Opodo is the flight-first online travel agency of eDreams ODIGEO, selling through around fifteen European storefronts, each with its own currency, locale and Prime pricing. Our Opodo scraper drives those filters the way a traveller would and returns clean fare tables you can analyse.
Our Opodo web scraper collects fares, routes and availability from opodo.com and its country storefronts without you touching an API. We drive the on-page search the way a traveller does - origin, destination, dates, cabin, baggage, stopovers - then export the results as CSV, Excel, JSON or a direct feed into your database. On a live client project this pipeline returns about 13,000 rows a day and took four working days to launch.
For every itinerary we capture the marketing and operating airline, flight numbers, departure and arrival airports with terminals, local departure and arrival times, total duration, number of stops and layover airports, cabin class, baggage allowance, fare conditions and the total price with taxes and charges. Where Opodo shows both a standard and a Prime price for the same itinerary, we record both, so the depth of the membership discount stays visible in the dataset.
Beyond the fare table we collect what explains a price: position in the results list, which filters were active when the price appeared, promotional labels, seat-availability warnings, dynamic flight-plus-hotel package offers, and hotel and car-hire results for the same destination. Run daily against a fixed set of routes, this becomes a time series showing how far ahead prices move and which carriers hold their fares.
Opodo is an online travel agency owned by eDreams ODIGEO, one of the largest flight retailers in Europe. It sells through opodo.com and around fifteen country storefronts - opodo.co.uk, opodo.fr, opodo.de, opodo.it, opodo.es, opodo.pl, opodo.nl and others - each with its own currency, language and inventory mix.
Flights are the core product, with hotels, car hire and dynamic flight-plus-hotel packages sold alongside them. Opodo also runs Prime, a paid membership that shows discounted fares to subscribers, so the same itinerary can carry two different prices depending on who is looking.
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Opodo results are assembled in the browser: filters, sliders and sorting all change what the server returns, and nothing useful comes back from a plain HTML fetch. A scraper that drives those controls can ask precise questions - only round trips where both legs are operated by the same airline, only the cheapest option per airline per departure date - and let the site do the filtering instead of downloading everything and discarding most of it.
That is how we built it for a client analysing airline pricing: full automation of the on-page filters including slider control, roughly 13,000 rows delivered daily, four working days from brief to first dataset.
Automated scraping of filtered flight ticket data from Opodo.com, including complex on-page interactions for airline and pricing selection.
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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 data extraction company specialising in collecting and delivering structured information from platforms across multiple industries - eCommerce, travel, real estate, job listings, and more. Our services handle the entire parsing process for you and provide clean, ready-to-use data exports tailored to your needs.
Yes. opodo.co.uk, opodo.fr, opodo.de, opodo.it, opodo.es, opodo.pl and the rest are handled as separate locales, each with its own currency and result set, and delivered in one combined dataset.
Where Opodo shows both, we record both on the same row, so you can measure the size of the membership discount per route and per airline.
Yes. Our automation drives the on-page controls, including price and time sliders, so the server returns only itineraries that match your rules - for example both legs operated by the same airline.
Daily is the usual cadence for fare monitoring, and shorter intervals are possible on a narrower set of routes. On one live project the daily dataset is about 13,000 rows.
A scoped flight-pricing pipeline with custom filter logic took four working days from brief to first delivery. Simpler route lists go faster.
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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