# Scrape Zillow · Listings, Zestimates and market data

> Turn Zillow into structured real-estate data: listings, property details, Zestimates, price history and market data, by city, ZIP or map bounds. One call, at scale, with Fetch.

## Every pin is a record.

Zillow is a map of listings. Fetch turns each one into structured data: price, beds, baths, sqft, Zestimate and more.

## Search the map, not the site.

Point Fetch at a city, a ZIP, or a drawn map region. For-sale, sold, or rentals, the response comes back as the same typed listings.

- By city zillow.com/ {city}-{state} /

- By ZIP zillow.com/homes/ {zip} _rb/

- Map bounds ?searchQueryState= {bounds}

- Status for-sale · sold · rentals

## Watch the price move.

Every listing carries its full price history. Scrape the events, not just today's number, and see how a home really priced.

## Zestimate, list, and sold.

The three numbers that never agree, side by side for every property, so your model can learn the gap.

Zestimate

$761K

Zillow's model estimate.

List price

$749K

What the seller asked.

Last sold

$742K

What it closed at.

## Zillow does not want a bot.

Between the map and the data sits a stack of defenses. Fetch clears each one so you never see them.

Bot walls

PerimeterX and CAPTCHA gates trip on the first burst. A real browser from rotating egress clears them.

Lazy map tiles

Listings load as you pan and scroll the map. The page renders fully, then every card is read.

Detail behind clicks

Price history and facts open in panels and tabs. They are triggered and captured for you.

Rate limits

Repeat hits from one IP get throttled fast. Each call runs from fresh egress, so volume holds.

## Own the whole market.

One address or an entire metro, the shape stays the same. Structured Zillow data, without the parsing or the blocks.

What teams build with it

_Canonical HTML: https://www.zenrows.com/scrape/zillow_

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