Why most revenue case studies are hard to trust
Short-term rental results are easy to inflate without saying anything untrue. Three things usually do it.
Portfolio growth counted as pricing growth. If an operator goes from 20 listings to 60 during an engagement, total revenue will triple whatever the pricing did. Unless a case study separates the original listings from the new ones, the headline number tells you about acquisition, not revenue management.
A rising market counted as skill. If every comparable listing in a market earned 15% more this year because of a new event, an airline route or a supply drop, a 15% lift means you kept pace. It does not mean you outperformed. The reverse is also true: holding revenue flat in a market that fell 10% is strong work that an absolute comparison hides.
Mismatched periods. Comparing a summer quarter with the previous winter, or a year with a renovation month against a year without one, produces big percentages that mean very little.
We built our reporting to avoid all three, because we use the same numbers to run our own listings.
How we measure every result
Every case study we publish follows the same rules. If a case study breaks one of them, it says so and explains why.
1. Like-for-like listings first. The headline result uses only listings that were live and bookable for the full period before and after we started. Listings added during the engagement appear in a separate table, clearly labeled, and never in the headline.
2. Same stay dates, year on year. We compare the same twelve months of stay nights, for example July to June against the previous July to June. We count revenue by the night stayed, not the date it was booked, so a busy booking month does not distort the picture.
3. Market index as the headline. Our main measure is RevPAR index: a listing’s revenue per available night divided by the revenue per available night of comparable listings in the same market. An index of 1.00 means earning exactly what the market earns. 1.10 means earning 10% more. We show the index before and after, then show absolute revenue alongside it, together with how much the market itself moved over the same period.
4. The supporting metrics. RevPAR index tells you whether you are winning. The supporting metrics tell you why:
- ADR index: your average nightly rate compared with the market.
- MPI (market penetration index): your occupancy divided by market occupancy.
- Booking pace: how fast future nights are filling compared with the market.
- Booking window: how far ahead guests are booking, split into the next 14 days, 30 days, 31-60 days and 61-90 days.
A higher rate with an emptier calendar is not a win, and neither is a full calendar at a discount. We show both sides.
5. Clean inputs. Owner stays, maintenance blocks and long single bookings distort occupancy figures. We exclude blocked nights from available nights and flag any listing where a single reservation dominates the period. Revenue figures exclude cleaning fees and taxes. Each case study states whether figures are before or after channel commissions.
6. Numbers that recompute. Every percentage on a case study can be recalculated from the figures shown on the same page. A second team member checks the math before anything is published.
7. Client permission. Case studies are anonymized by default, describing the client only by portfolio size and market. We only use a client’s name, logo or words with their written permission.
What a good result looks like
Revenue management results are rarely dramatic for well-run portfolios, and anyone promising a fixed percentage before seeing your data is guessing. In our experience the gains come from a handful of places:
- Prices that respond faster when a date starts filling ahead of the market.
- Last-minute discounts that are gradual, not a cliff in the final week.
- Minimum stays that do not hide listings from guests filtering for short trips.
- Price floors that protect what a listing is actually worth.
- Event dates caught early.
Some portfolios have a lot of room on these. Some are already priced well and the gain is small. Our case studies will include both, because an honest small number is more useful to you than a flattering big one.
Case studies
We have not published any client case studies yet. The first ones will be added here once clients complete twelve months with us, because we do not publish partial-year comparisons as headline results.
Until then, the methodology page sets out exactly how each case study will be measured, so you can hold us to it when they appear.
Where our method comes from
Airyield was built by an Australian operator managing around 200 listings, including motels. After working with an external revenue manager, they built their own pricing analyzer to check every listing against the market each morning. The same software and the same rules now run client portfolios. Read our story.
See your own numbers
The fastest way to judge whether we can help is to look at your own RevPAR index. Our free revenue audit compares your listings against the market on the same measures we will use in our case studies, and shows where the gaps are, if there are any.
Results vary by market, listing and season. Past results for one portfolio do not predict results for another. See How we measure results for full definitions.