and very few people have booked three months out. That is your booking window rather than a demand problem. Act on the nearer half of the horizon and treat the far end as a placeholder that will fill in.

  • Can I change a rate from this screen?

    No. Demand Forecasting is read-only. Change the price of individual nights on the rate calendar, or set boundaries and strategies in Autopilot and let the engine move rates for you.

  • Does the forecast account for events, weather or competitor pricing?

    No. Prostay holds none of that data. The forecast projects your own reservations forward and labels each day with the patterns it can see, which are the season, the day of the week and how full the day already is.

  • The menu says Forecasting but the page says Demand Forecasting. Are they the same screen?

    Yes. Forecasting in the Revenue Management menu opens the screen titled Demand Forecasting. There is only one forecasting screen in the module.

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