US Parcel Ownership with Owner Mailing Addresses

What’s in the listing

Civly compiles public records into analytics-ready datasets. This product is parcel ownership with owner mailing addresses, compiled from county assessor and land-record sources. Every parcel carries the owner’s name and normalized name, mailing address, the property’s situs address, sale history with prices, assessed and market values, acreage, property type, and owner-occupied and homestead flags.

Common uses: owner outreach and absentee-owner analysis, market research, land research, and investigative work. Data refreshes weekly, and every record carries source attribution and a refresh date.

Data dictionary — PARCEL_OWNERSHIP.PARCEL_OWNERS

One view serves the trial and the subscription. During the free trial it returns Wyoming and the District of Columbia only. Subscribers see all 22 states. 36 columns, uppercase names.

Sample queries

After installing, set your worksheet’s database selector to the installed database and these run as written.

-- Parcel counts by state (trial returns WY and DC)
SELECT STATE, COUNT(*) AS PARCELS, SUM(SALE_PRICE) AS SOLD_VALUE
FROM PARCEL_OWNERSHIP.PARCEL_OWNERS
GROUP BY STATE ORDER BY PARCELS DESC;

-- Absentee owners: mailing state differs from parcel state
SELECT OWNER_STATE, STATE AS PARCEL_STATE, COUNT(*) AS PARCELS
FROM PARCEL_OWNERSHIP.PARCEL_OWNERS
WHERE OWNER_STATE IS NOT NULL AND OWNER_STATE <> STATE
GROUP BY 1, 2 ORDER BY PARCELS DESC LIMIT 25;

-- All parcels owned by a name (use the normalized column)
SELECT OWNER_NAME, OWNER_STREET, OWNER_CITY, OWNER_STATE, OWNER_ZIP,
       SITUS_ADDRESS, SITUS_CITY, SALE_DATE, SALE_PRICE, ACRES
FROM PARCEL_OWNERSHIP.PARCEL_OWNERS
WHERE OWNER_NAME_NORM = UPPER('Jane Q Public');

Sourcing and attribution

Source data is county assessor and land-record data collected from public county sources across the 22 covered states. Civly cleans, normalizes, and standardizes owner names and addresses and stamps every record with its source attribution and refresh date. When you publish analysis based on this dataset, credit the county sources and Civly as compiler.

Questions about this dataset: matthew@civly.ai