The same hotel room can cost one price on a Tuesday in March and double on a Saturday in July. A holiday package changes with the departure date, the length of stay and the number of travellers, and a room that is bookable today may be sold out tomorrow.
For anyone who has to price in this market, the question is not what a competitor charges. It is what they charge for which stay, on which date and under which conditions.
Because the price is not a property of the product. It is the result of a search: dates, length of stay, number of guests and room or package type go in, and a price comes out. The same property shows a different price for every combination, and that price moves with availability and with how far ahead the booking is made. A benchmark therefore has to define which searches to run, and has to record when each price was collected.
Benchmark the stay, not the headline rate. Two offers are only comparable if the elements that drive the price match: the type of room or accommodation, the board (for example breakfast only or all-inclusive), the cancellation conditions, the length of stay and the number of guests. For packages, add what is included, such as flights or transfers. Treat attributes that change the proposition as hard filters and use a weighted score for the rest. We describe this logic in more detail in Matching without a barcode: How to compare prices when there's no EAN.
Choose a reference calendar. Include peak and off-peak periods, typical lengths of stay and the booking horizons that matter. Checking the same stay date at several moments before arrival shows how competitors move their prices as the date gets closer. Focus on the combinations that drive most of your bookings: covering every date for every property creates a large dataset without a commercial question behind it.
Normalise every offer to a common basis, such as the total price per person per night for an equivalent stay. Include mandatory fees and local taxes where they are part of what the traveller pays, and be explicit about what is not included. Otherwise you reward whoever shows the lowest headline price and adds costs later.
A competitor that is sold out changes your position even if its price did not move. Availability signals, such as sold out, few rooms left or minimum-stay requirements, tell you something about demand and about how a competitor manages its inventory. Collect them together with prices, so you can see when a price gap is real and when the cheaper offer cannot be booked.
Travellers compare on comparison sites and booking platforms before they book. The same offer can show different prices per channel, and ranking, presentation and review scores influence the choice at least as much as the price. Monitoring only your competitors' own websites misses how the market is actually seen, so include the channels where your customers search.
Collecting prices at scale means completing search and booking flows the way a traveller would. That comes with the same challenges as any configurator: many combinations, flows that change, and scrapers that can break without anyone noticing. Store each price together with its stay date, length of stay, number of guests, room or package type and the moment it was collected. Validate every run and detect changes in the flow early. We cover this in Configurator scraping: how to monitor prices that only appear after configuration. Monitoring only works for prices that are publicly visible.
Deciding which stays and periods matter for your business is something you are well placed to do. What is harder to sustain is the engineering: completing search flows at scale, matching comparable offers and keeping everything accurate when competitors change their websites or their packages.
At Competify, we do this for markets such as hospitality, automotive leasing, telecom and insurance. We agree with you which stays, periods and channels matter, build and maintain the data collection, match and validate the results, and deliver them through a dashboard, API or file transfer. If you would rather not own that part yourself, please plan an introduction meeting.
Want to know how we work?
We build and maintain custom webscrapers that turn any website into structured data and insights.
