Single-tenant retail analysis often suffers from a data problem rather than a market problem. While listings are widely available, the underlying information is frequently inconsistent, unstructured, or incomplete—making it difficult to compare assets across markets.
Vetting Attributes That Drive Value
Not all single-tenant assets perform the same, even when pricing and cap rates appear similar. Landchecks places specific emphasis on attributes that materially affect valuation:
- Corner Sites: Correlating visibility, access, and traffic exposure.
- Building Configuration: Distinguishing between freestanding and inline locations.
- Physical Scale: Standardizing building square footage, frontage, and acreage.
Normalizing Tenants for True Comparability
One challenge is inconsistent labeling. LandfinderAI solves this by normalizing tenant names and assigning standardized use subtypes (e.g., Chipotle = QSR, 7-Eleven = C-Store).
Standardized Labels
Aggregated Trends
Once data is structured, we enable multi-level analysis from statewide yield trends down to 1, 3, or 5-mile submarket sub-sets, moving seamlessly from macro context to micro, site-specific insight.