A short-term-rental gross-booking-value proxy and a hotel
ADR & availability index — built from proprietary,
continuously-collected, point-in-time observations of listings, nightly rates and calendar availability.
Ticker-mapped to ABNB and BKNG. Aggregated, no personal data.
Web-observed availability and rate is widely regarded as the most reliable independent read on Airbnb and Booking gross bookings — because bookings show up as calendar dates going from open to unavailable, and rate shows up as the posted nightly price. Our panel captures both, continuously, before the companies report.
Short-term-rental gross booking value is the core KPI. Our STR GBV proxy — active listings × occupancy × nightly rate — tracks it at city and market level, weeks ahead of the print, with occupancy inferred from availability-calendar movement on a fixed listing panel.
Hotel room-nights and ADR drive the model. Our hotel ADR index plus availability / sold-out rate — by city and forward booking window — reads accommodation demand and pricing power across the same markets Booking monetizes.
Two derived series, both delivered as aggregated panels. No individual host, guest, or booking is identifiable — every metric is a city / market aggregate over a fixed, matched panel.
A gross-booking-value proxy for the short-term-rental market, built from three continuously-collected inputs on a fixed panel of listings: the count of active listings, the occupancy rate, and the posted nightly rate. Occupancy is derived from how a listing's availability calendar changes over time — a night that flips from available to unavailable, and stays that way, reads as booked. Matched panel over time isolates true demand from listing churn.
STR GBV proxy = active listings × occupancy × nightly rateAn average-daily-rate index for hotels by city and by forward booking window (e.g. check-in in 7 / 14 / 30 days), paired with an availability / sold-out rate — the share of the observed inventory that is unavailable for a given date. Together they read both pricing power and demand intensity across markets, and the forward-window dimension surfaces booking momentum before the stay date.
Hotel ADR index (city, fwd-window) + sold-out rate = rate × demand readThe value is in the panel design: the same listings and the same inventory, observed on a fixed cadence, so a change in the series is a change in the market — not a change in what we happened to look at that week.
Proprietary, continuously-collected, point-in-time data. Everything is captured as it was on the observation date, aggregated to city / market level, and mapped to the relevant ticker — nothing is back-filled or revised.
Every observation is stamped with the date it was collected. Historical series reflect exactly what was visible then — no restatement, no survivorship.
Delivered as panel aggregates — occupancy, ADR, sold-out rate, GBV proxy per city / week. No listing-level or booking-level rows in the product.
No host or guest identities, no contact details, no reservation-holder information. The feed is a market statistic, not a record of people.
Each series carries the equity ticker it informs (ABNB / BKNG) so it drops straight into a factor model or KPI nowcast.
An illustrative slice of the weekly city panel — STR occupancy and ADR alongside the hotel ADR index and sold-out rate. Values shown are representative, not live. Request a sample for the full schema and a market of your choice.
# travel_city_panel.csv — Barcelona (ES) · weekly · reads ABNB + BKNG week str_active str_occ str_adr str_gbv_proxy hotel_adr_idx soldout fwd_win 2026-W28 17,905 0.741 158.10 € 2,097,540 112.6 0.183 14 2026-W29 18,040 0.760 160.80 € 2,204,610 114.9 0.195 14 2026-W30 18,155 0.773 162.40 € 2,279,910 116.8 0.206 14 2026-W31 18,240 0.782 164.20 € 2,342,760 118.4 0.214 14 # str_gbv_proxy = active_listings × occupancy × adr × 7 nights (weekly) # hotel_adr_idx base=100 (trailing-year city mean); soldout = share of panel unavailable at fwd_win
Point-in-time, ticker-mapped, aggregated travel signals — STR GBV proxy and hotel ADR index. Request a sample slice for the market you care about.
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