Price Reduced Property Scraper

A price cut is usually the clearest sign a seller is ready to deal. The catch is finding the fresh ones, which normally means refreshing a portal all day or paying for a subscription you barely use. This scraper does the watching for you. Hand it a ZIP code or a state and it returns every home that just dropped its price as clean rows: the new asking price, the exact dollar amount cut, the full address, beds and baths, square footage, agent contacts, coordinates, and photos. One run gets you a price-drop dataset you can load into a spreadsheet, a CRM, or a model.

What you get

Every home comes back as one flat row, so columns line up when you load the results into a sheet or database. The fields sort into a few groups:

• Price and timing — currentPrice, priceDropAmount, closedPrice, dateListed, dateClosed, plus the flagPriceDrop marker
• Identity and status — homeId, listingRef, listingPath, saleStatus, and lifecycle flags like flagPending, flagContingent, flagAuction, flagFreshListing
• Home details — homeType, homeSubType, bedrooms, bathrooms, livingArea, lotArea, constructionYear, garageCount, hasVirtualTour
• Location — addressLine, cityName, stateName, stateCode, zipCode, geoLat, geoLng, countyName, countyFips, streetViewLink
• Media — heroPhoto, imageTotal, imageGallery
• Agents and source — leadAgentName, leadAgentEmail, leadAgentPhones, coAgentName, brokerBranding, feedName, openHouseSlots

Quick start

1. Press Try for free to open the input form.
2. Type a location into at least one of ZIP code, City, or State abbreviation.
3. Add any filters you like, such as an asking-price range, bedroom count, or home type.
4. Set a Total listings cap to keep spend predictable, choose a proxy, then press Start.
5. Once the run finishes, export the data as JSON, CSV, Excel, or XML.

Use cases

• Buyer hunting — pull every recent price drop in your target ZIP and reach out before the listing climbs back up
• Investor sourcing — sort by priceDropAmount to find sellers cutting hard and chasing a quick close
• Lead generation — collect listing agent names, emails, and phone numbers for homes that just got cheaper
• Market tracking — schedule a daily run and watch how reductions move across a neighborhood over time
• Deal screening — filter by price, beds, square footage, and build year to shortlist drops that fit your budget

Input

Field	Type	Required	Description
zipCode	string	One of zipCode, cityName, stateCode, or addressLine	Single 5-digit US ZIP code, the tightest location filter. Prefilled 78704.
stateCode	string	One of zipCode, cityName, stateCode, or addressLine	Two-letter US state code, best paired with another filter. Example TX.
cityName	string	One of zipCode, cityName, stateCode, or addressLine	Exact city name; pair with stateCode for clean results. Example Austin.
streetName	string	Optional	Limit results to homes on one named street, e.g. Congress Ave.
addressLine	string	Optional	One precise street address line.
homeCategories	array of strings	No	Keep only chosen home categories, e.g. single_family, condo.
featureTags	array of strings	No	Filter by features such as pool, hardwood_floors, central_air.
bedroomsFrom / bedroomsTo	integer	No	Fewest and most bedrooms to allow.
bathroomsFrom / bathroomsTo	integer	No	Fewest and most bathrooms to allow.
priceFrom / priceTo	integer	No	Current asking-price range in USD.
closedPriceFrom / closedPriceTo	integer	No	Closed-price range in USD.
closedDateFrom / closedDateTo	string	No	Closed-sale date window, written YYYY-MM-DD.
livingAreaFrom / livingAreaTo	integer	No	Interior living area range in square feet.
lotAreaFrom / lotAreaTo	integer	No	Lot size range in square feet.
builtYearFrom / builtYearTo	integer	No	Construction year range.
hoaFeeCap	integer	No	Highest monthly HOA fee to allow.
noHoaOnly	boolean	No	Return only homes with no HOA fee. Default false.
openHouseFrom / openHouseTo	string	No	Open-house date window, written YYYY-MM-DD.
batchSize	integer	No	Listings fetched per request. Default 150.
startIndex	integer	No	Position where pagination begins. Default 0.
maxRecords	integer	No	Hard cap on total listings collected. Default 3000.
runBudgetSeconds	integer	No	Whole-run time budget in seconds. Default 360.
requestBudgetSeconds	integer	No	Per-request time budget in seconds. Default 45.
proxyConfiguration	object	No	Proxies used for requests. Defaults to US datacenter.

