If you've evaluated property data providers before, you know the frustration. One vendor has good valuation data but no lien information. Another has MLS listings but no foreclosure details. A third has owner information but charges per field. Stitching together a complete property profile means managing multiple subscriptions, APIs, and data formats.
Datalara takes a different approach: one lookup, one response, 230+ fields across 13 data categories. Every field is available on every lookup. You map the ones you need to your Salesforce fields and ignore the rest. No per-field charges, no tiered access, no data fragmentation.
Here's exactly what's included.
Address (18 Fields)
The foundation of every property record. Datalara normalizes and validates addresses, then provides:
- Full formatted street address with all components (number, direction, name, suffix, unit)
- City, state, ZIP, and ZIP+4 for complete postal addressing
- Carrier route code for direct mail campaigns
- Latitude and longitude with geocoding accuracy score
- Census tract and FIPS code for demographic analysis
Why it matters: Clean, standardized addresses prevent duplicate records and enable geographic analysis in Salesforce reports.
Parcel (31 Fields)
The land itself — legal descriptions, zoning, and lot characteristics:
- Assessor Parcel Number (APN) — the unique county identifier
- Lot size in both acres and square feet, plus frontage and depth measurements
- County name and FIPS code for jurisdiction identification
- Land use category and type — residential, commercial, industrial, agricultural
- Zoning designation — the official zoning code
- Legal description and subdivision name
- HOA information — name, type, and fee amount
- School district codes — elementary, middle, and high school
- Tax rate area for property tax calculations
Why it matters: Investors use parcel data for land use analysis. Lenders use it for collateral evaluation. Everyone uses APN for cross-referencing county records.
Structure (29 Fields)
Everything about the physical building:
- Year built and effective year built (accounts for major renovations)
- Stories, rooms, bedrooms, and bathrooms (including partial baths)
- Building area in square feet
- Parking — type (garage, carport, none) and number of spaces
- Pool type and other amenities
- Architecture style and construction materials
- Exterior walls, roofing type, and foundation
- Heating and AC type
- Basement presence and type
- Quality and condition ratings
- Plumbing count and water/sewer information
Why it matters: Structure data drives property valuation models and helps agents match properties to buyer preferences.
Taxes (4 Fields)
Current tax obligations:
- Tax year and amount owed
- Land value and improvement value (the tax assessor's breakdown)
Assessments (4 Fields)
The county assessor's official valuation:
- Assessment year
- Land value, improvement value, and total assessed value
Market Assessments (4 Fields)
Market-adjusted values from the assessor:
- Market assessment year
- Land value, improvement value, and total market value
Why taxes and assessments matter: These three categories give you three different valuation perspectives — what the owner pays in taxes, what the county says the property is worth, and what the market-adjusted value is. Comparing them reveals assessment appeal opportunities and potential undervaluation.
Valuation (10 Fields)
Automated Valuation Model (AVM) data:
- Estimated value with high and low range estimates
- Forecast standard deviation — confidence level of the estimate
- Valuation date — when the estimate was calculated
- LTV (loan-to-value) — current outstanding debt relative to value
- Equity percent and equity in dollars — the owner's stake
- Purchase LTV — original leverage at time of acquisition
Why it matters: Valuation fields are the most-used data points for mortgage brokers, lenders, and investors. Instant LTV and equity calculations eliminate manual math.
Owner (20 Fields)
Current ownership and portfolio information:
- Primary and secondary owner names
- Mailing address (may differ from property address — absentee owner signal)
- Owner-occupied status — does the owner live there?
- Ownership start date and length of residence in months
- Total properties owned by this owner
- Total mortgages across their portfolio
- Average and total mortgage balances
- Total equity across all properties they own
- Estimated value of all properties in their portfolio
- Census median income for the property's area
Why it matters: Owner portfolio data is gold for investors. A landlord with 12 properties and declining equity across the portfolio is a different prospect than a homeowner with one fully paid-off house. Absentee owner identification is a classic lead generation signal.
Deeds (23 Fields)
The most recent deed transfer:
- Document type — Grant Deed, Warranty Deed, Quitclaim, etc.
- Recording and contract dates
- Sale price and transfer tax
- Distressed sale indicator — was this a short sale, REO, or auction?
- Seller and buyer names
- Buyer mailing address
- Lender name and type — who financed the purchase
- Loan amount, type, and interest rate
- Loan due date and financing type (Conventional, FHA, VA, etc.)
- Deed book and page numbers for county record lookup
Why it matters: Deed data reveals transaction history, financing terms, and whether the property has changed hands under distress. Lender and loan details enable competitive analysis.
MLS — Multiple Listing Service (20 Fields)
Active and historical listing data:
- MLS number and listing status (active, pending, sold, expired)
- Listing subtype and rental indicator
- Initial and original listing dates
- Days on market — how long the property has been listed
- Current list price, minimum list price, and maximum list price
- Sold price and sold date
- Listing agent — name, license number, and agent key
- Brokerage — name, address, phone, and email
Why it matters: MLS data enables market analysis directly in Salesforce. Agents can track competing listings. Investors can identify overpriced or stale listings as negotiation opportunities.
Last Sale (13 Fields)
The most recent completed sale:
- Sale price and price per square foot
- Sale date and recording date
- Document type and number
- Book and page numbers
- Buyer and seller names
- Distressed sale flag and REO status
Why it matters: Last sale data provides the baseline for appreciation analysis. Price per square foot enables quick comparable analysis across properties.
Open Liens (20 Fields)
Current debt obligations on the property:
- Open lien count — how many active liens exist
- First lien recording date
- Interest rates on open liens
- First mortgage details — current balance, original loan amount, estimated payment
- Lien position — first, second, or junior
- Lender name and type
- Financing type and due date
- Loan term in months
- Document number and recording date
Why it matters: Lien data is essential for lenders evaluating refinance or purchase loans. For investors, combined lien balances compared to property value reveal equity and distress opportunities.
Foreclosure (33 Fields)
The most detailed category — complete foreclosure status and auction information:
- Preforeclosure status code and description
- Recording, filing, and default dates
- Case number for legal tracking
- Auction date, time, location, and minimum bid
- Trustee information
- Borrower name
- Unpaid balance and past-due amount
- Original loan amount
- Title company
- Release date and reason (if resolved)
- Transaction ID
Why it matters: Foreclosure data is the most time-sensitive property information. Investors use it to find deals. Lenders use it to monitor risk. Having 33 fields — not just a "yes/no" flag — gives you the complete foreclosure story.
How Field Mapping Works
You don't need all 230+ fields on every record. Datalara's field mapping lets you choose exactly which fields land on your Salesforce object:
- Any Datalara field can map to any Salesforce field (text, number, date, checkbox)
- Any Salesforce object can be the target — Lead, Account, Contact, or custom objects
- You control the mapping — add fields, remove fields, or change mappings at any time
A mortgage broker might map 30 fields focused on valuation, liens, and owner data. An investor might map 50 fields spanning foreclosure, deeds, and owner portfolio. A brokerage might map 20 fields covering MLS and structure data. The data adapts to your workflow.
Explore the complete field list on our Data Fields page, or get started to see this data on your Salesforce records.