Get structured property listing data without building or maintaining a scraper. Specrom handles the extraction, anti-bot evasion, proxy rotation, and data normalization. You get 50+ clean fields per listing delivered via REST API or CSV — daily updates, US-wide coverage, starting at $99.
// Real property record — Specrom API { "property_id": "3173751224", "status": "for_sale", "list_price": 3650000, "days_on_market": 12, "description": { "beds": 4, "baths": 4, "sqft": 2482, "type": "single_family", "year_built": 1920 }, "location": { "address": { "line": "1815 E 3rd St", "city": "Brooklyn", "state_code": "NY" }, "coordinate": { "lat": 40.605971, "lon": -73.97002 } }, "local": { "flood": { "flood_factor_score": 1, "fema_zone": ["X (unshaded)"] } }, "photo_count": 22, "flags": { "is_new_listing": true, "is_price_reduced": false } }
Every property record in the feed is fully parsed and normalized — no HTML fragments, no field mapping, no schema surprises. The same clean structure across every listing from every source.
// Valuation — 3 independent AVMs included "estimates": { "current_values": [ { "source": "quantarium", "estimate": 3480000 }, { "source": "cotality", "estimate": 3510000 }, { "source": "collateral_analytics", "estimate": 3440000 } ], "historical_values": [...], "forecast_values": [...] }, // Risk data — per property, not by ZIP "local": { "flood": { "flood_factor_score": 1, "fema_zone": ["X (unshaded)"] } }, // Tax history — multi-year series "tax_history": [ { "year": 2025, "amount": 7381 }, { "year": 2024, "amount": 7102 } ]
No scraper to build. No proxies to manage. No pipeline to maintain when Zillow ships a front-end update. You describe what you need and we deliver the data.
Specify your target geography (state, ZIP code, metro area, or bounding box), listing status, price range, and property type. One-time pull or recurring delivery — daily, weekly, or monthly.
Our infrastructure manages rotating proxies, anti-bot evasion, CAPTCHA handling, and pagination. We scrape MLS-sourced data from Zillow, Realtor.com, and partner feeds at scale — validated before delivery.
Data arrives as normalized JSON via REST API, or as CSV/Parquet for bulk delivery. Push to your S3 bucket, database, or email. Same clean schema every time.
The same underlying data powers very different use cases depending on which fields you prioritize and how you consume the feed.
Build property search portals, listing alert products, or valuation tools on top of a stable API — without managing scraper infrastructure or worrying about schema changes when listing sites update.
Pull price history, AVM estimates, tax data, and days-on-market for modeling. Score acquisition pipelines, track market indicators by ZIP, and identify properties where list price diverges from consensus valuation.
Build segmented real estate agent contact lists from active listing data. Filter by market, price range, and property type to reach agents who are actively working — not stale registry exports.
Access flood factor scores, FEMA zone classifications, mortgage estimate breakdowns, and tax history per property for underwriting and risk workflows. Three AVM estimates included per record.
Most developers start by writing their own scraper. It works for a day or two, then Zillow starts returning empty pages, CAPTCHAs, or 403s. Here's what you're actually dealing with.
Zillow, Realtor.com, and Redfin all run enterprise-grade bot detection. They fingerprint browser headers, track request patterns, flag datacenter IP ranges, rotate CAPTCHAs, and silently serve fake or empty data to detected bots — without ever returning an error. Your scraper thinks it's working. The data you're collecting is garbage.
Even if you solve the proxy problem, selectors break constantly. Frontend teams push updates. A class name changes, a GraphQL endpoint changes its response shape, a new authentication header gets added. You find out when your pipeline silently stops writing rows. Real estate sites update their structure often enough that you can expect to spend meaningful engineering time every month just keeping scrapers running — not building features.
The hidden cost of DIY scraping isn't the initial build. It's the permanent maintenance overhead. Every engineer who has run a serious scraping operation knows the feeling of getting paged on a weekend because the pipeline went dark.
// What you query instead — clean REST API GET /listings ?zip=10001 &status=for_sale &property_type=condo &min_price=400000 &max_price=1200000 // Returns normalized records: { "total": 312, "page": 1, "per_page": 100, "listings": [ // 50+ fields per record, // same schema every time ] }
We pull from MLS-sourced data including Zillow and Realtor.com, along with direct MLS feeds where available. Coverage is US-wide across major metro areas and MLS regions, refreshed daily. For coverage confirmation in specific markets before integrating, reach out and we'll verify.
Every record includes listing core (status, price, days on market, price change history), property details (beds, baths, sqft, year built, type), full address and coordinates, photos, school data, three independent AVM estimates (Quantarium, Cotality, Collateral Analytics), multi-year tax history, flood factor score and FEMA zone, mortgage estimate breakdown, and MLS source data including disclaimer text.
We maintain rotating residential proxy infrastructure, browser fingerprint management, and CAPTCHA handling in-house. This is what makes managed scraping worth paying for — we absorb the infrastructure cost and ongoing maintenance so you don't have to.
Both. One-time pulls are priced at $99 for up to 20,000 listings. Recurring feeds (daily, weekly, or monthly) are available with volume discounts. Delta feeds — delivering only new listings, price changes, status changes, and delistings since the last pull — are available for recurring customers.
REST API with JSON responses for real-time queries. Bulk CSV or Parquet delivery for one-time or scheduled feeds. Delivery to S3, SFTP, PostgreSQL, BigQuery, or via webhook. Email delivery for smaller one-time orders.
Yes. Request a free sample dataset through the form on this page — no sales call required, just data you can evaluate. For API access, we can also provide trial credentials so you can make live queries against your target geographies before signing up.
DIY scraper tools hand you the infrastructure problem — you're still responsible for maintaining selectors, managing proxies, handling anti-bot countermeasures, and normalizing the output. When Zillow updates their front-end, your Octoparse scraper breaks. Specrom is a managed service: we own the infrastructure, the maintenance, and the normalization. You get a stable API with a consistent schema.
Tell us your target markets and what you're building. We'll respond within 24 hours with a free sample and pricing.