Know what every hotel charges, everywhere that matters
We scrape rates across OTAs, brand sites, and metasearch engines, then match establishments, room types, and meal plans so you can compare like with like. One-off benchmark, recurring delivery, or self-serve access for your team.
Starts at 3,000 EUR. On-demand or recurring.
Why hotel pricing benchmarks are harder than they look
The same hotel room appears on Booking.com, Expedia, the brand’s own site, and three metasearch engines. Each source names it differently, bundles breakfast or doesn’t, quotes for different occupancies, and applies dynamic pricing that shifts by the hour. Downloading rates from five platforms gives you five spreadsheets that don’t line up. The real work is matching: this Superior Double on Booking.com is the same product as that Deluxe King on the hotel’s own site, with breakfast included in one price and not the other. We handle that matching, normalize the dimensions, and deliver a dataset where every row is a true comparison.
Cross-source matching
Establishments and room types reconciled across OTAs, brand sites, and metasearch. Same product, single row.
Every rate dimension
Occupancy, board basis, cancellation policy, minimum stay. Captured so comparisons hold.
Budget-aware scoping
Hotel pricing data scales fast. We design the crawl to hit the dimensions that matter to you, not every permutation.
Three delivery models
A one-off dataset for strategy reviews, recurring deliveries on a schedule, or a self-serve interface where team members pull benchmarks on demand.
What most teams try first
Manual rate shopping
Open five OTAs, search the same dates, copy prices into a spreadsheet. No vendor needed.
Works for a handful of properties. Falls apart beyond 10 hotels × 20 dates × 10 room types × 5 sources. Room type matching is guesswork, and the data is stale before the spreadsheet is done.
Rate intelligence SaaS
Automated rate feeds with dashboards. Subscription model, always-on.
Predefined source list, rigid room type taxonomy. If your competitive set doesn’t fit their model, you get approximate matches or gaps. Limited control over which dimensions are captured.
OTA data partnerships
Direct data feeds from booking platforms. High volume, structured format.
Restricted to one source per agreement. No cross-source matching. You still need to reconcile the same property across feeds yourself.
Built for these situations
Tell us what you’re benchmarking
Which markets, which competitors, which dimensions? We’ll scope the data and the delivery model.
Get a QuoteFrom scattered rates to a clean benchmark
Define the scope
Markets, property types, competitive sets, booking sources, date ranges, and the rate dimensions you care about. We assess feasibility and estimate data volume against your budget.
Build the matching model
We map establishments and room types across sources. This is the hard part: reconciling naming conventions, board basis differences, and occupancy variations into a unified schema.
Run a pilot extraction
A test crawl on a slice of your scope. You review the matched output to verify accuracy before we scale.
Deliver the benchmark
For one-off projects: a clean dataset in your format. For recurring needs: scheduled deliveries. For teams that need flexibility: a self-serve interface where members define parameters and pull fresh benchmarks on demand.
Maintain and adapt
Source sites change layouts and rate structures. We update scrapers and matching rules. Your data stays accurate.
Why choose Stratalis for hospitality benchmarks
Matching is what we actually sell
Anyone can scrape a price. The value is in knowing that two listings describe the same room. We invest the engineering time here because that’s where benchmarks succeed or fail.
Budget-conscious crawl design
Hotel pricing data explodes combinatorially. We work with you to target the dimensions that answer your question without burning budget on permutations you won’t use.
Engineers who understand hospitality data
Room categories, rate plans, board basis codes, OTA-specific quirks. We’ve built these pipelines before. You don’t spend weeks teaching us the domain.
On-demand or always-on
Not every team needs a standing subscription. We offer one-off deliveries, recurring schedules, and a self-serve interface. Pick the model that fits how your team works.
FAQ
We capture rates at defined intervals and store snapshots with timestamps. For benchmarks, we typically align on a consistent capture window (e.g., same time of day, same advance booking period) so comparisons are valid. If you need intraday price tracking, that’s a monitoring engagement with a different scope.
We scrape direct booking engines and hotel websites alongside OTAs. If a property only sells through its own site, we capture those rates. The matching model adapts to whatever sources carry the data.