Flight Pricing at Scale: Opodo Scraped with Full Filter Logic
Automated scraping of filtered flight ticket data from Opodo.com, including complex on-page interactions for airline and pricing selection.
Learn MoreFour products sit behind one Priceline search box, and the Express Deal row is the odd one out: the travel provider is named only after booking, so an opaque offer has no seller to join on.
The site is closed to automated clients, and clearing that is our side of the job, not yours: anti-bot handling, proxy rotation and CAPTCHA solving are part of the service, along with the rendering needed to reach app-side pages that never arrive as plain markup.
You define scope as a list - city ids, hotel ids, airport pairs, pickup locations - plus a stay or departure window and a refresh rhythm. We hold the query key on every row, so occupancy, dates, currency and capture time travel with the price instead of being reconstructed later. Delivery is CSV, JSON or XLSX by SFTP, S3 or Google Cloud Storage, or a Priceline API endpoint of your own over the same fields. When a layout shifts or a field is renamed, we repair the parser and backfill the gap; you are told what changed rather than left with a column of nulls.
A lodging row is keyed twice. The numeric hotelId is the stable handle that survives a slug rewrite, and the itemKey beside it is a base64 blob that unpacks into the whole question the price answered: hotel id, rooms, adults, children, currency and the rate product, which reads CORE on every public row. Lose the key and you are left with a number that no longer states who it was quoted for.
What we extract from Priceline on the lodging side:
A fare row is a different animal: origin and destination codes with coordinates, departure and arrival stamps, elapsed duration, segment count, the stops list, the marketing carrier per leg, the validating carrier, a cabin code and the amount with its currency. Price-drop rows add a strike price and the percentage cut. A car offer carries a daily rate, a total, the number of rental days, the pickup stamp, a supplier code and a location code, then a vehicle block - class, example model, seats, bags, automatic flag - and a features block for pay-now, credit-card-required, unlimited mileage, free cancellation and online check-in. Car rates are labelled as including taxes and fees; the nightly hotel figure is a starting rate, and the tax and fee line only resolves at room level in the booking flow.
Express Deals is the surface that makes this site different from its siblings, and it is also the one that breaks naive joins. On a route page an express row carries origin, destination, departure date, an amount and a currency - and nothing that identifies an airline. The carrier field is a dash. Priceline's footnote settles the rest: the travel provider is shown after booking. On the lodging side the same idea sells a stay by star rating and area with the name withheld, and the car funnel still reserves paths named for opaque booking, inherited from the Name Your Own Price era, whose route is also still reserved.
VIP is a second price surface rather than a discount code. The ladder runs member, blue, gold and platinum, reached at two, five and twenty-five completed trips, with the co-branded card granting gold outright. Each step widens exclusive hotel savings, rental car discounts and add-on deals, raises the Express Deal coupon issued after every trip, and moves you up the support queue; the Best Price Guarantee refunds a VIP member up to 200% of a price difference. All of it sits behind sign-in, so we do not collect it - we log the public rate and mark that a member tier exists above it.
Two more traps. A strike-through price here is a Priceline-constructed reference, compared against the most recent actual or an estimated average retail price on the site, not a rival's number. And the crawl rules close the flight and car search paths and an internal flight namespace, so they stay out of scope. We do not sign in, we do not touch checkout, and reviewer first names are dropped by default.
Priceline is the discount arm of Booking Holdings for North America, run out of Norwalk, Connecticut next to Booking.com, Agoda, KAYAK and OpenTable. Its header carries six tabs - Hotels, Flights, Rental Cars, Packages, Cruises and Experiences - plus Penny, the assistant that fields booking questions. Four of those tabs share one cart and one loyalty account, and each of the four writes a record with its own shape.
The public half of the site is a static layer whose pages end in .ssp, and its address grammar is worth learning before anyone scopes a crawl. A property page reads /hotel-deals/en-us/P3000035825/H975003/park-plaza-victoria-london.ssp: a city id carrying a P prefix, a hotel id carrying an H prefix, then a slug. Geography above the city climbs in two more shapes, a two-letter country such as GB and a region code such as GBENG for England. Flights abandon that scheme for airport pairs at /flight-routes/en-us/JFK/LAX/, with a parallel business-class branch. Cars live under /rental-car-deals/en-us/ and bundles under /package-deals/en-us/ keyed by origin and destination.
