What is commercial property data?
Commercial property data refers to the records, measurements, and intelligence that describe a commercial building and the parcel it occupies.
That includes transaction history, physical building attributes like roof condition and square footage, risk and hazard scores, tenant and occupancy details, and mortgage or lien records. Lending, insurance, real estate investment, and construction teams use commercial property data to evaluate risk, price assets, and plan projects without visiting a property in person.
No single source captures the full picture. County assessors track ownership and tax valuations. MLS platforms log sale prices. But physical building attributes are often missing or outdated in public records. The details that determine whether a roof can survive another storm season, or whether a structure matches its listed classification, rarely show up in assessor databases.
Below, we break down the major commercial property data categories, explain where each one comes from, identify the gaps that trip up underwriters and adjusters, and show how high-resolution aerial imagery and AI-driven attribute extraction close those gaps across large portfolios.
Key takeaways
- Commercial property data spans five major categories: transaction history, physical building attributes, risk and hazard scoring, tenant and occupancy details, and mortgage or lien records.
- County assessor records leave significant gaps in building classifications, square footage, and roof condition, forcing lenders, insurers, and portfolio managers to work with incomplete information.
- High-resolution aerial imagery paired with AI-driven extraction closes the physical-attribute gap that transaction-focused platforms like CoStar and CompStak weren't designed to address.
- Eagleview's 60+ petabyte property data ecosystem, built from 3.5 billion aerial images covering 94% of the U.S. population, delivers 125+ verified building attributes at the parcel level.
Major data categories
No single database holds all commercial property data. The information spreads across overlapping datasets, each maintained by a different source and updated on a different schedule. The major categories include:
- Transaction data. Sale prices, deed transfers, and comparable sales are recorded through county recorder offices and platforms like CoStar and CompStak. Appraisals and investment analysis depend on transaction data, but comps tell you what a property sold for, not what physical shape the building is in.
- Physical building attributes. Roof type, pitch, material, square footage, number of stories, building footprint, wall types, and condition. Sources include assessor records, inspection reports, and aerial imagery analyzed by machine learning models. Public records are weakest here, and the stakes are highest for insurance carriers and lenders.
- Risk and hazard data. A property's exposure to floods, wildfire, seismic activity, and other natural hazards. FEMA flood maps, state fire agencies, and private risk modelers contribute here. Carriers and underwriters pair hazard data with building conditions to set premiums and evaluate collateral.
- Tenant and occupancy data. Who's leasing space, how much they're paying, and when leases expire. Brokers and investors use this for income analysis and deal sourcing. Sources range from CoStar and Yardi Matrix to direct landlord reporting.
- Mortgage and lien records. Debt tracked against a property, including loan amounts, maturity dates, and lender identity. County recorder offices and commercial mortgage databases house these records. Debt brokers, originators, and investors looking for distressed opportunities rely on them heavily.
Where public records fall short
County assessor databases are the default starting point for commercial property data, and they're useful for ownership lookups, tax valuations, and basic parcel boundaries. But they weren't built for the kind of building-level detail that underwriters, adjusters, and portfolio managers need. The same problems show up across jurisdictions:
- Vague building classifications. A county office might label a property "commercial" without distinguishing between a single-story retail strip and a three-story mixed-use building. That distinction matters for replacement cost, risk scoring, and zoning analysis.
- Incomplete or self-reported measurements. Square footage records are often missing or based on what the owner reported at the time of construction. Roof age, material, and condition are rarely tracked, even though they directly affect insurance pricing and capital planning.
- Stale records. A property last inspected in 2014 may have gone through a full roof replacement, an addition, or significant deterioration since then. The assessor record doesn't reflect any of that, and there's no trigger for an update until the next reassessment cycle.
For teams that manage portfolios of hundreds or thousands of properties, these gaps multiply fast. When you're evaluating collateral for a commercial mortgage-backed security, a missing roof age on 30% of the parcels amounts to a material blind spot, not a minor data gap.
How different industries use commercial property data
Mortgage underwriting and collateral risk
Mortgage underwriters rely on property data to assess the physical condition of collateral backing a loan. Roof age and condition top the checklist, because a 25-year-old asphalt shingle roof signals replacement costs that affect the loan-to-value ratio. Building footprint, wall height, and structure type all feed into replacement cost models.
