Zillow All-in-One Scraper

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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/"}]}

searchUrls accepts both plain region pages (like the one above — the actor resolves the area automatically) and zoomed map / search-results URLs that already carry filters and map bounds.

{
"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:

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).

Other real-estate actors

Part of the same Apify real-estate collection — every actor emits stable JSON you can union downstream: