Set a nightly rate by feel and you're guessing against hosts who aren't. In 2026, AirROI's Airbnb API gives market analysts, property managers, and PropTech platforms programmatic access to more than 20 million active and historical Airbnb listings across 190+ countries, with 15+ years of historical trend data behind every market it covers (AirROI, Airbnb API product page, retrieved 2026-08-20). That is the dataset Riviera Host draws on to read occupancy and pricing patterns for every property we manage, from Montreux's lakefront to the wider Swiss market our owners ask us about.
Most self-managed hosts price off two things: what the calendar next door looks like, and a gut sense of "high season." Neither tells you whether a comparable listing three streets away is running 15 points higher occupancy at a lower rate, or whether the market you're about to buy into has genuinely tight supply or just looks that way from one listing. That gap between feel and evidence is what a market-data API exists to close.
Short answer: Riviera Host benchmarks every managed listing against AirROI's regional occupancy, average daily rate, and RevPAR data — drawn from a dataset covering 20M+ listings, 190+ countries, and 15+ years of history through 22 documented endpoints. We use it to see how a specific micro-market is pacing, not just what the citywide average says, and then combine that benchmark with local calendar knowledge — Jazz Festival, Christmas Market, cantonal caps — that no dataset captures on its own.
In this guide
What AirROI is, and why it exists alongside Airbnb's own API
Airbnb's own Official Partner API is a closed integration program for vetted property management systems and channel managers — even approved partners only get operational hooks like syncing listings, processing bookings, and exchanging guest messages, not occupancy data, revenue benchmarks, or historical trends (AirROI, Airbnb API product page, retrieved 2026-08-20). Airbnb was never going to hand every host a live feed of what every comparable listing nearby is actually earning — that gap is exactly why independent market-data providers like AirROI exist.
In 2026, AirROI documents 22 REST endpoints split across a Listings API (8 endpoints covering property-level search, comparables, and up to 60 months of listing history) and a Markets API (13 endpoints covering city- and neighbourhood-level occupancy, ADR, RevPAR, revenue, booking-lead-time, length-of-stay, and seasonality). The distinction matters for how we use it: the Listings API tells us what a specific comparable property is doing; the Markets API tells us what the whole micro-market around it is doing — and pricing a Montreux apartment well means reading both together, not picking one.
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In 2026, AirROI's Airbnb API covers more than 20 million active and historical listings across 190+ countries with up to 15 years of historical trend data, delivered through 22 documented REST endpoints (AirROI, Airbnb API product page, retrieved 2026-08-20). That is a materially deeper history than most third-party Airbnb data providers publish, which matters directly for seasonal pricing accuracy.
Why region-level data beats a citywide average
A single "Montreux average" hides more than it reveals, because a lakefront apartment in Montreux Centre, a family flat in Clarens, and a studio in Villeneuve are not competing in the same auction. AirROI's Listings API supports search by market, by radius from a set of GPS coordinates, or by a custom-drawn polygon — the kind of geographic precision a citywide average simply cannot offer (AirROI, Airbnb API product page, retrieved 2026-08-20). That precision is the difference between pricing against your actual comp set and pricing against a number that includes properties nothing like yours.
When we set up pricing for a new managed property, the first pass is never "what's the Montreux rate" — it's "what are the five to ten closest comparable listings within realistic walking distance actually achieving this month." A property two blocks from the lakefront promenade and one four streets back are not the same market, even inside the same commune, and treating them as one number is how self-managed hosts leave revenue on the table without ever realizing it.
| Search method | What it answers |
|---|---|
| Market search | How is this whole city or neighbourhood performing right now? |
| Radius search | What's happening within a set walking distance of this exact address? |
| Polygon search | What's happening inside a custom boundary — a lakefront strip, a specific district? |
This is also where the difference between market-level and listing-level data matters for pricing strategy. We've written separately about why dynamic pricing tools alone no longer create an edge now that most operators run one — the edge has shifted to what you do with region-specific comparables the tool can't see on its own.
Reading occupancy pacing before you have to react to it
By the time a slow week shows up as empty nights on your own calendar, it's already too late to reprice effectively. AirROI's Markets API includes a dedicated future-pacing endpoint that reads forward-looking occupancy based on current bookings across the market, alongside booking-lead-time and seasonality metrics that show how far in advance guests in a given market typically commit (AirROI, Airbnb API product page, retrieved 2026-08-20). That combination is what turns pricing from reactive into anticipatory.
