FSBO Owner Scraper

Finding out who actually owns a property usually means crawling through county recorder sites or paying per-record fees, and you still end up guessing half the time. This scraper skips all of that. Hand it a US street address and it returns the names on the title, an equity estimate, tax and parcel records, and the core property facts as clean, structured data. Drop in one address or a list of thousands. Each one comes back as its own row, ready to load into a CRM or spreadsheet.

What you get

Every address you submit turns into one row with a steady shape, so your columns line up even when a field is unavailable. The data falls into a few groups:

• Owner — primaryOwner, secondaryOwner, plus the full ownerInfo record
• Property — propertyInfo with location, size, and other characteristics
• Financials — equityInfo for value and equity figures, taxInfo for assessment and tax data
• Parcel — parcelInfo with lot identifiers and parcel-level details
• Run metadata — queryAddress, collectedAt, and errorMessage

Quick start

1. Click Try for free and open the input form.
2. Paste your US addresses into Property addresses — full or partial both work.
3. Choose a proxy type and set a Results limit if you want to cap the run.
4. Hit Start, then export to JSON, CSV, Excel, or XML once it finishes.

Use cases

• Real estate wholesaling — turn a list of target addresses into owner names you can contact directly
• Investor lead generation — qualify deals faster by pulling equity estimates before you reach out
• Skip tracing — start from an address and recover the people on the title
• Direct mail campaigns — build owner-name mailing lists from a batch of properties
• Market research — gather ownership and tax data across a neighborhood or ZIP code
• CRM enrichment — append owner and parcel details to addresses you already track

Input

Field	Type	Required	Description
addressList	array of strings	Yes	US property addresses to look up. Full or partial addresses both work. Each entry is handled on its own.
resultsLimit	integer	No	Cap on how many addresses to process per run. Default 5000.
timeoutSeconds	integer	No	Seconds to wait per request before timing out. Default 45; raise it on slower proxy tiers.
proxyConfiguration	object	No	Proxies used for requests. Defaults to Datacenter; switch to Residential only if you hit blocks.

Example input

{
    "addressList": [
        "742 Evergreen Terrace, Springfield, IL 62704",
        "55 Maple Court, Austin TX",
        "210 Harbor View Rd, Seattle WA"
    ],
    "resultsLimit": 5000,
    "timeoutSeconds": 45,
    "proxyConfiguration": {
        "useApifyProxy": true
    }
}

Output

Each address produces one row. Owner names and the nested record objects are always present in the shape below — fields that aren't available come back as null so the dataset stays rectangular.

Example output

{
    "queryAddress": "742 Evergreen Terrace, Springfield, IL 62704",
    "primaryOwner": "JANE A DOE",
    "secondaryOwner": "JOHN R DOE",
    "propertyInfo": {
        "address_details": {
            "city": "Springfield",
            "state": "IL",
            "zip": "62704"
        },
        "bedrooms": 3,
        "bathrooms": 2,
        "square_feet": 1840
    },
    "ownerInfo": {
        "owner_occupied": true,
        "mailing_address": "742 Evergreen Terrace, Springfield, IL 62704"
    },
    "equityInfo": {
        "estimated_value": 312000,
        "estimated_equity": 168000
    },
    "taxInfo": {
        "assessed_value": 254000,
        "tax_year": 2024
    },
    "parcelInfo": {
        "apn": "14-21-308-016-0000",
        "lot_size_acres": 0.21
    },
    "collectedAt": "2026-06-29T12:00:00.000000+00:00",
    "errorMessage": null
}

Output fields

Field	Type	Description
queryAddress	string	The address exactly as you submitted it
primaryOwner	string	Name of the first person or entity on the title
secondaryOwner	string	Name of a co-owner on the title, when there is one
propertyInfo	object	Core property facts such as location, size, and characteristics
ownerInfo	object	Ownership record details beyond the listed owner names
equityInfo	object	Estimated equity and related value figures for the property
taxInfo	object	Assessment and tax data tied to the parcel
parcelInfo	object	Parcel-level identifiers and lot information
collectedAt	string	ISO 8601 timestamp of when the row was captured
errorMessage	string	Reason a lookup failed; null on success

Tips for best results

• Start small. Run 10 addresses before a large batch so any formatting quirks show up early.
• Add city and state. A street paired with city/state or a ZIP code matches far more reliably than a street alone.
• Cap test runs with resultsLimit. Keep it low while you confirm the output fits your pipeline, then raise it for the full list.
• Switch to Residential if you get blocked. Datacenter clears most lookups; residential helps when requests start failing.
• Read errorMessage first. When a row has no owner, that field explains why — usually no match was found for the address as written.

How can I use US property owner data?

How can I use the FSBO Owner Scraper to find off-market deals? Feed it the addresses of properties you're watching and it returns the owner names plus an equity estimate for each one. High-equity, owner-occupied records often signal motivated sellers, so you can prioritize who to contact before a property ever hits the market.

How can I look up a property owner from just an address? Paste a single address into addressList and run it. The scraper matches the address, then returns primaryOwner and secondaryOwner along with the full ownerInfo, taxInfo, and parcelInfo records — no county-by-county searching required.

How can I build a skip-tracing or direct-mail list from a batch of addresses? Drop your whole address list into addressList and set resultsLimit to cover the batch. Each address comes back as one row with the title-holder names and parcel data, which you can export to CSV and load straight into a mail-merge or skip-tracing workflow.

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.