Compare a defined competitor set
Select hotels and consistent stay dates before comparing advertised offers. Preserve room and cancellation conditions to explain meaningful differences between prices.
Hotel Pricing Dataset
Scope hotel rate observations by stay dates, occupancy, room and booking conditions. Discuss source coverage and repeat collections for a meaningful comparison.
Destinations on requestAvailability on inquiry14 proposed fields
Coverage, pricing and delivery confirmed individually. Requests open your email app.Compare rates under the same stay conditions
Hotel prices only become comparable when the stay conditions are explicit. An observation should include check-in and check-out dates, guest count, room type and the terms attached to the rate. A refundable room with breakfast and a non-refundable room-only offer are different products. This specification covers how to define a rate dataset; it does not promise live room inventory, a booking service or a ready-made historical rate archive.
Study rates around selected dates
Request observations for holidays, events or an agreed future booking window. A displayed price depends on observation time as well as arrival date and length of stay.
Prepare channel-level research
Keep the source channel and rate context for each offer. Separate missing rates and collection failures from explicit sold-out states so the resulting analysis remains interpretable.
Agree on the shopping context
Specify destinations or hotel identifiers, arrival and departure dates, adults and children, room count and market or currency context. Record whether taxes, fees, meals and cancellation terms are included. Member, mobile or promotional rates need separate labels if they are in scope. Comparing only a numeric nightly price can obscure different room products and booking restrictions.
Confirm the source and update design
Rate observation requires a suitable pricing source and a collection process for the agreed dates and occupancy. Extracto’s existing Booking and Tripadvisor review scrapers collect reviews, not hotel room rates. A pricing workflow, historical coverage and recurring deliveries must therefore be reviewed independently. Source availability can change between observation and booking, and a saved rate never guarantees a room can still be reserved at that amount.
Define your structure
Data fields to discuss
Use this field guide to plan your request. Coverage and completeness will be confirmed individually. The CSV template contains column headers for planning.
| Field | Column name | Description |
|---|---|---|
| Hotel ID | hotel_id | Stable source hotel identifier when provided. |
| Hotel name | hotel_name | Property name published with the rate. |
| Destination | location | Source-supported city or geographic location. |
| Check-in date | check_in | Arrival date used for the rate request. |
| Check-out date | check_out | Departure date defining the length of stay. |
| Occupancy | occupancy | Guest and room counts used for the observation. |
| Room type | room_type | Published room or accommodation category. |
| Rate amount | rate_amount | Advertised offer amount with nightly or stay-total basis specified. |
| Currency | currency | Currency in which the rate was displayed. |
| Taxes and fees | tax_fee_basis | Whether taxes and mandatory fees are included, when stated. |
| Cancellation terms | cancellation_terms | Published refundable or cancellation conditions. |
| Meal plan | meal_plan | Breakfast or other inclusions explicitly attached to the rate. |
| Source channel | channel | Website or channel from which the offer was observed. |
| Observed at | observed_at | Timestamp associated with the shopping context and returned rate. |
From requirements to a clear scope
Share your requirements
Send your target sources, locations, essential fields, dates and expected volume. Mention the Hotel Pricing Dataset so the team has context.
Confirm the details
Discuss availability, source coverage, sample requirements, pricing and delivery timing before deciding.
Agree on the output
Confirm the final fields, file format and delivery method for the agreed dataset.
Frequently asked questions
Is this a ready-made download?
This page defines a dataset specification. Contact Extracto to confirm source coverage, available records, price and delivery timing for your requirements. A displayed sample is a saved example with its own location and collection date.
Can the Booking reviews scraper collect room prices?
The existing review scraper supplies review observations. Room rates need a dedicated pricing source and the full stay context. That workflow and its coverage must be confirmed separately for this dataset.
Can I compare prices for different stay lengths?
Store the nightly or total-stay basis explicitly along with the check-in and check-out dates. Minimum stays, promotions and taxes can affect the result, so different lengths should not be assumed directly comparable.
Is a displayed rate a booking guarantee?
No. It is an observation under a recorded context. Inventory and booking terms can change, and the source must be checked again before making a reservation or relying on current room availability.
Keep exploring
View category →Related datasets
Ecommerce
Product Price History Dataset
Markets on requestSpecify product price history by seller, market and observation interval. Define identifiers, currencies, availability and the dates your analysis needs.
Product IDVariant IDProduct titleBrand+9 fields
Confirm availabilityView dataset →
Business
New Business Leads Dataset
United StatesPlan a newly opened business list with explicit opening or registration evidence. Define dates, categories, locations and public business contact requirements.
Business nameQualifying eventEvent dateEvent evidence+9 fields
Confirm availabilityView dataset →
Automotive
Used Car Listings Dataset
Markets on requestDefine a used-car listing dataset with asking prices, vehicle specifications, seller types and dated observations for your chosen market.
Listing IDPublic vehicle IDMakeModel+9 fields
Confirm availabilityView dataset →
Your market. Your requirements.
Discuss your dataset requirements
Have a narrower location, a specific field list or a target volume in mind? Send your requirements to the Extracto team.