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AirROI's Airbnb API includes a dedicated market-pacing endpoint that reads forward-looking occupancy from current bookings, plus separate booking-lead-time and seasonality endpoints (AirROI, Airbnb API product page, retrieved 2026-08-20). Together they show whether a market is pacing ahead of or behind its own seasonal norm — not just what happened last year.
We've seen this play out concretely with winter pricing: US ski markets that raised rates uniformly last winter lost RevPAR in more than half the markets tracked, precisely because they priced against last year's calendar instead of this year's actual pacing. The full breakdown is in our winter 2026-2027 booking pace analysis — the same pacing logic applies whether you're watching Verbier's ski season or Montreux's Christmas Market weeks.
What 15 years of history changes about a pricing decision
A pricing model built on one or two years of data can't tell a genuine anomaly from a repeating seasonal pattern — it just doesn't have enough cycles to know the difference. AirROI's Listings API exposes up to 60 months of listing-level historical performance, while the Markets API draws on 15+ years of market-level trend data (AirROI, Airbnb API product page, retrieved 2026-08-20). That depth is what lets a seasonality read distinguish "this is what August always does here" from "this August is unusual."
Across the properties Riviera Host actively manages in Montreux and Clarens, our own multi-season booking data already shows the same pattern at the individual-listing level: Jazz Festival week and the two weeks around Christmas Market consistently outperform the shoulder months by a wide, repeatable margin year over year — exactly the kind of structural seasonality that only becomes visible with several years of history, not one.
What this actually changes for your Swiss listing
None of this replaces knowing that a specific commune caps short-term rentals at 90 days, or that a particular week is booked out three years running because of one recurring event. Market data narrows the guesswork on where to start; local knowledge is what turns that starting point into the right number for your specific property. Riviera Host's pricing work always layers both — the regional benchmark first, then the calendar and regulatory context that makes it real for your listing.
For owners weighing whether a market has room to grow before buying, the same region-versus-city logic applies to acquisition research, not just pricing — see our five-metric framework for analyzing a Montreux market before you buy. And if you're wondering where realistic income actually lands once regional benchmarks meet a real calendar, our Montreux earnings guide and the Verbier, Crans-Montana & Zermatt chalet income comparison both work from the same kind of regional benchmarking described here.
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Talk to Riviera HostFrequently asked questions
What is AirROI and why does Riviera Host use it?
AirROI is a third-party Airbnb market-data provider covering 20M+ active and historical listings across 190+ countries, with 15+ years of history and 22 documented API endpoints. Riviera Host draws on its region-level occupancy, ADR, and RevPAR data to benchmark every managed listing against real comparables instead of guesswork.
How is AirROI's data different from Airbnb's own numbers?
Airbnb's own Official Partner API covers operational hooks — syncing listings, bookings, and messages — not analytics. It does not expose occupancy rates, revenue benchmarks, or historical trends to hosts or managers. AirROI is an independent data provider built specifically to fill that gap with market-level and listing-level performance metrics.
Does this replace local knowledge of the Montreux or Swiss market?
No. Data tells you what comparable listings are earning and how occupancy is pacing; it does not know that a specific Jazz Festival week or a commune's 90-day cap changes the picture. Riviera Host uses market data as the starting benchmark, then layers in the local, regulatory, and seasonal context data alone can't capture.
How often is the underlying occupancy and rate data refreshed?
AirROI states its Airbnb dataset refreshes frequently across all 22 endpoints, combining current listings with up to 60 months of listing-level history and 365 days of forward-looking future rates, so pricing decisions can be checked against both what already happened and what's already booked ahead.
Can this data tell me exactly what to charge tonight?
It tells you the range comparable properties in your micro-market are actually achieving, not a single guaranteed number. Riviera Host combines that regional benchmark with your property's specific amenities, reviews, and calendar position to set the actual nightly rate — the data narrows the guesswork, it doesn't replace the judgment.
Related reading: Dynamic pricing isn't your Montreux Airbnb edge anymore · How to analyze a Montreux Airbnb market before you buy · Winter 2026-2027 booking pace: a pricing lesson for Montreux · How much can you earn renting your Montreux apartment?
Founder of Riviera Host. BBA Hospitality (Glion), MSc Tourism (FHGR), MSc Data Science (HSLU). 8+ years managing short-term rentals across Switzerland.