The site disallows its own doctor ranking pages. When a source draws that line itself, the polite thing and the correct thing are the same.
ScrapeIt runs the collection as a managed service. You name the markets, specialties and regions; we build the pipeline with market and consultation type as fields, prices where published, ranking surfaces excluded, and hand back CSV, JSON, Excel or a push into your warehouse.
Where a brief spans several markets we deliver them as separate markets on one schema, so aggregation is your deliberate choice rather than a side effect.
We collect published directory data, honour the crawl rules including the ranking exclusion, and pace requests. Review text is only in scope with a specific purpose and your own legal position. Your counsel should see the use case before the project starts.
Practice records carry the practitioner name as listed, specialty and subspecialties, clinic or practice name, full address, city, region, country, consultation types offered - in person, video, home visit - and consultation price where published.
Consultation price is one of the more unusual fields in a European provider directory and it is collected where the listing states it, with currency and consultation type attached. A price without the type of consultation it applies to is not comparable to anything.
Market is a first class field because the platform operates several national sites with different practitioner bases, regulatory contexts and pricing norms. Merging markets produces averages that describe no health system.
Availability indicators are collected where published as a state with a timestamp, since bookability is inherently time sensitive.
Aggregate rating and review count are available as numbers on the practice row; review text is a separate decision and not collected by default.
Cross-market comparison is the distinctive output: specialty density, consultation types and published prices across several countries on one schema, with market as a field so nothing is averaged across health systems by accident.
Telehealth adoption is measurable here in a way it rarely is elsewhere. Which specialties offer video consultation, in which markets, and how that share moves over time is a direct read on a structural shift, and it needs only repeat collection of the consultation type field.
Price transparency analysis covers what practitioners choose to publish, which is itself informative - the decision to publish a fee is a market signal as much as the fee is.
Scope we hold to: ranking addresses are disallowed by the site and out of bounds; review text is a separate decision and excluded by default; nothing behind a login; and we do not build reputation profiles of named practitioners.
Doctoralia is a doctor search and appointment booking platform operating across Spain and several other markets, listing practitioners with specialties, locations, consultation types, prices where published and availability.
Its crawl rules do something worth noticing. The site is broadly open, and it specifically disallows the doctor ranking addresses. That is the platform drawing a line around the part of its content that ranks named individuals - and it is a line we would want to respect even if it were not stated.
The effect on scope is concrete: practice and specialty listings are in, ranking surfaces are out, and a brief that was really about ranking doctors has an answer before any code is written.
What remains is substantial directory data: who practises what, where, at what consultation price where published, with what availability. The search responds directly with a great deal of content.
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Provider directory briefs almost always contain an unexamined assumption about reputation data, and on this source the site itself resolves it.
By disallowing its ranking addresses the platform says plainly which part of its content is not for bulk collection. We honour that, and it turns what is usually an awkward conversation about individual reputation into a simple statement of scope at the start of the project.
What is left is the part with real analytical value anyway. Specialty distribution across regions, consultation type availability - particularly the growth of video consultation - and price transparency where practitioners publish fees are all structural questions about health system access, and none of them needs to rank anybody.
The second reason to use this source is the multi-market footprint. Comparable directory data across several countries from one platform is a better basis for cross-country comparison than assembling separate national directories with different structures - the same argument that makes a single newsroom useful for cross-language media work.
The third is consultation price, which is rare in European provider data and directly interesting to insurers, health systems and anyone studying private healthcare pricing.
Learn how to use web scraping to solve data problems for your organization
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.
If you specialize in machine learning, you need to feed large amounts of data to the algorithms. Web scraping is the easiest and the most efficient method of collecting the data from all over the Internet.
ScrapeIt is a managed extraction company, not a tool you have to learn. Our team builds the pipeline, watches it as market sites diverge, and repairs it before a telehealth series loses the quarter that mattered.
You see a sample first, in your format, over the markets and specialties you actually cover, with consultation types and prices separated so you can judge the structure on real listings.
No - the site disallows those addresses in its own crawl rules. That is the platform drawing a line around content that ranks named individuals, and it is a line we would respect even if it were not stated.
Because published fees are rare in European provider data. We collect them with the consultation type and currency attached, since a price without the type of consultation it applies to is not comparable to anything.
Yes, and that is the source's strongest use. Comparable directory data across markets from one platform beats assembling separate national directories with different structures - market stays a field so nothing gets averaged across health systems by accident.
Yes, from the consultation type field over repeat collection: which specialties offer video consultation, in which markets, and how that share moves. It is a direct read on a structural shift and rarely measurable elsewhere.
Not by default. Aggregate rating and review count come through as numbers on the practice row. Review text is a separate decision needing a specific purpose and your own legal position, and we ask for both beforehand.
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.
Scrapeit Sp. z o.o.
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