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Land-Based Data & Consumer Intelligence

Real Estate Property Data

155M U.S. residential and commercial property records with ownership, valuation, and characteristics.

Since 2018

Privacy-safe enterprise data

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Consent-first data sourcing

Overview

A national property database covering 155 million U.S. residential and commercial records. Each row carries owner information, assessed and market value, property characteristics (beds, baths, square footage, lot size, year built), and transaction history where available. Powers site selection, mortgage and insurance targeting, portfolio analysis, and residential market intelligence across all 50 states.

Need an API key + JSON sample?

For technical evaluation, we can provide a sample payload, schema notes, and delivery options (S3/SFTP/Snowflake) aligned to your workflow.

Data Types

  • Property address
  • Owner name & mailing address
  • Assessed and market value
  • Property characteristics
  • Transaction history

Delivery Formats

CSVTXTParquet

Key Features

  • 155M U.S. records
  • Residential + commercial
  • National coverage incl. HI/MT/WI
  • Periodic refresh

Sample fields

A representative slice of the Real Estate Property Data schema. The data dictionary shared during evaluation lists every field with its type, nullability, join keys, and refresh cadence.

FieldWhat it contains
parcel_idCounty or source parcel identifier for the property.
property_addressNormalized situs address for the parcel.
owner_nameRecorded legal owner name when disclosed.
owner_mailing_addressMailing address associated with the recorded owner.
assessed_valueLatest available assessed property value.
market_valueEstimated or reported market value when available.
square_feetRecorded building area in square feet.
year_builtRecorded construction year for the structure.
last_transaction_dateMost recent disclosed property transaction date.

How Real Estate Data Is Compiled

GSDSI's Real Estate Property Data is aggregated from county assessor and recorder offices, tax authorities, and commercial real-estate data partners. Each record carries the parcel address, legal owner name, current mailing address, assessed value and estimated market value, structural characteristics (square footage, bedrooms and bathrooms, lot size, year built, property class), and the most recent transaction date where disclosed. Commercial properties include additional firmographic attributes like NAICS category and tenancy type where observable. Records are refreshed on a periodic cadence that reflects county-level publication frequency: monthly where counties publish monthly, quarterly otherwise, so downstream users work with current ownership and valuation rather than stale rolls.

Common Applications for Property Data

Mortgage and refinance lenders use property records to pre-qualify direct-mail and digital audiences by loan-to-value band, owner tenure, and refinance propensity. Home-improvement retailers and solar/energy brands target by year-built and property type to reach homes in specific renovation windows. Insurance carriers use structural characteristics and assessed value to segment homeowner, renter, and commercial-line prospects and to enrich underwriting files. Real-estate investment firms combine property records with foot-traffic and mobility data to score acquisition candidates, evaluate trade areas, and monitor portfolio performance. Municipal and academic researchers use property data for housing-market research, displacement studies, and economic-indicator reporting.

Proof & buyer diligence for property data

  • Use parcel, ownership, and assessment records to screen deals and map the seller before LOI pricing.
  • Treat property data as an independent read that runs beside title, not a replacement for it.
  • Carry the assessment trajectory into the pro forma instead of relying on trailing tax expense.

Vendor comparisons

Use these buyer guides to compare this feed category with adjacent vendor offerings.

How buyers diligence property data

Property-data diligence depends on county refresh lag, ownership normalization, parcel matching, and field completeness. Buyers should sample states and counties that matter to the target portfolio rather than relying on national averages.

  • Review county-level freshness, assessor/recorder lag, and transaction-date availability.
  • Validate owner, mailing address, parcel, property class, and valuation completeness.
  • Test commercial vs. residential fields separately because source coverage differs.
  • Confirm whether delivery supports portfolio append, site selection, mortgage, or insurance workflows.

Frequently asked questions about Real Estate Property Data

What's in the Real Estate Property Data file?

155M U.S. residential and commercial property records. Each row carries parcel address, legal owner name + mailing address, assessed and market value, property characteristics (beds, baths, square footage, lot size, year built, property class), and transaction history where counties disclose it.

What's the source and refresh cadence?

Records are aggregated from county assessor and recorder offices, tax authorities, and commercial real-estate data partners. Refresh cadence is county-driven: monthly where counties publish monthly, quarterly otherwise. National coverage incl. HI, MT, and WI.

Is this an FCRA consumer report?

No. GSDSI is not a consumer reporting agency and this dataset is not a consumer report. It's sourced from publicly available county records and commercial data partnerships, and is intended for marketing, site selection, portfolio analysis, and research, not for consumer credit, insurance, employment, housing, or government-benefit decisions.

Can I filter by property type or value band?

Yes. Custom cuts by residential vs. commercial, property class (single-family, multi-family, condo, etc.), value band, year built, square footage, and geography (state, county, ZIP, custom polygon) are standard delivery options.

How does this link to consumer or mortgage signals?

Owner-name + mailing-address columns link deterministically to GSDSI's 301M+ consumer master, and the property itself links probabilistically to the GSDSI Mortgage & Refi Lead flow through address matching. Common use is enriching a consumer file with home-ownership + property-value context.

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