Zillow Search Scraper with Property Detail & Agent Leads

A Zillow property listings scraper for Apify that extracts search-result data (price, beds, baths, address, status, Zestimate, days on market, and more) and can optionally enrich each listing with its own property detail page — agent/broker contact leads, price history, tax history, and school ratings — plus locally computed investment-analytics fields (price per sqft, rent-to-price ratio, Zestimate vs. list price, school quality score).

Use it as a Zillow real estate data scraper for market research, a Zillow API alternative for property listings, or a real estate lead generation tool that surfaces the listing agent's name, license number, and brokerage for every enriched home.

Key Features

• ✅ Real estate search scraping via Zillow's own search API, with an automatic dynamic-zoom split for large result sets (breaks past Zillow's ~800-result cap per query)
• ✅ HTML-pagination fallback method for reliability
• ✅ Automatic connection fallback if the default connection is interrupted
• ✅ Live data saving to the Apify dataset (results appear as they're collected)
• ✅ Bulk URL/keyword input, configurable delay, limits, and sort order
• ✅ Property Detail Enrichment — optional per-listing fetch of the full detail page, returning agent name, license number, brokerage name, price history, tax history, school ratings/distance, description, and year built
• ✅ Investment-Analytics Fields — pricePerSqft, rentToPriceRatioPct, zestimateVsListPricePct, and a distance-weighted schoolQualityScore, all computed locally from the enriched data
• ✅ Category-A search-result fields most Zillow scrapers miss: daysOnZillow, rentZestimate, taxAssessedValue, lotAreaValue, homeType, open-house and price-reduction flags
• ✅ Absolute scrapedAt timestamp on every row

Input

Required Fields

• searchUrls (array): List of Zillow search URLs (full URLs with searchQueryState are recommended) or location keywords.

Optional Fields

• extractionMethod (string): "PAGINATION_WITH_DYNAMIC_ZOOM_INCREASE" (default, API-based, auto-splits large areas), "PAGINATION_WITHOUT_ZOOMING_IN" (HTML-based fallback), or "MAP_MARKERS" (capped at ~500 results per URL).
• maxItems (integer): Maximum number of listings to scrape (1-10000, default: 10).
• delay (integer): Delay between requests in seconds (0-10, default: 2).
• sortOrder (string): Optional Zillow sort value, e.g. globalrelevanceex, price_asc, price_desc, days, zest_desc. Leave blank to keep each URL's own sort order.
• fetchDetails (boolean): Enable per-listing property detail page enrichment (default: false).
• maxDetailFetches (integer): Maximum number of listings to enrich when fetchDetails is on (0-500, default: 20).
• proxyConfiguration (object): Proxy settings (default: no proxy, with automatic fallback).

Input Example

{
  "searchUrls": [
    "https://www.zillow.com/dallas-tx/?category=SEMANTIC&searchQueryState=..."
  ],
  "extractionMethod": "PAGINATION_WITH_DYNAMIC_ZOOM_INCREASE",
  "maxItems": 100,
  "delay": 2,
  "fetchDetails": true,
  "maxDetailFetches": 20,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}

Output

Every run produces two row shapes in the same dataset, distinguished by type.

type: "listing" — one row per search result

{
  "type": "listing",
  "zpid": "55826232",
  "id": "55826232",
  "price": "$1,000,000",
  "unformattedPrice": 1000000,
  "address": "3810 Hawthorne Ave, Dallas, TX 75219",
  "addressCity": "Dallas",
  "addressState": "TX",
  "beds": 3,
  "baths": 3.0,
  "area": 2622,
  "detailUrl": "https://www.zillow.com/homedetails/...",
  "statusType": "FOR_SALE",
  "zestimate": 994000,
  "daysOnZillow": 14,
  "rentZestimate": 4200,
  "taxAssessedValue": 812000,
  "homeType": "SINGLE_FAMILY",
  "hasOpenHouse": false,
  "scrapedAt": "2026-08-15T10:22:31.000Z",
  "...": "..."
}

type: "detail" — one row per enriched listing (only when fetchDetails is on)