When this data is missing from public records, lenders send inspectors to verify conditions onsite or they work with incomplete information and accept more risk than they realize.
Our property data platform delivers verified roof measurements, condition assessments, and 125+ AI-extracted building attributes at the parcel level. Underwriting teams get the physical detail they need without the site visit.
Insurance underwriting and claims
Insurance carriers need accurate structure identification and roof measurements to price policies and process claims. Pitch, material, area, and the presence of features like skylights or solar panels all affect risk scoring and replacement cost calculations. After a storm, adjusters need pre-loss imagery and measurements to compare against damage reports.
Sending adjusters to climb every roof doesn't scale during catastrophic events when thousands of claims come in at once. Aerial imagery with AI-driven analysis lets carriers assess properties remotely, validate claims faster, and reduce disputes tied to missing or inaccurate pre-loss documentation. Eagleview's aerial maps for commercial real estate give claims teams a verified baseline they can reference before and after a loss event.
Portfolio management and capital planning
Real estate portfolio managers overseeing hundreds or thousands of commercial properties need consistent, standardized building attributes across every parcel. They're tracking roof age distributions to forecast capital expenditures, monitoring building condition trends to prioritize repairs, and running trend analysis to identify properties at risk of deferred maintenance.
Manual parcel-by-parcel assessment is slow and inconsistent. Different inspectors use different methods. Reports arrive in different formats. Data ages out before the analysis is finished. A centralized property intelligence platform with API access lets portfolio teams pull standardized attributes into their own systems across thousands of parcels.
Approaches to closing the physical-attribute gap
The market has developed several approaches for filling in the building details that public records miss. Each one trades off coverage, accuracy, and cost differently.
| Approach |
How it works |
Strengths |
Limitations |
| Crowdsourced comps |
Users contribute transaction data and some property details to shared databases. |
Strong for transaction data where deal professionals have an incentive to share and receive comps. |
No built-in verification for physical building attributes. Data quality depends entirely on who contributes. |
| Satellite imagery |
Broad geographic coverage captured from orbit at low resolution. |
Useful for detecting land-use changes over large areas at low cost per parcel. |
Pixel density limits building-level detail. Measuring roof pitch, identifying material type, or counting solar panels requires closer capture. |
| High-resolution aerial imagery with AI |
Manned aircraft capture at low altitude, paired with machine learning models trained on billions of images. |
Resolution supports precise measurements and feature identification. Extracts 125+ attributes automatically. |
Higher per-capture cost than satellite. Coverage depends on flight schedules and geography. |
How Eagleview fills the gap
We built our property data ecosystem around a gap other platforms weren't designed to fill. Transaction databases like CoStar and CompStak capture who bought what, for how much, and when. Eagleview focuses on the building itself.
And that focus runs deep: 3.5 billion high-resolution aerial images covering 94% of the U.S. population, totaling more than 60 petabytes of property intelligence. From that imagery, we extract 125+ parcel-level attributes, from roof measurements, pitch, and material classification to structure identification, wall dimensions, and condition scoring.
The imagery is captured by manned aircraft using proprietary orthogonal and oblique technology, not satellites. That resolution makes precise measurements and feature identification possible in ways lower-resolution sources can't touch. Models trained on this data distinguish between dozens of roof material types, detect features like chimneys and vent pipes, and calculate measurements accurate enough to support insurance pricing, underwriting decisions, and capital planning.
For teams that need this data integrated into their own workflows, Eagleview's property data analytics platform and API deliver standardized data directly into underwriting platforms, claims systems, and portfolio management tools. No manual lookups, no inspector wait times, no inconsistency between
Get building-level property data without the guesswork
Public records give you ownership and tax history. Transaction platforms give you comps and sale prices. Neither one tells you whether a roof has five years left or needs replacing next quarter.
Eagleview's property intelligence, built from high-resolution aerial imagery and 125+ AI-extracted attributes, gives lending, insurance, and real estate teams the verified building data they need to make faster, more accurate decisions. No climbing. No manual inspections. No gaps.
Explore Eagleview Property Data and see what building-level intelligence looks like across your portfolio.