Property data, United States
Neighborhood & ZIP Intelligence
ZIP code demographics, home values, rents, income, schools and housing stock in one row per ZIP, with county and metro rollups.
One row per ZIP code that answers the questions a product, a territory model or a site-selection analysis asks first: what homes are worth, how fast values and rents are moving, who lives there, what they earn, how old the housing stock is and how the schools rate. Property metrics are computed from our own assessor, transaction and listing files rather than sampled, so the median value in a ZIP is the median of the parcels in it.
Demographic fields come from the Census and licensed consumer data, normalized to the ZIP. School and crime indicators come from public sources and are expressed as indices so they compare across states. County, metro and state rollups are included in the same file, and block group or tract versions are available on request.
The file drops into a warehouse or a consumer product without a join. Teams use it as the geography layer under a home-value feature, as the basis of insurance and lending territory models, for retail and franchise site selection, and to rank ZIPs for marketing spend.
Sample rows
Illustrative and synthetic. Real samples for your geography are a reply away.
| zip | city | state | median_value | appreciation_1y | median_rent | owner_occ_pct | median_income | school_rating | crime_index | median_year_built |
|---|---|---|---|---|---|---|---|---|---|---|
| 606•• | Chicago | IL | $7••,000 | 4.1% | $2,6•• | 52% | $1••,000 | 8 | 62 | 1938 |
| 37064 | Franklin | TN | $8••,000 | 2.7% | $2,9•• | 74% | $1••,000 | 9 | 31 | 1996 |
Schema
| Field | Type | Notes |
|---|---|---|
| zip | identifier | personal data |
| city | text | non-personal |
| state | text | non-personal |
| median_value | currency | non-personal |
| appreciation_1y | text | non-personal |
| median_rent | currency | non-personal |
| owner_occ_pct | number | personal data |
| median_income | text | non-personal |
| school_rating | text | non-personal |
| crime_index | text | non-personal |
| median_year_built | number | non-personal |
Abridged. The full data dictionary ships with every sample and lists every field, its fill rate and its source.
Used for
- ZIP-level home value and market pages in consumer products
- Insurance and lending territory models
- Retail, franchise and clinic site selection
- Ranking ZIPs for direct mail and digital spend
- Neighborhood context on a property report
How it is built
Property metrics are aggregated from parcel-level assessor, recorder and listing data: median and quartile values, one and five year appreciation, median asking and estimated rent, owner-occupancy share, housing stock by decade built and structure type, and market velocity from listing and sale dates.
Demographics are Census-derived and refreshed with each release, with licensed consumer data used to fill the age, household and income fields between releases. School ratings and crime figures are pulled from public sources and converted to indices with the source and date retained.
Every ZIP carries its county, CBSA and state so the file rolls up cleanly, and the ZIPs that are post office boxes or single-building ZIPs are flagged rather than dropped.
Questions we get
How is this different from free Census data?
Census tables give you demographics on a Census schedule. This file joins them to current property values, rents, appreciation and housing stock computed from live parcel and listing data, refreshed monthly, and delivers the result as one flat row per ZIP.
What are the best sources for ZIP code demographic data?
For raw demographics, the Census Bureau's ACS is the reference and it is free. For property metrics you need a parcel-level source, and for a single file that has both you need someone to do the join and keep it current. That is what this dataset is.
Do you have block group or tract?
Yes, on request. ZIP is the default because it matches how most teams target and report.
Can we compare ZIPs across states?
Yes. Indices are normalized nationally, and value and rent fields are in dollars, so a ranking across states is meaningful.
How is it delivered and priced?
A flat file, monthly, as CSV or Parquet, or a one-time pull. Priced as a flat license for the national file or per ZIP for a metro cut.