Real Estate Deal Finder

Find motivated sellers, not just listings.

Real Estate Deal Finder scrapes Zillow across the US and Canada and returns what deal sourcing actually needs: the property, the person to call, and the signals that say a seller wants out.

Every row includes:

• Property facts — address, price, beds, baths, sqft, lot size, year built, status, coordinates
• Agent contact — listing agent name, phone, and brokerage
• Deal signals — days on market, full price-cut history, price per sqft, and list price against Zestimate and tax assessment
• A distress score — transparent and auditable, built from price cuts, time on market, and motivation language like as-is, motivated seller, estate sale, and cash only. Every factor that contributed is recorded on the row, so you can see exactly why a property scored high

Most scrapers hand you listings. This one tells you which listings are worth a phone call — and gives you the number to dial.

Paste a Zillow search URL, set how many properties you want, and run. Export as JSON, CSV, or Excel, or pull straight from the API. Schedule runs to catch new price cuts the day they land.

Built for wholesalers, investors, bird dogs, and agents working stale or expired inventory.

Cost control is built in. You set the property cap per run and nothing goes past it. Every field is optional except listing ID and URL, so a missing agent phone never costs you the whole row.

Coming next: Zoopla, Rightmove, Redfin, and Inmuebles24.

Why use Real Estate Deal Finder?

Most real estate scrapers answer "what is for sale?" That question is already well served. This Actor answers a harder one: "who is likely to sell at a discount, and how do I reach them?"

• Wholesalers and investors — build a call list ranked by seller motivation instead of reading listings one by one
• Bird dogs — surface stale and price-cut inventory in a target ZIP before it hits the usual channels
• Agents — find expired, withdrawn, and long-sitting listings worth a conversation
• Analysts — track price-cut velocity and days-on-market trends across a market over time

Because it runs on the Apify platform, you also get scheduling, a REST API, webhooks, integrations with Make and Zapier, proxy rotation, and run monitoring without building any of it yourself.

How to use Real Estate Deal Finder

1. Open Zillow and search the way you normally would — set your area, price range, and any filters.
2. Copy the resulting URL from your browser.
3. Paste it into the Start URLs field on the Input tab.
4. Set Max properties to cap how many results you want. The default is 25.
5. Click Start and wait for the run to finish.
6. Open the Output tab, or download the dataset as JSON, CSV, or Excel.

To keep a list fresh, use the Schedule tab to run it daily or weekly. New price cuts appear as soon as Zillow publishes them.

Input

Field	Type	Description
startUrls	array	Zillow search or property URLs. US and Canadian URLs both work.
maxProperties	integer	Maximum properties to return. Default 25. Caps both output size and cost.
maxRequestsPerCrawl	integer	Safety ceiling on requests during enrichment. Rarely binds.
brightDataApiKey	string	Optional. Leave blank to use the system key.

Example:

{
    "startUrls": [{ "url": "https://www.zillow.com/whitby-on/houses/" }],
    "maxProperties": 25
}

Output

Each property becomes one dataset row. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

{
    "zpid": "2078143210",
    "url": "https://www.zillow.com/homedetails/...",
    "address": { "street": "1428 Elm St", "city": "Whitby", "state": "ON", "zip": "L1N 3B4" },
    "price": 649000,
    "beds": 3,
    "baths": 2,
    "sqft": 1740,
    "yearBuilt": 1974,
    "status": "FOR_SALE",
    "latitude": 43.8975,
    "longitude": -78.9428,
    "agentName": "Jordan Avery",
    "agentPhone": "+1-905-555-0142",
    "brokerageName": "Lakeshore Realty",
    "daysOnMarket": 96,
    "priceHistory": [
        { "date": "2026-05-02", "event": "Listed for sale", "price": 719000 },
        { "date": "2026-07-18", "event": "Price change", "price": 649000 }
    ],
    "priceCutCount": 1,
    "priceCutTotalPct": 9.7,
    "pricePerSqft": 373,
    "motivationKeywords": ["96 days on market", "1 price cut(s)", "price down 9.7%", "as-is"],
    "distressScore": 74
}

