Stop chasing
random properties.
We turn large-scale property records into a focused pipeline of high-priority real estate prospects — so investors can spend less time sorting data and more time talking to owners.
Raw public records in.
Prioritized opportunities out.
The workflow is designed to reduce a massive property universe into smaller, more actionable groups using property characteristics and scoring signals.
Acquire
Start with county-level assessor and parcel records containing property identifiers, address, use, year built and valuation fields.
Clean
Remove non-residential and irrelevant property uses so the working dataset focuses on residential opportunities.
Filter
Apply property-age, value and other screening signals to shrink the universe into increasingly focused stages.
Prioritize
Rank the remaining properties with a lead score so the highest-priority records can be reviewed first.
Lead Screening Engine
Not every house deserves a phone call.
A large property list is only useful when it can be narrowed down. Our screening approach is built around finding records that fit an investor's buying criteria before the outreach team ever touches the list.
The fields that make a property record useful.
Our current county dataset contains core parcel and property characteristics that can be used for screening, segmentation and enrichment workflows.
Property Identity
APN, situs address and ZIP information create the base record for property-level organization.
Property Profile
Use description, year built, bedrooms, bathrooms and main living area help describe the asset.
Assessed Values
Land value and improvement value provide additional signals for property screening and analysis.
Market Segments
ZIP-level grouping makes it possible to build localized acquisition lists instead of one giant spreadsheet.
Lead Score
Records can be ranked into priority bands so outreach starts with the strongest available signals.
Enrichment Ready
Owner mailing information and other contact fields can be added in a separate enrichment step where legally and commercially appropriate.
Give your acquisition team a starting point.
Instead of treating 247,234 filtered properties equally, the workflow assigns priority bands. The existing dataset contains scores from 35 through 90, allowing the highest-scoring records to be reviewed first.
Get a Targeted List →Build a list your acquisitions team can actually work.
Tell us your target market, property profile and acquisition criteria. We'll structure the property screening around the signals that matter to your strategy.
Dataset figures shown are from the current California property-data workflow and describe records processed/filtered; they are not a guarantee that every property is a motivated seller.