Example input

{
    "stateCode": "TX",
    "cityName": "Austin",
    "homeCategories": ["single_family", "condo"],
    "priceTo": 800000,
    "bedroomsFrom": 2,
    "maxRecords": 200,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyCountry": "US"
    }
}

Output

Each price-reduced home becomes one flat JSON row. Every declared field shows up on a normal row, and any value the source does not provide comes back as null or empty so your dataset stays rectangular.

Example output

{
    "feedAttribution": true,
    "homeId": "9482736150",
    "listingRef": "2967451308",
    "listingPath": "1809-Kinney-Ave_Austin_TX_78704_M94827-36150",
    "saleStatus": "for_sale",
    "currentPrice": 524000,
    "closedPrice": null,
    "priceDropAmount": 26000,
    "dateListed": "2026-05-22",
    "dateClosed": "",
    "homeType": "single_family",
    "homeSubType": "",
    "bedrooms": 3,
    "bathrooms": "2",
    "livingArea": 1720,
    "lotArea": 6100,
    "constructionYear": 2004,
    "garageCount": 2,
    "addressLine": "1809 Kinney Ave",
    "cityName": "Austin",
    "stateName": "Texas",
    "stateCode": "TX",
    "zipCode": "78704",
    "geoLat": 30.2453,
    "geoLng": -97.7691,
    "countyName": "Travis County",
    "countyFips": "48453",
    "streetViewLink": "https://maps.googleapis.com/maps/api/streetview?location=30.2453,-97.7691",
    "heroPhoto": "https://ap.rdcpix.com/example/hero-2x.jpg",
    "imageTotal": 28,
    "imageGallery": [
        "https://ap.rdcpix.com/example/photo-1.jpg",
        "https://ap.rdcpix.com/example/photo-2.jpg"
    ],
    "hasVirtualTour": true,
    "flagComingSoon": false,
    "flagFreshListing": false,
    "flagPriceDrop": true,
    "flagNewBuild": false,
    "flagPending": false,
    "flagContingent": false,
    "flagAuction": false,
    "flagFractional": false,
    "feedId": "ACTRIS",
    "feedName": "Austin Board of Realtors",
    "feedType": "mls",
    "feedListingRef": "T7891234",
    "offersAgentContact": true,
    "leadMarket": "for_sale",
    "leadCategory": "advantage",
    "flagVaEligible": false,
    "productSet": ["co_broke"],
    "productBrand": "essentials",
    "leadAgentRole": "seller",
    "leadAgentName": "Daniel Reyes",
    "leadAgentEmail": "daniel.reyes@example.com",
    "leadAgentBrokerage": "Hill Country Realty",
    "leadAgentPhones": ["5125550174"],
    "coAgentRole": null,
    "coAgentName": null,
    "coAgentEmail": null,
    "coAgentBrokerage": null,
    "coAgentPhones": [],
    "brokerBranding": "Hill Country Realty",
    "searchPromos": [],
    "communityPromos": [],
    "openHouseSlots": [
        {
            "start_date": "2026-06-14T17:00:00Z",
            "end_date": "2026-06-14T20:00:00Z",
            "description": "Saturday open house",
            "time_zone": "America/Chicago"
        }
    ],
    "capturedAt": "2026-06-29T12:00:00.000000+00:00",
    "failureReason": null
}

