Use Cases

Enriched real estate data for investors, developers, researchers, and analysts. See how different teams use Vitki Data property datasets and APIs.

Market analysis and deal sourcing

Real Estate Investors

Screen properties across entire metros with enrichment data that goes far beyond listing details. Filter by census tract income, crime rates, flood risk, and price trends to find undervalued markets before they show up on mainstream radar.

Key data fields used

  • Median household income and home values by census tract
  • House price index trends (FHFA HPI) for market timing
  • Fair market rents (HUD FMR) for rental yield estimates
  • Crime rates for neighborhood risk assessment
  • Flood zone and disaster history for insurance cost modeling
Build data-driven real estate applications

Proptech Developers

Skip months of data pipeline work. Get structured, enriched property data delivered as JSON with consistent schemas, confidence scoring, and granularity metadata. Feed it directly into your application, model, or dashboard.

Key data fields used

  • Structured JSON with consistent field names and types
  • Per-field confidence scoring and value provenance
  • Granularity metadata for every enrichment field
  • USPS Pub 28 normalized addresses for reliable joins
  • Placekey POI identifiers for cross-dataset matching
Comprehensive housing market intelligence

Market Researchers & Analysts

Combine property-level listing data with tract-level demographics, county-level employment, and metro-level housing trends in a single dataset. No more juggling Census downloads, BLS spreadsheets, and MLS feeds separately.

Key data fields used

  • Census ACS demographics and income by tract
  • BLS employment and wage data by county and metro
  • IRS SOI migration flows and ZIP-level income
  • Mortgage approval rates and loan amounts (CFPB HMDA)
  • Walk Score, transit, and bike scores by property
Neighborhood context for comparable analysis

Appraisers & Valuators

Supplement comparable sales analysis with quantitative neighborhood context. Understand why properties in the same ZIP code sell at different prices by looking at tract-level demographics, walkability, flood risk, and local employment data.

Key data fields used

  • Walk Score, transit, and bike scores per property
  • Flood zone designation and disaster history
  • Census tract vacancy rates and owner/renter mix
  • EPA brownfield proximity flags
  • Price history and days on market from listings
Risk assessment and loan portfolio analysis

Lenders & Underwriters

Enrich loan applications and portfolio holdings with property-level and neighborhood-level risk indicators. Flood zone classification, disaster history, crime rates, and economic health metrics help quantify location-based risk.

Key data fields used

  • FEMA flood zone and flood disaster history
  • Crime rates (violent and property) by county
  • County employment totals and average wages
  • Mortgage approval rates and mean loan amounts
  • 30-year fixed mortgage rate benchmarks
Ready-made datasets for modeling and research

Data Scientists & Academics

Get clean, deduplicated, geocoded property datasets with 48 enrichment fields already joined. Spend time on analysis instead of data collection, cleaning, and geocoding. Bulk exports available as JSON with full field documentation.

Key data fields used

  • Geocoded coordinates with census tract and FIPS codes
  • 4-layer deduplication for clean training data
  • Completeness scores and confidence metadata
  • All 48 enrichment fields from 13 government APIs
  • Canonical address keys for entity resolution

Don't see your use case?

Vitki Data works for any workflow that needs property listings combined with location intelligence. Bulk real estate data, delivered as structured JSON, ready to use.