Zillow Price Drop Scraper

What does Zillow Price Drop Scraper do?

Zillow Price Drop Scraper extracts Zillow listings with a detected asking-price reduction and returns a clean row for each property. It is built for real-estate agents, investors, wholesalers, and operations teams that want a focused feed of current opportunities instead of a full dump of every home in a market.

What data can you extract from Zillow price drops?

• Price movement — current price, previous price, signed Zillow price change, dollar drop, percentage drop, reduction label, and change timestamp
• Property identity — ZPID, listing URL, full address, street, city, state, ZIP code, latitude, and longitude
• Home facts — home status, home type, bedrooms, bathrooms, living area, lot size, days on Zillow, Zestimate, and Rent Zestimate
• Listing context — broker, source search URL, scrape timestamp, and photo URLs exposed on the result page

The actor calculates previousPrice from Zillow's current price and signed price change, so every emitted row can be sorted by the size of the opportunity. priceDropAmount and priceDropPercent are positive values for easy threshold filters; the original priceChange remains negative for a reduction.

How to use Zillow Price Drop Scraper

1. Open a Zillow price-reduced or saved search-result page and copy its URL.
2. Paste one or more URLs into the Zillow search URLs input.
3. Set the maximum listings and pages, then optionally require a minimum dollar or percentage reduction.
4. Click Run. Use Dry run first if you want to inspect matched versus written rows without creating dataset records.
5. Download the output as JSON, CSV, or Excel, or read it through the Apify dataset API.

The actor follows Zillow's own next-page links, deduplicates by ZPID across all supplied URLs, and filters before output is written. A record rejected by a drop threshold is not emitted or billed as a dataset item.

How much does it cost?

Pricing starts at $1.50 / 1,000 price-drop listings. One billable unit is one listing written to the default dataset after duplicate and threshold filters. Apify free credits cover small tests. Set a low maximum listings value while validating a new market; page fetching itself does not create dataset charges.

Residential Apify Proxy is enabled by default because Zillow can challenge datacenter traffic; proxy transfer can affect platform usage, so the input includes an explicit proxy toggle. The measured deployed smoke cost is about $0.12 / 1,000 before the actor event price, leaving room for the listed price.

Input

searchUrls is required and accepts one or more Zillow search URLs. Use maxItems to cap all output, maxPages to control pagination per URL, minDropUsd for a dollar threshold, and minDropPercent for a percentage threshold. The default proxy configuration uses a U.S. residential group. A minimal input looks like this:

{
  "searchUrls": [
    { "url": "https://www.zillow.com/new-york-ny/price-reduced/" }
  ],
  "maxItems": 50,
  "maxPages": 2,
  "minDropUsd": 10000
}

Output

Each row contains the listing identity, current and previous asking prices, drop size, property facts, broker, photos, source URL, and scrape timestamp. A real output row is shaped like this:

{
  "zpid": "32035196",
  "detailUrl": "https://www.zillow.com/homedetails/160-11-24th-Ave-Flushing-NY-11357/32035196_zpid/",
  "address": "160-11 24th Avenue, Whitestone, NY 11357",
  "city": "Flushing",
  "state": "NY",
  "zipcode": "11357",
  "price": 1298000,
  "previousPrice": 1328000,
  "priceChange": -30000,
  "priceDropAmount": 30000,
  "priceDropPercent": 2.259036144578313,
  "datePriceChanged": "2026-07-09T07:00:00.000Z",
  "priceReduction": "$30,000 (Jul 9)",
  "homeStatus": "FOR_SALE",
  "homeType": "SINGLE_FAMILY",
  "beds": 4,
  "baths": 3,
  "livingArea": 1865,
  "brokerName": "MAB Realty Group Inc",
  "sourceUrl": "https://www.zillow.com/new-york-ny/price-reduced/",
  "scrapedAt": "2026-08-08T16:01:00.000Z"
}

Integrations

Use the Apify API, webhooks, schedules, Make, Zapier, n8n, or a small Python/Node.js job to send price-drop rows into a CRM, spreadsheet, alert channel, or market dashboard. The dataset URL is available immediately after a successful run.

Related actors

• Zillow Search Scraper — broad for-sale and rental search extraction when you need the full result set.
• Zillow Detail Scraper — detail-page enrichment for history, agent, tax, school, and amenity fields.

FAQ

How does Zillow Price Drop Scraper work?

It reads the rendered data Zillow places in each search-result page, follows the page's own pagination link, normalizes the listing fields, and emits only records with a price reduction. It does not open a detail page for every listing.

Can I use Zillow Price Drop Scraper as an API?

Yes. Start a run through the Apify API with the same JSON input, then read the default dataset through its API URL. You can also attach a webhook or schedule recurring runs in Apify.

Can I use Zillow Price Drop Scraper in Python or Node.js?

Yes. Use the official apify-client package to start the actor and list its dataset items.

What does this actor access?

It accesses publicly rendered Zillow search-result pages supplied in searchUrls. No Zillow account, login, or Zillow API key is required. Search pages are fetched live for each run.

Is it legal to scrape Zillow?

The actor is intended for publicly visible listing data. Your use of the output must follow applicable laws, contracts, and platform requirements; review your use case with qualified counsel when personal or commercial data is involved.

Why is a listing missing from the output?

The source must expose a price change on the supplied search page. Listings without a detectable reduction are intentionally skipped, as are duplicate ZPIDs and rows that fail your dollar or percentage threshold. For a larger feed, provide a saved price-reduced URL and raise maxPages or split the market by ZIP code.

Your feedback

If Zillow changes its search-page fields or you need another price-drop filter, use the Issues tab on the actor page. Suggestions for new buyer-facing fields are welcome when the source exposes them consistently.