Output fields

Field	Type	Description
feedAttribution	boolean	Attribution flag passed through from the listing feed
homeId	string	Stable internal identifier for the home
listingRef	string	Identifier of the specific listing
listingPath	string	URL slug for the listing
saleStatus	string	Current state, such as for_sale or sold
currentPrice	integer	Latest asking price in USD after any reduction
closedPrice	integer	Final closing price in USD, on sold homes only
priceDropAmount	integer	Dollar amount the asking price has been cut, in USD
dateListed	string	ISO 8601 date the listing went live
dateClosed	string	ISO 8601 date the sale closed, when applicable
homeType	string	Top-level home type, e.g. single_family
homeSubType	string	Finer home classification
bedrooms	integer	Number of bedrooms
bathrooms	string	Consolidated bathroom count
livingArea	integer	Interior living area in square feet
lotArea	integer	Outdoor lot size in square feet
constructionYear	integer	Year the home was built
garageCount	integer	Number of garage spaces
addressLine	string	Full street address line
cityName	string	City the home sits in
stateName	string	Full state name
stateCode	string	Two-letter US state code
zipCode	string	ZIP or postal code
geoLat	number	Latitude of the home
geoLng	number	Longitude of the home
countyName	string	County the home falls under
countyFips	string	County FIPS code
streetViewLink	string	Link to a street-level map preview
heroPhoto	string	Direct link to the headline photo
imageTotal	integer	How many photos accompany the listing
imageGallery	array	Direct image URLs for the home
hasVirtualTour	boolean	True when a Matterport 3D tour is attached
flagComingSoon	boolean	True when marked coming soon
flagFreshListing	boolean	True when flagged as a new listing
flagPriceDrop	boolean	True when the price recently dropped
flagNewBuild	boolean	True when newly built
flagPending	boolean	True when the sale is pending
flagContingent	boolean	True when the sale is contingent
flagAuction	boolean	True when sold at auction
flagFractional	boolean	True when ownership is fractional
feedId	string	Identifier of the originating feed
feedName	string	Name of the originating feed, e.g. the local MLS
feedType	string	Type of the originating feed
feedListingRef	string	Listing ID in the source feed
offersAgentContact	boolean	Whether a contact-an-agent action is offered
leadMarket	string	Lead market classification
leadCategory	string	Lead type for the listing
flagVaEligible	boolean	True when flagged Veterans United eligible
productSet	array	Distribution products attached to the listing
productBrand	string	Brand name tied to the products
leadAgentRole	string	Role of the primary representative
leadAgentName	string	Name of the primary representative
leadAgentEmail	string	Email for the primary representative
leadAgentBrokerage	string	Office handling the primary representative
leadAgentPhones	array	Phone numbers for the primary representative
coAgentRole	string	Role of the secondary representative
coAgentName	string	Name of the secondary representative
coAgentEmail	string	Email for the secondary representative
coAgentBrokerage	string	Office handling the secondary representative
coAgentPhones	array	Phone numbers for the secondary representative
brokerBranding	string	Affiliated agent branding label
searchPromos	array	Search-level promotions attached to the listing
communityPromos	array	Community-level promotions attached to the listing
openHouseSlots	array	Scheduled open house entries with times and notes
capturedAt	string	ISO 8601 timestamp of when the row was captured
failureReason	string	Reason a row failed; null on success

Tips for best results

• Always set a location. Give the scraper at least one of zipCode, cityName, stateCode, or addressLine, or it has nothing to search against.
• Start small. Drop maxRecords to around 50 on your first run so you can confirm the fields match your pipeline before pulling thousands.
• Pair cityName with stateCode. A city name on its own can match across several states; the two together keep results tight.
• Sort by priceDropAmount. The biggest cuts usually point to the most motivated sellers, so that column is a fast way to rank the list.
• Switch proxy tiers if requests start failing. US datacenter clears most runs; move to residential if you hit repeated errors.
• Raise requestBudgetSeconds toward 60 to 90 on slower proxies, and give runBudgetSeconds more room for large states.

How can I use price-drop property data?

How can I use the Price Reduced Property Scraper to find motivated sellers? Enter a target ZIP code or city and the scraper returns every home with a recent price cut, each carrying the new currentPrice, the priceDropAmount, the street address, beds and baths, and the listing agent's name, email, and phone. Sort by priceDropAmount to put the deepest reductions at the top, then export the rows straight into your CRM.

How can I track price reductions across a neighborhood over time? Save your filters and schedule the run on Apify to repeat daily. Every row stamps capturedAt and carries flagPriceDrop along with dateListed, so you can diff one day's dataset against the last and watch how asking prices move block by block.

How can I scrape discounted home listings across a whole state? Pass a stateCode such as TX, raise maxRecords, and the scraper paginates through the available inventory and hands back one row per home. Filter by homeCategories, an asking-price range, or bedroom count to keep only the reduced listings that match your buy box.

How can I pull listing agent contacts for homes that just dropped in price? Each row includes leadAgentName, leadAgentEmail, leadAgentPhones, and leadAgentBrokerage, plus the same set for a co-agent when one is present. Combine those with the price and location fields to build an outreach list aimed only at sellers who have already shown they will negotiate.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.