Inside the booking app the addresses change again. A property becomes a /relax/at/ path carrying the bare hotel id, then check-in, check-out and room count as further path segments rather than query parameters, and a car search writes pickup and drop-off stamps straight into the path the same way. Cruises sit on their own host. The index side is single-storefront: every sitemap section is published for en-us alone, even though the app itself offers Spanish (US), Canadian French and a currency picker. The hotel sitemap currently spans 270,791 property pages across 38,771 city ids, beside 13,160 route pages (September 2026).
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Revenue teams buy Priceline price data because the same room they sell direct is resold here under a different label, and the starting-from figure per property per stay date is the parity input that argument needs. The half-step star rating and the district line make the comparison set honest: a 3.5-star property in Earl's Court is not competing with a 4.5-star one in Victoria, whatever the nightly number says.
The opaque channel is the reason many buyers come at all. The saving on an Express Deal is defined against the lowest retail rate for the same itinerary on the same site, so the distance between the hidden offer and the named one is a readable measure of how deep the discount channel is running in a market that week.
Car rental brands use the agency directory, where Turo is ranked in the same list as Enterprise, Avis, Budget, Hertz, Dollar, Thrifty, National, Alamo, Sixt, Payless and Europcar, each with a rating out of ten and a review count. Airline analysts use the route furniture: departure-time buckets with the number of flights behind each, a best-day-to-fly table with averages and the gap below them, layover cities tagged with carrier codes, and a price range distribution that separates a good deal from a typical one. Bundle cards state their saving as a percentage or a dollar figure against the same trip bought in pieces, which turns package economics into a series you can chart.
Automated scraping of filtered flight ticket data from Opodo.com, including complex on-page interactions for airline and pricing selection.
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Daily scraping of Booking.com services - hotels, flights, car rentals, and attractions - with best-price selection across global destinations.
Learn MoreLearn how to use web scraping to solve data problems for your organization
If you work in travel tech, an OTA, a hotel chain, or at an airport, you are in a price-and-availability arms race. Fares change by the hour, room inventory disappears in minutes, and competitors test new bundles and ancillaries constantly.
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
ScrapeIt is a managed web scraping agency. We run travel feeds as an operated service: scope agreed once, schedule set once, and after that the output lands in your warehouse without anyone on your team babysitting a crawler. A pilot on a handful of cities or routes comes first, so you can check the field mapping against your own records before the run widens. We collect published, public information only, skip anything behind a login, and leave personal details out of the deliverable.
No open data API exists for buyers. The Priceline Partner Network is an affiliate and white-label channel, its developer portal sits behind approval and a bot wall, and it is built for selling travel rather than for price research. What is genuinely public is the .ssp layer: property, route, car and bundle pages served as HTML with structured data attached. A Priceline API from us means our endpoint over the fields we collect on your behalf, on your schedule - not a resold product of theirs.
Both, labelled separately, because they are not the same claim. The property row publishes a starting nightly figure and, where present, a strike-through reference; a car offer publishes a daily rate and a total for the whole rental and states that taxes and fees are included; a bundle card publishes a per-person figure and a trip total. We keep each as its own column with the currency and the occupancy the quote assumed, so nothing silently blends a pre-tax nightly rate with a tax-inclusive total.
Express Deal rows are collectable as published: the price, the dates, the route or the area, the star rating, and the fact that no provider is named. What we cannot hand you is the identity behind the offer, because it is disclosed only after booking - anyone promising the hotel name on an unbooked express row is guessing. VIP rates sit behind sign-in, and we do not log in to anything. We record the public rate and flag that a member level prices above or below it.
As wide as the address grammar allows. Lodging is scoped by city id, and a large city is covered by slicing it into districts, star bands and price ranges rather than paging one endless list. Flights are scoped as airport pairs with a date grid, and the business-class branch is a separate pass. Cars are scoped by pickup location and rental length. Give us the markets and the calendar depth and we size the run, then hold it steady so the series stays comparable week to week.
CSV, JSON, XLSX or an API endpoint, pushed to SFTP, S3 or Google Cloud Storage on the cadence you set, with a history file so old runs stay queryable. On lawfulness: we gather publicly published listing information, we honour the site's stated crawl rules, we do not sign in, we do not touch checkout, and we leave personal data out by default - reviewer first names included. If your counsel wants a scope note before the pilot, we write one.
Step 1 - Make a Request
You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.
Step 2 - Configuring Custom Web Crawlers
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Step 3 - Collect and Deliver
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Step 4 - Maintain and Support
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
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