Unlock Turkey’s vast real estate marketplace with ScrapeIt. We extract comprehensive listings from Sahibinden — formatted and organized for instant integration into your analytics, apps, or market models.
Sahibinden’s listings are dynamic, multilingual, and regionally dense — but ScrapeIt simplifies the entire process. We scrape Sahibinden data using custom-built extractors tailored to your goals: whether that’s isolating villa listings in İzmir, comparing apartment prices in Istanbul, or tracking rental supply in Anatolian cities. Our extraction flow targets visible listing fields, parses multilingual content, and removes duplicates or noise — delivering clear, structured property data without any manual effort on your side.
ScrapeIt collects granular property data using our custom Sahibinden scraper, tailored to capture every relevant detail from active listings. Each record includes the price in Turkish Lira (TRY), full address with province and district, property category (apartment, detached house, villa, commercial unit), and detailed specs like net/gross area (m²), number of rooms, floor level, total building floors, and age of the property. We also capture the heating system, furnishing status, availability of balconies, elevators, and parking.
Additionally, our Sahibinden scraper extracts listing titles, descriptions, posting dates, image URLs, and the type of advertiser — whether it’s a verified real estate agent, a construction company, or an individual seller. Every field is cleaned, structured, and formatted for export in CSV, JSON, or Excel — ready to support your real estate tools or market reports.
Sahibinden isn’t just a listing portal — it embeds layers of metadata that reveal listing behavior and market context. ScrapeIt captures promotional labels like “Urgent,” “From Owner,” or “New Listing,” which signal time sensitivity or direct deals. We also extract advanced filters such as earthquake resistance, security systems, building complex features, and proximity to transportation lines — elements especially valued by Turkish buyers and renters.
For each listing, we can track engagement signals like number of views or whether the property is marked as a “Featured Ad.” Combined, these extra layers allow you to segment inventory by urgency, seller type, lifestyle preference, or marketing strategy — insights that go far beyond traditional listing exports.
As Turkey’s top classifieds portal, Sahibinden.com has grown into a powerhouse for property search — listing homes, commercial units, land plots, and rentals in every province. Founded in 2000, it now serves over 50 million users monthly, offering content exclusively in Turkish and pricing in Turkish Lira (TRY).
The platform blends listings from both private owners and professional agencies, giving users a fuller view of the market. With built-in features like map search, saved filters, and alerts, it supports everything from daily browsing to long-term investment scouting. Users can even search by building age, proximity to metro lines, or earthquake safety features — a must for urban Turkish markets. From Istanbul penthouses to countryside parcels, Sahibinden provides one of the most active and localized real estate directories in the region.
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Developers
Customers
Pages extracted
Hours saved for our clients
Customized plans that grow with your data needs.
€199 / one-time
setup fee — included
€169 / mo
setup fee €499
€229 / mo
setup fee €499
€349 / mo
setup fee €499
€549 / mo
setup fee €799
Sahibinden is rich in listings but limited in how you can use that data at scale. Using a Sahibinden scraper gives you control — to analyze rent fluctuations across Istanbul districts, monitor new development supply in Ankara, or benchmark prices between owner-listed and agency properties. It’s especially useful for real estate platforms expanding into the Turkish market, analysts tracking urban growth, or investors comparing regions.
With ScrapeIt’s Sahibinden scraper, you don’t rely on inconsistent filters or limited exports. You get clean, structured property data pulled directly from the source — customized to support your pricing models, dashboards, or competitive insights.
Learn 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.
If you sell online, run a marketplace, or advise e-commerce clients, you already know why eBay matters: it’s one of the few places where big retailers compete side by side with thousands of small merchants and private sellers.
E-commerce teams do not just need “some” competitor data anymore. They need a continuous stream of real prices, discounts, stock levels, reviews, and seller behavior from the platforms that actually shape their markets.
Instead of offering generic tools or APIs, ScrapeIt focuses on delivering exactly the data you ask for — already filtered, formatted, and cleaned. When you need to scrape Sahibinden data, we build custom extractors that understand the platform’s structure, language, and listing logic. Whether you want only owner-listed rentals in Izmir or a full database of commercial properties in Bursa, we align the extraction to your business case. You get complete control without having to manage any tech — just consistent housing data ready to support your operations.
Our clients range from Turkish analytics firms to international proptech companies and investment teams tracking regional real estate shifts.
Yes — we collect all visible attributes, including technical specs such as property condition, heating system, number of floors, and more.
Absolutely. We can isolate owner-listed properties and exclude agency entries if that’s part of your targeting strategy.
Yes. All pricing remains in TRY, and fields like descriptions or titles are preserved in Turkish unless otherwise requested.
We can filter by keyword tags, map zones, or neighborhood mentions — allowing you to analyze transit-accessible listings or urban clusters.
1. Make a request
You tell us which website(s) to scrape, what data to capture, how often to repeat etc.
2. Analysis
An expert analyzes the specs and proposes a lowest cost solution that fits your budget.
3. Work in progress
We configure, deploy and maintain jobs in our cloud to extract data with highest quality. Then we sample the data and send it to you for review.
4. You check the sample
If you are satisfied with the quality of the dataset sample, we finish the data collection and send you the final result.
Scrapeit Sp. z o.o.
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