Extract property listings, pricing trends, agent profiles, MLS records, rental data, foreclosure notices, and neighbourhood intelligence from Zillow, 99acres, MagicBricks, Realtor.com, Housing.com, and 30+ portals β globally.
Real estate data scraping is the automated extraction of property listings, pricing, agent profiles, market intelligence, and transactional data from property portals, MLS databases, and real estate platforms. The real estate industry runs on data β and the most competitive players are the ones with the freshest, most comprehensive datasets.
Investors, brokerages, PropTech startups, mortgage companies, and urban planners all rely on real estate data scraping to power their products, analytics, and decision-making. DataFlirt extracts this data at scale β from residential listings to commercial properties, from foreclosure notices to zoning records β and delivers it clean and structured.
Whether you need a one-time dataset of property listings in a specific city, or a continuously updated pipeline tracking price movements and new listings across an entire market, we build it for you β with daily refresh cycles and change detection built in.
Every data point across residential, commercial, and investment real estate β extracted, cleaned, and delivered.
Extract residential and commercial listings including price, square footage, bedrooms, bathrooms, amenities, floor plans, images, agent contact, address, listing date, and availability status.
Scrape MLS databases and real estate portals for listing status, days on market, price history, open house schedules, school district ratings, and neighbourhood details at scale.
Collect apartment, condo, townhouse, and single-family rental listings including rent prices, deposit terms, pet policies, lease durations, and availability dates across platforms.
Scrape office spaces, retail units, warehouses, and industrial properties with zoning, lease terms, cap rate, floor area, building class, parking, and broker information.
Track historical and current pricing across property types and neighbourhoods β asking price, sold price, price per sqft, price reductions, and comparable sales over any time period.
Extract foreclosure listings and auction data including property addresses, opening bids, auction dates, lien details, property condition, and redemption period information.
Scrape walkability scores, school ratings, crime statistics, nearby amenities, public transport data, demographics, average income, and all publicly available location intelligence.
Extract mortgage rates, loan types, lender details, eligibility criteria, repayment terms, property tax records, HOA fees, and insurance estimates for full cost-of-ownership analysis.
Gather agent names, licence numbers, brokerages, active listings, transaction history, client reviews, ratings, specialisations, years of experience, and contact details.
Extract buyer and renter reviews for properties, landlords, property managers, and agents β enabling sentiment analysis and quality benchmarking across your market.
Extract zoning classifications, land use codes, building permits, construction approvals, variance requests, and regulatory filings for any property at scale.
Scrape cap rates, gross rental yields, vacancy rates, net operating income, cash-on-cash returns, and property appreciation data to power investment screening tools.
Every field structured and ready for your AVM, analytics platform, or investment tool.
From portal selection to a clean, deduplicated property dataset β delivered on your schedule.
{ "status": "success", "portal": "magicbricks", "scraped_at": "2025-03-10T07:15:00Z", "listing": { "id": "mb_blr_4481209", "type": "Apartment", "status": "For Sale", "locality": "Koramangala, Bengaluru", "bedrooms": 3, "area_sqft": 1640, "price": { "asking": 14500000, "per_sqft": 8841, "currency": "INR" }, "days_on_market": 18, "agent": { "name": "Rahul Sharma", "agency": "PropEdge Realty", "phone": "+91-98XXXXXXXX" }, "amenities": ["Gym","Pool","Club House"] } }
Real estate portals use map-based interfaces, login walls, and aggressive rate limiting. Our scrapers handle every challenge.
Coordinate-grid scraping extracts listings from map views that paginated list views cap β getting you every property in a geography.
Playwright handles advanced filter interactions, infinite scroll property cards, and lazily loaded listing data.
City and region-specific proxy pools deliver accurate local listing data and bypass geo-restrictions on portals.
Detect new listings, price reductions, status changes (Active β Sold), and removals with automated daily diff tracking.
Cross-portal deduplication and address normalisation so the same property from multiple portals becomes one clean record.
CSV, JSON, PostgreSQL, Airtable, Google Sheets, AWS S3, BigQuery, or direct API integration β you choose.
From PropTech startups to institutional investors β how organisations put real estate data to work.
The most successful PropTech products, investment platforms, and brokerages are built on one thing: comprehensive, fresh property data. A listing that's 48 hours stale is worth less than one that's 2 hours old. DataFlirt delivers daily β and for high-frequency use cases, multiple times a day β so your models, tools, and decisions are always grounded in current market reality across every portal that matters.
Start with a single portal or run a multi-market pipeline β pricing scales with your needs.
Custom property portal scraper, tested and handed to your team with one month maintenance.
Daily delivery of clean, deduplicated property data β we handle all maintenance.
For national coverage, multi-country markets, and dedicated real-time pipelines.
Common questions about real estate data scraping with DataFlirt.
Tell us which portals and geographies you need. We'll scope the project and have your property data pipeline running fast.