{
  "type": "detail",
  "zpid": "55826232",
  "agentName": "Jane Doe",
  "agentLicense": "0123456",
  "brokerName": "Example Realtors",
  "priceHistory": [{"date": "2026-08-07", "event": "Listed for sale", "price": 1000000}],
  "taxHistory": [{"year": 2025, "taxPaid": 18420}],
  "schools": [{"name": "Example Elementary", "rating": 8, "distance": 0.4}],
  "description": "...",
  "yearBuilt": 1996,
  "pricePerSqft": 381.39,
  "rentToPriceRatioPct": 5.04,
  "zestimateVsListPricePct": -0.6,
  "schoolQualityScore": 7.6,
  "isDetailValid": true,
  "scrapedAt": "2026-08-15T10:22:41.000Z"
}

Output Fields (listing rows)

• zpid / id: Zillow Property ID
• price / unformattedPrice: Formatted and numeric list price
• pricePerSqft: List price divided by area, computed when both are available
• address / addressStreet / addressCity / addressState / addressZipcode: Address components
• beds / baths / area: Bedrooms, bathrooms, square footage
• detailUrl: Link to the property detail page
• statusType / statusText: Property status (FOR_SALE, etc.)
• zestimate / zestimateVsListPricePct: Zillow's estimated value and its percentage difference from the list price
• daysOnZillow / timeOnZillow: Time on market
• rentZestimate / rentToPriceRatioPct: Estimated monthly rent and its annualized ratio to the list price
• taxAssessedValue / lotAreaValue / lotAreaUnit / homeType: Property attributes
• hasOpenHouse / openHouseDescription / openHouseStartDate / openHouseEndDate: Open-house details
• priceChange / priceReduction / datePriceChanged / comingSoonOnMarketDate: Price/market-timing signals
• scrapedAt: ISO timestamp of extraction
• And more fields in the raw JSON — every field above is also visible directly in the Output table.

Output Fields (detail rows, only with fetchDetails on)

• agentName / agentLicense / brokerName / agentPhone / agentEmail: Listing agent and brokerage contact
• priceHistory: Array of historical listing/sale events
• taxHistory: Array of yearly tax assessment records
• schools: Array of assigned schools with name, rating, distance, and grade range
• description: Full listing description text
• yearBuilt: Year the property was built
• schoolQualityScore: Distance-weighted average of assigned school ratings (closer schools weighted more heavily)
• isDetailValid: true if the detail page returned real data, false if it could not be fetched (never a faked row)

How Property Detail Enrichment Works

When fetchDetails is enabled, the actor fetches the property detail page for up to maxDetailFetches listings, in addition to the search-result data it already collects. Each enriched listing produces one extra type:"detail" row. This uses additional requests per listing, so it is off by default — enable it when you need agent leads, price/tax history, or school data on top of the base listing set.

Best Use Cases

• Real estate market research and price/status monitoring
• Property investment analysis (price per sqft, rent-to-price ratio, Zestimate spread)
• Real estate lead generation — listing agent and brokerage contact data
• School-quality-aware home search
• Competitive and comparable-sale analysis

Frequently Asked Questions

Q: Which extraction method should I use? A: PAGINATION_WITH_DYNAMIC_ZOOM_INCREASE is the default and handles large result sets by auto-splitting the search area. Use PAGINATION_WITHOUT_ZOOMING_IN as a fallback.

Q: How does the connection fallback work? A: The actor starts with a direct connection. If it runs into trouble, it automatically escalates to a residential connection with retries. Once escalated, it stays on that connection for the rest of the run.

Q: Can I scrape multiple locations at once? A: Yes — add multiple entries to the searchUrls array to process them in bulk.

Q: What happens if the actor stops mid-scrape? A: All data collected so far is saved live to the dataset, so partial runs are not lost.

Q: Does Property Detail Enrichment cost more? A: It uses one extra fetch per enriched listing (capped by maxDetailFetches), so runs with it enabled take proportionally longer and use more requests than listing-only runs.

Cautions

• Data is collected only from publicly available sources.
• No data is taken from private accounts or password-protected content.
• The end user is responsible for ensuring legal compliance (spam laws, privacy, data protection, etc.).
• Please respect Zillow's terms of service and rate limits.