Zillow All-in-One Scraper

Listings, full property details, photos, agents, price history, and tax history -- in one actor.

Point it at a city, a neighborhood, a map area, or a Zillow search URL. The actor returns a clean, normalized dataset row for every property: address, geo coordinates, price, beds, baths, square footage, lot size, year built, home type, full-resolution photo URLs, the listing agent's name and phone, multi-year price history, and multi-decade tax history.

What it can do

• Search by location -- paste any Zillow search URL or supply a map bounding box. The actor follows the same pagination Zillow's own UI uses.
• Full property details -- every listing is enriched with the data from its detail page, not just the search-results summary. No second pass needed.
• Large areas, no truncation -- when an area exceeds Zillow's per-query result ceiling, the actor automatically subdivides the map into smaller tiles and stitches the results back together.
• Price + tax history -- the actor pulls the same multi-year financial history Zillow shows on each listing page (commonly 5-20+ years of tax data and the full list-of-events timeline).
• Listing agent contact -- name, phone number, brokerage for every active listing.
• High-resolution photos -- up to ~40 photo URLs per listing at 1152px width, ready to download.

Use cases

• Real-estate market analytics, comparable-sales modelling.
• Investor lead lists -- agents, brokerages, price-change signals.
• AVM training data with historical assessment values.
• Neighborhood-level inventory tracking, price-drop alerts.
• Building competing listing portals or filtered home-search products.

Why use this actor

• One run, complete data. You don't need a separate "details" scraper. Every row is fully enriched.
• Map-aware. Drop in a bounding box and the actor handles the per-tile ceilings transparently. No "missing 60% of listings" because of pagination limits.
• Normalized output. The dataset schema matches the Realtor.com All-in-One Scraper so the two sources can be unioned into one table downstream.
• Production-tested for Apify. Built and verified on Apify cloud with residential proxy. The starter input below was the actual test run.

Sample input

{
  "boundingBoxes": [
    { "north": 30.31, "south": 30.27, "east": -97.72, "west": -97.78 }
  ],
  "useMapResults": true,
  "maxItems": 5,
  "maxConcurrency": 2,
  "maxRetries": 8,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Other ways to seed:

{ "searchUrls": [{ "url": "https://www.zillow.com/austin-tx/" }] }

{
  "boundingBoxes": [{ "north": 30.45, "south": 30.15, "east": -97.55, "west": -97.95 }],
  "filterState": { "price": { "min": 400000, "max": 900000 }, "beds": { "min": 2 } },
  "useMapResults": false
}

Sample output (real data from the live Apify test run above)

Three real Austin TX listings emitted from the Apify run on 2026-05-14 against bounding box 30.27/30.31, -97.78/-97.72 (East Austin / UT neighborhood):

{
  "source": "zillow",
  "sourceId": "29397590",
  "url": "https://www.zillow.com/homedetails/809-E-38th-St-Austin-TX-78705/29397590_zpid/",
  "address": {
    "line": "809 E 38th St",
    "city": "Austin",
    "state": "TX",
    "zip": "78705",
    "lat": 30.296783,
    "lng": -97.72628
  },
  "status": "FOR_SALE",
  "price": 950000,
  "currency": "USD",
  "beds": 4,
  "baths": 3,
  "sqft": 1765,
  "lotSqft": 11830,
  "yearBuilt": 1953,
  "propertyType": "SINGLE_FAMILY",
  "photos": [
    "https://photos.zillowstatic.com/fp/c184eaedca0e0c1d671cb7aca341d9c6-cc_ft_1152.jpg",
    "https://photos.zillowstatic.com/fp/a12a162e0d6724c1e88cabdab47b15d4-cc_ft_1152.jpg",
    "https://photos.zillowstatic.com/fp/3f1f0c1d904a63966211b8a3292ae9c5-cc_ft_1152.jpg"
    /* ... 15 more photo URLs ... */
  ],
  "listingAgent": {
    "name": "Clay Byrne",
    "phone": "(512) 942-7880",
    "brokerage": "Keller Williams Realty"
  },
  "priceHistory": [
    { "date": "2026-04-07", "event": "Price change",    "price": 950000 },
    { "date": "2026-03-17", "event": "Price change",    "price": 1049900 },
    { "date": "2026-02-09", "event": "Listed for sale", "price": 1100000 }
  ],
  "taxHistory": [
    { "year": 2025, "amount": 11231.14, "value": 680091 },
    { "year": 2024, "amount": 11155.90, "value": 674528 },
    { "year": 2023, "amount": 15568.63, "value": 860503 },
    { "year": 2022, "amount":  7631.93, "value": 696858 },
    { "year": 2020, "amount":  7646.81, "value": 575915 },
    { "year": 2002, "amount":  5161.45, "value": 223429 }
    /* ... 17 more years ... */
  ],
  "scrapedAt": "2026-05-14T14:50:54Z"
}

Two more rows from the same run:

sourceId	Address	Price	Beds	Baths	sqft	Type	Agent	Brokerage
29401557	4404 Barrow Ave, Austin 78751	$550,000	2	1	896	SINGLE_FAMILY	Vanessa Hadrych	Keller Williams Realty
338246448	2500 Longview St #518, 78705	$500,000	2	2	1010	CONDO	Georgia Spiropoulos	Christie's Int'l Real Estate

Tips for best results

• Residential proxy is the default and the right choice. Datacenter IPs get flagged within a few requests.
• Start small. Set maxItems: 5 and maxRetries: 8 for your first run. Adjust upward once it works for your input.
• Bounding boxes beat city URLs for completeness. A city URL is bound by Zillow's URL-encoded filter; a bounding box gets every listing in the box regardless.
• Photos are CDN-direct. Each URL in photos is a stable, no-auth zillowstatic.com URL you can store or hot-link.

Output dataset

Each row is pushed to the actor's default dataset as a flat JSON object with the schema shown above. Export to CSV, JSON, JSONL, XML, or Excel from the Apify Console.

Notes & limits

• The actor scrapes only publicly visible data -- no login, no agent-only MLS fields, no off-market records.
• Some listings (sponsored or partial markers) are intentionally skipped when they lack a property identifier.
• For technical / architectural details, see the repo's root README (no-browser HTTP-only stack, TLS impersonation, multi-step warmup, bbox quadtree, full operations playbook).