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Methodology

How scores work.

A rigorous, two-level scoring system built on 85catalog feeds across 8 signal groups. Every sub-score is traceable to verifiable public data.

How composite scores work

Every composite score is a weighted average of 8 independent signal groups, each scored 0–100. The groups cover commercial health, population trends, demographics, economic strength, development activity, infrastructure, safety, and amenity demand.

Each signal group is itself a weighted average of multiple sub-scores — each derived from a specific, verifiable data source. No single data point can dominate the final score.

Composite = Σ(group_score[i] × weight[i]) / Σ(weight[i])
group_score = Σ(sub_score[j] × sub_weight[j]) / Σ(sub_weight[j])

The 8 signal groups

Each group captures a distinct dimension of location quality. Weights are calibrated per scoring profile to emphasize factors relevant to each CRE use case.

Group
What it measures
Weight
Net business openings, category diversity, rating trajectories, and business license activity — the pulse of commercial activity.
20%
Migration flows, vacancy trends, and residential demand signals that lead economic growth by 6-12 months.
15%
Income levels, population density, daytime population, age distribution, and household composition.
12%
Employment growth, wages, GDP, banking activity, and small business lending.
15%
Building permits, satellite-detected construction, land cover change, and opportunity zones.
12%
Transit access, walkability, traffic flow, broadband coverage, EV infrastructure, and 5G cell tower density.
10%
Crime rates, natural disaster risk, air quality, flood risk, 311 complaints, and environmental quality indicators.
8%
Job market density, events, school quality, food access, unemployment, and Google Trends search intent.
8%
No black-box algorithms. No proprietary foot traffic panels. Every sub-score in Axiom Locus traces to a specific, verifiable source you can inspect.
85 catalog feeds — every number traces back to its origin

Scoring profiles

Five built-in profiles adjust signal group weights for specific CRE use cases. The underlying data and sub-score calculations remain the same — only the group-level emphasis changes.

Profile
Emphasis
General
Balanced weights across all 8 groups. Good starting point for multi-use CRE evaluation.
QSR / Fast-Casual
Emphasizes demographics, amenity demand, and accessibility — the factors that drive foot-traffic restaurant success.
Self-Storage
Heavily weights population momentum and economic strength — the primary demand drivers for storage facilities.
Retail
Prioritizes business vitality and accessibility — key foot-traffic and co-tenancy signals that predict retail performance.
Office
Emphasizes economic strength, demographics, and accessibility for workforce-oriented locations.

Normalization

Each sub-score is normalized to 0–100 using ranges calibrated to US metro distributions. Linear scaling maps proportionally within range; logarithmic scaling is used for metrics with wide distributions (permit values, population density) to prevent outliers from compressing the useful range.

Fixed-range normalization keeps scores comparable across all metros. A 70 in Nashville means the same thing as a 70 in San Francisco.

Range
Interpretation
0–30
Significant weakness — investigate before committing.
30–70
Average to solid. Review specifics for the CRE type.
70–100
Strong signal. Corroborate with site visit.

Confidence

Every score includes a confidence value (0.0–1.0):

confidence = sources_available / sources_possible

A confidence of 1.0 means all expected data sources returned data for this location. Lower confidence indicates some sources were unavailable — typically because the location is outside city-specific data coverage, or in a rural area with sparse government data.

Transparency

Every sub-score in Axiom Locus traces to a specific, verifiable data source. Our 85 catalog feeds include federal government datasets, municipal open data portals, and established commercial providers.

If a score does not match your on-the-ground experience, drill into the sub-scores and signal groups to understand why. No black-box algorithms, no proprietary foot traffic panels.

Browse all 85 catalog feedsExplore signal groups