Most short-term rental intelligence is modelled from comparables: listings observed from the outside, by a company that has never taken a booking. That is a reasonable way to estimate a market and an unreliable way to underwrite a purchase, and it is why buyers treat these figures as indicative rather than dependable.
Stayful is a management company. We forecast a property’s income, then — for the ones we take on — operate it and find out what it really earned. This page is the whole of that: every source we use, how the number is assembled, and the record of where our forecasts landed against Jan–Dec 2025 reality.
Two of these we generate ourselves by operating properties. The rest we license or take from public registers. Each entry says what it contributes and where it runs out — a source with no stated limit is a source nobody has examined.
Nightly rates, occupancy, cleaning and turnaround costs from the UK short-lets we manage ourselves. Observed, not inferred — but it only covers the markets we operate in.
Bookings taken on our own channels, which is the only way to see what a night actually earns once the platform's cut is removed.
Active listings near the postcode. Strong on what a market looks like from the outside; it cannot see a listing's real costs or cancellations.
Sale prices and rental benchmarks, used for yield-on-cost and the long-let comparison. Lags the market by the length of a conveyance.
What is actually near the property. Good coverage in cities, thinner in rural areas.
Scheduled events that move nightly rates. Catches arenas and festivals; misses private and unticketed demand.
Official floor area and energy rating, which feed running costs. Only as current as the last assessment.
Who else is operating at scale in the area. Statutory filings, so accurate but slow.
Not a black box. Four steps, in order, and you can argue with any of them.
Live comparables near the postcode set the range. This is the same class of data every platform in the category works from, and on its own it is a guess about a property nobody has operated.
Size and efficiency from the EPC register, amenities and location from Google Places, event-driven demand from the calendar. A three-bed on a main road and a three-bed on a green do not earn the same, and comparables alone cannot see the difference.
Cleaning, turnaround, platform fees and management come off the top using the rates we pay on our own portfolio — not a percentage assumption. This is where a headline revenue figure and an owner-net figure stop resembling each other.
Because we manage short-lets ourselves, a forecast is not the end of the process. Twelve months later we know what the property did, and that variance goes back into the model and onto the ledger below.
Six properties Stayful took under management in 2025. For each, the Income Estimate we produced before it went live, next to twelve months of real bookings. No retro-fitting, no cherry-picked month.
n = 6 · Forecasts produced pre-onboarding, Nov 2024 – Feb 2025 · Actuals from Airbnb host dashboards and Stayful direct bookings, Jan–Dec 2025 · Owner net is after platform fees, cleaning and management · Occupancy variance is in percentage points. Six properties is a small sample, and past results are not a forecast.
Occupancy runs slightly high. On five of the six, the property was occupied a little less than we projected — by 3.2 points on average. We would rather show that than round it away.
Nightly rate is a harder problem, and it is the reason ADR is not in the table above. Our forecast quotes a rate per booked night; the figure that comes back off a host dashboard at year end is built on a different denominator, so putting the two side by side would imply a gap that is partly definitional rather than a real miss. Until we can publish both on identical terms, showing them as a like-for-like comparison would be misleading, so we don’t. Owner net — the number a purchase decision actually turns on — is measured the same way on both sides, and that is what the ledger reports.
The full case study for each of the six — the estimate we produced before the property went live, the year it actually had, and the PDF we would hand a lender. Named addresses, not anonymised comparables.
Stayful runs short-lets for owners across the UK. Every week we get the same question from people thinking about turning a property into a short-let — what could it actually earn? The Analyser is our answer: the same model we use to estimate income before we take a property under management, now available to anyone who needs that decision in 20 seconds rather than on a sales call.
Because we operate the properties, so we find out. For the six short-lets Stayful took under management in 2025, the ledger on this page shows the Income Estimate produced before each went live next to twelve months of real bookings. Six is a small sample and we say so; it is also six more named, dated, published comparisons than the category usually offers.
It is a fair question. Running the properties is what lets us check a forecast against reality, and it also gives us a commercial interest in you liking the number. Two things keep us honest: the estimate is produced before we know whether a property will come under management, and we publish the variance either way — including where the model was wrong. Most Analyser users never become management clients, and the tool is priced to work that way.
Because our forecast and the year-end figure are not currently measuring it the same way. Our estimate quotes a rate per booked night; the number that comes back off a host dashboard is built on a different denominator. Putting them side by side would show a gap that is partly definitional rather than a real miss, so we have left it out until we can publish both on identical terms. Owner net is measured the same way on both sides, which is why the ledger reports that.
No. You see the realistic range, not a best-case projection. The figure you take into a decision is the figure you can defend to a lender.
You get the market data every platform has — live comparables, long-let benchmarks, demand drivers — without the first-party layer on top. The report says which is which rather than presenting both with the same confidence.
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