We extract property listings, price histories, agency portfolios, and energy class ratings from Immobiliare.it. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Property Listings objects from immobiliare.it. All fields typed and schema-versioned.
"property_id": "89341205", "title": "Trilocale via Roma 12, Milano", "property_type": "Apartment", "price": 450000.0, "surface_area_sqm": 95, "rooms": 3, "bathrooms": 2, "energy_class": "A", "condition": "Excellent/Renovated"
| # | property_id | title | property_type | price | surface_area_sqm | rooms |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Valuations objects from immobiliare.it. All fields typed and schema-versioned.
"property_id": "89341205", "current_price": 450000.0, "price_per_sqm": 4736.84, "original_price": 475000.0, "discount_pct": 5.2, "condominium_fees": 150.0, "omi_zone": "B1/Centro Storico", "price_timestamp": "2026-05-12T10:15:00Z"
| # | property_id | current_price | price_per_sqm | original_price | discount_pct | condominium_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agency Profiles objects from immobiliare.it. All fields typed and schema-versioned.
"agency_id": "AG-74839", "agency_name": "Milano Real Estate Srl", "address": "Via Torino 45, Milano", "phone_number": "+39021234567", "active_listings_count": 142, "rating": 4.6, "review_count": 89, "vat_number": "IT12345678901"
| # | agency_id | agency_name | address | phone_number | website | |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Building Specs objects from immobiliare.it. All fields typed and schema-versioned.
"property_id": "89341205", "construction_year": 2018, "heating_type": "Centralised", "air_conditioning": true, "energy_performance_index": "34.5 kWh/m2a", "building_floors": 6, "parking_spaces": 1, "wheelchair_accessible": true
| # | property_id | construction_year | heating_type | air_conditioning | energy_performance_index | building_floors |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location & POIs objects from immobiliare.it. All fields typed and schema-versioned.
"property_id": "89341205", "region": "Lombardia", "province": "Milano", "municipality": "Milano", "neighborhood": "Duomo / Centro Storico", "latitude": 45.4642, "longitude": 9.19, "distance_to_transit_m": 150, "distance_to_supermarkets_m": 300
| # | property_id | region | province | municipality | neighborhood | street_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Immobiliare.it scraper handles every layer of the platform: residential listings, dynamic pricing, agency portfolios, and energy class data, with JavaScript rendering and anti-bot circumvention built in.
Title, specifications, description, floor plans, images, and every metadata field Immobiliare.it surfaces, scraped at the individual listing level.
Capture current price, original price, condominium fees, and price drops, timestamped per crawl.
Extract agency name, contact details, active listing counts, and physical addresses for every property.
Capture APE (Energy Performance Certificate) ratings, heating types, construction year, and accessibility features.
Extract exact latitude and longitude coordinates, neighbourhood boundaries, and proximity to transit.
Scrape retail spaces, offices, warehouses, and judicial auction listings with base price and auction date.
Track days on market, price reductions, and delisting events across millions of properties.
Capture high-resolution image URLs, floor plan links, and virtual tour endpoints.
Run one-off bulk exports or configure continuous pipelines at hourly, daily, or real-time cadences with change-detection diffing.
Extract listings within custom geographic polygons to bypass standard search limitations.
Brief in. Clean data out.
Provide regions, municipalities, property types, or agency IDs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for immobiliare.it.
Schema validation, null-rate checks, price-outlier detection, and sample listings before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Immobiliare.it employs strict rate limiting and geo-blocking. Here is how we maintain extraction stability.
Immobiliare.it blocks data centre IPs and non-Italian traffic. Our crawlers use Italian residential ISP proxies with realistic browser fingerprints and full cookie session management, trained on real user behaviour patterns.
Immobiliare.it search results and interactive maps are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution to trigger lazy-loaded listings and hydrate map clusters.
The portal changes its DOM structure frequently. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and structured data extraction (LD+JSON), ensuring layout changes do not break your data pipeline.
For large national catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost, storage bloat, and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, price outliers, schema drift, and coverage drops, responding before you notice.
AVM (Automated Valuation Model) providers use historical listing data and OMI zones to train property pricing algorithms.
Institutional investors track price-per-square-metre trends and rental yields across Italian municipalities to identify undervalued assets.
Real estate networks monitor competitor portfolios, days on market, and market share at the provincial level.
Researchers analyse housing supply, energy class distribution (APE), and urban sprawl using geospatial listing data.
Moving companies, utility providers, and renovation firms identify new listings to target properties coming onto the market.
Banks and macroeconomists track inventory levels and price drops to gauge the health of the Italian real estate sector.
"Immobiliare.it holds the definitive dataset for Italian real estate, but extracting accurate historical pricing and agency data requires bypassing aggressive bot mitigation."
Most teams underestimate the investment required: reliable Immobiliare.it scraping requires Italian residential proxies, full JavaScript rendering for map clusters, CAPTCHA handling, daily selector maintenance, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our immobiliare.it scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across Italian regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About immobiliare.it scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Immobiliare.it is generally permissible under applicable law, provided it targets only public, non-authenticated property and agency data. We do not extract personal user data, circumvent authentication walls, or violate GDPR. Clients should review portal ToS and consult legal counsel for specific use cases.
We use Italian residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. Our selectors have multi-layer fallback chains so DOM changes do not break the pipeline.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per property for price changes, allowing you to track original listing price versus current price.
Yes. We extract agency names, physical addresses, phone numbers, and VAT numbers as displayed on public listing pages and agency profile directories.
Real-time streaming pipelines achieve sub-60-minute latency for new listings in targeted municipalities. Full national catalogue refreshes at daily cadence complete within a 12-24 hour window depending on volume.
Our smallest packages start at a defined regional scope (e.g., Lombardy only) with weekly delivery. For national catalogues or custom schema requirements, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 500 properties or 50 search result pages as part of the pre-engagement scoping process, so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of Milan properties or a continuous price-monitoring feed across Italy, we scope, build, and operate the pipeline. Tell us what you need.