Data fields

Field	Description
zpid, url	Listing identifier and link. Always present
address, latitude, longitude	Split address plus coordinates
price, beds, baths, sqft, lotSize, yearBuilt, propertyType, status	Core property facts
agentName, agentPhone, brokerageName	Listing agent contact, where published
daysOnMarket	Days since listing
priceHistory, priceCutCount, priceCutTotalPct	Full price timeline and cut totals
pricePerSqft, zestimate, priceVsZestimatePct, taxAssessedValue	Valuation comparisons
motivationKeywords	Every factor that contributed to the score
distressScore	Composite seller-motivation rating

Every field except zpid and url may be null. A property with no published agent phone is still returned, with that field empty, rather than being dropped.

priceCutCount and priceCutTotalPct measure different things and are both worth reading. The count is explicit price-change events. The percentage is how far the asking price has fallen since this campaign opened, which also captures a seller who withdrew and relisted lower without ever filing a price change — often the more motivated seller of the two. Sorting on the count alone will miss them. Where a listing has no opening price on record, the percentage is null rather than 0, so an unknown is never read as "no cut".

How much does it cost to scrape Zillow?

Pricing is pay per event, so you are charged for results rather than for compute time. Two events are billed: one per row returned, and a higher one per property that gets a dedicated second lookup. That second lookup is what buys square footage, year built, tax assessment, Zestimate, and the full price timeline the cut signals are computed from. How much it adds varies by market — see the Canada note below, where several of those fields do not exist at source.

The practical control is maxProperties. It caps output and spend together — raise it for a bigger pull, lower it to sample a market cheaply. A run cannot exceed the cap you set, so a broad search URL cannot produce a surprise bill.

Tips

• Filter on Zillow first. Narrowing by price, beds, or property type before copying the URL is free; filtering afterwards is not. Treat Zillow's filters as strong hints rather than hard limits — a price-banded search still returns some listings just outside the band, the same way it does in your browser.
• Raise maxProperties when you want stale inventory. Discovery favours recently listed properties, so a small run is mostly fresh listings — and fresh listings have no price cuts and little time on market to score on. A wider pull reaches deeper into a market's older inventory.
• Start at the default 5. Confirm the data is what you expect, then raise maxProperties.
• Give a big pull a bigger timeout. Collection happens upstream and its latency varies a lot with how busy the source is — the same three-property search has finished in two minutes and in eight. If a run ends early saying it ran out of time, raise the run timeout rather than lowering the cap. Rows already collected are always returned; the run never throws away what it has.
• Sort by distressScore descending and work top-down — that is the whole point of the field.
• Schedule daily on a tight geography. Price cuts are most actionable the day they appear.
• Check motivationKeywords before calling. It shows why a property scored the way it did.

What affects how many rows you get back

maxProperties is a ceiling, not a guarantee. A run can return fewer rows when the search area holds less inventory than you asked for, or when an upstream page fails to load — a 25-property pull on a large market returned 22 in testing, with three pages erroring. You are charged for what you receive, so a short run costs less rather than costing you the difference.

FAQ, disclaimers, and support

Does it work for Canada? Yes, with one caveat worth knowing before you run it. Zillow publishes Canadian listings through partnerships with 250+ brokerages, and coverage is strongest in Ontario, BC and Alberta, thinner in Quebec and Atlantic Canada. But Zillow computes no Zestimate and holds no tax-assessment data outside the US, and Canadian listings frequently publish only the brokerage rather than a named agent. Canadian rows are therefore scored on fewer factors than US rows — the score is still honest, because absent inputs are skipped rather than counted as zero, but it is built on less evidence. For the richest signal, use US markets.

Why is an agent phone missing on some rows? Not every listing publishes one — this is common on Canadian listings, where the brokerage is often the only published contact. The row is still returned with the field empty rather than discarded.

Is distressScore a prediction? No. It is a transparent sum of observable factors, all listed in motivationKeywords. It ranks candidates for a conversation; it does not predict a sale.

Is scraping legal? This Actor collects publicly available listing data. Laws and site terms vary by jurisdiction and change over time. Review your local regulations and each site's terms before using the data commercially, particularly for outreach to contacts.

Found a bug or want another portal? Open an issue on the Issues tab. Custom versions and additional markets are available on request.