Wikicasa Scraper

Explore Italy’s property landscape with precision - ScrapeIt extracts detailed listings from Wikicasa, delivering ready-to-use housing data tailored for CSV, JSON, or analytics platforms.

Plans from €169 a month · Free project assessment · Reply within 1 business day

CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud

wikicasa.it
Wikicasa Scraper
wikicasa.itwhat you get
Typical fields for property portals
addresspriceproperty_typebedroomsarea_m2agentlisted_at
Delivery

API, JSON feed or CSV, XLSX and JSON files

Schedule

One-time, monthly, weekly, daily or 3 times a day

Navigating Italian Listings, the Structured Way

  1. You send

    Wikicasa pages, filters, fields and a schedule

  2. We run the scrapers

    Built, monitored and repaired by our team

  3. You receive the data

    API, JSON feed or CSV, XLSX and JSON files

Wikicasa aggregates properties across all of Italy - from Milan’s urban condos to countryside villas in Tuscany. ScrapeIt builds extraction flows that match your targeting: filter by region, price, energy class, square meters, or listing type (vendita vs. affitto). Our system processes Italian-language content, parses location data accurately (including CAP and province), and standardizes fields for export. No scraping tools or browser tricks needed - just a structured stream of Italian real estate data, ready for analysis or integration.

What the Wikicasa Scraper Extracts

From high-rise penthouses in Rome to restored villas in the Umbrian hills - our Wikicasa scraper captures listings rich in structured details and brings them into focus. ScrapeIt extracts pricing in euros, precise geographic data (including CAP codes and province), and listing types across both residential and commercial segments.

You’ll get technical specs like livable area (in mq), floor number, energy class (from A4 to G), and the building’s condition or renovation status. We also parse fields unique to Italian listings - such as heating type (centralizzata, autonoma), property exposure (doppia, angolare), and visibility tags like “Nuovo” or “Esclusiva.” Where available, we include listing descriptions in Italian, agent contact blocks, media galleries, and embedded map data - all organized for direct export into your workflow.

What the Wikicasa Scraper Extracts
Beyond Listings: Certification Tags, Highlight Labels, and Filters that Matter

Beyond Listings: Certification Tags, Highlight Labels, and Filters that Matter

Wikicasa listings often contain hidden value in the form of visual cues, badges, and embedded metadata. Scrape Wikicasa data with ScrapeIt to uncover deeper layers - like “In Evidenza” (featured), “Prezzo ribassato” (price reduced), or “Nuovo annuncio” - all of which signal listing freshness, seller urgency, or paid promotion.

We also extract filters related to accessibility, mortgage assistance, investment properties, and green building status (such as Classe Energetica A1+). Listings may include map placement, visibility level, or even mentions of virtual tours or certified appraisals. These elements help platforms and analysts go beyond simple housing records - offering behavioral context, urgency indicators, and commercial positioning within the Italian property market.

About Wikicasa: Italy’s Tech-Driven Real Estate Network

Source
wikicasa.it
Category
property portals
Delivery
API, JSON feed, CSV, XLSX
Plans
From €169 a month
Get a quote

Italy’s real estate scene gets a digital upgrade with wikicasa.it, a platform built around agency-verified listings and advanced search tools. As part of the RE/MAX and Casa.it network, it hosts a wide selection of residential, commercial, and upscale properties - all listed by licensed professionals.

Wikicasa serves urban markets like Rome, Milan, and Naples, as well as provincial areas and popular seaside towns. Features like energy certificate filters, map-based browsing, mortgage calculators, and alerts make it ideal for both everyday users and investors. The site is fully in Italian, with a mobile-optimized interface and an app for on-the-go property tracking.

More than just listings, Wikicasa delivers insights: property price trends, new-build spotlights, and neighborhood-level reports give users the context they need to buy, rent, or evaluate the market intelligently.

25Developers
500+Customers
1.5BPages extracted
15,000+Hours saved for our clients

Wikicasa scraping plans and pricing

Airplane

€199one-time

Setup fee included

100,000
One-time
Up to 5 days
7 days

Helicopter

€169/ mo

Setup fee €499

250,000
Monthly
Up to 5 days
14 days

Glasses

€229/ mo

Setup fee €499

1,000,000
Weekly
Up to 5 days
30 days

Microscope popular

€349/ mo

Setup fee €499

2,000,000
Daily
Same day
60 days

DNA

€549/ mo

Setup fee €799

3,000,000
3 times daily
Same day
90 days

Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.

Full plan details

Why Use a Wikicasa Scraper?

Wikicasa offers clean listings and rich filters - but it wasn’t designed for scale or integration. Using a Wikicasa scraper unlocks granular real estate data from across Italy, ideal for tracking regional pricing trends, inventory fluctuations, or property availability by CAP code, energy class, or property type.

Whether you're powering a national aggregator, enriching CRM data, or building dashboards for market intelligence, ScrapeIt’s Wikicasa scraper gives you the structure Wikicasa doesn’t. You can monitor new construction rollouts, analyze investment-labeled units, or benchmark urban vs. coastal housing - all without relying on limited front-end filters or manual copy-paste.

ScrapeIt for Italy: Custom Data, No Compromise

Instead of handing you a one-size-fits-all scraper, ScrapeIt builds a pipeline tailored to the way you need Italian property data. With our service to scrape Wikicasa data, we extract only the listings that matter - filtered by location, energy class, agency type, or listing status.

Need daily updates on new rentals in Bologna? Historical snapshots of luxury listings in Milan? Structured data on price drops in coastal Liguria? We make it happen. You choose what to track - we handle the parsing, formatting, and delivery. Fast, accurate, and built for real estate workflows.

FAQ

Still unsure? Write to info@scrapeit.io

What types of clients typically request Wikicasa data extraction?

We support real estate marketplaces, CRM providers, proptech startups, and analytics firms focused on the Italian housing market.

Can I receive exports broken down by province, ZIP code, or neighborhood?

Yes - we can organize data by location granularity, including comune, CAP, or even custom-defined zones.

Is it possible to capture listing tags like “In Evidenza” or status changes?

Definitely. We extract promotional labels, status flags, and visibility signals that help categorize listings beyond price and location.

Can you filter for specific energy classes or building conditions?

Of course - we can extract only listings with Class A or newly built homes, for example, depending on your needs.

What delivery formats do you support?

Data is available in CSV, JSON, or XLSX - all cleaned, structured, and ready to integrate into your analysis or application.

How it works

  1. 1

    Make a request

    You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.

  2. 2

    We configure the crawlers

    Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.

  3. 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.

  4. 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.

Request a quote

Tell us which sites, which fields and how often. A couple of lines is enough to start.

  • We reply within 1 business day
  • A sample dataset before the full run
  • We sign an NDA on request
  • Delivery by API, JSON feed or files
Which sites, which fields, how often. A couple of lines is enough.

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Wikicasa data from €169/month. Free project assessment, reply within 1 business day.