CLASSIFICATION SYSTEM

U.S. Market Profiles

A market profile describes a county's housing-market character — its long-term trajectory, supply-demand balance, demographics, and economic footprint. Most U.S. counties cluster into one of eight recurring profiles. About a third don't fit any single profile cleanly — those are surfaced separately.

A profile is descriptive context; the BoomTown Score is a 5-year price-growth forecast. They usually agree — when they diverge sharply for a given county, that county is moved to Idiosyncratic Markets rather than carry a profile label that doesn't fit.

[01] The Eight Profiles

Heartland Steady Growth
Heartland Steady Growth
Established Midwest and Great Lakes markets with strong, steady housing growth.
145 COUNTIES MEAN BTI 83
Educated Suburban Growth
Educated Suburban Growth
Highly-educated large-metro suburbs with fast-moving markets and low inventory.
110 COUNTIES MEAN BTI 44
Western Premium Correction
Western Premium Correction
California, Pacific Northwest, and Mountain West premium markets correcting from prior highs.
78 COUNTIES MEAN BTI 25
Sun Belt Post-Surge Correction
Sun Belt Post-Surge Correction
Sun Belt metros that surged sharply and are now seeing the steepest 1-year declines.
76 COUNTIES MEAN BTI 14
Affordable Slow Markets
Affordable Slow Markets
Older accessibly-priced markets with high inventory and slow but steady prices.
75 COUNTIES MEAN BTI 68
Sun Belt Exurban Boom
Sun Belt Exurban Boom
Sun Belt exurbs with the nation's highest population growth and construction.
43 COUNTIES MEAN BTI 24
Secondary Market Surge
Secondary Market Surge
Small metros that surged on remote-work demand and are now moderating.
35 COUNTIES MEAN BTI 56
Persistent Housing Weakness
Persistent Housing Weakness
Counties with chronic housing underperformance the model also expects to underperform forward.
11 COUNTIES MEAN BTI 55

[02] Counties That Don't Fit a Profile

Idiosyncratic Markets
Idiosyncratic Markets
Counties whose data resists a single-profile label.
414 COUNTIES →

[03] How These Were Derived

Profiles are derived empirically from 24 features per county — housing trajectory (Zillow ZHVI 1yr / 3yr / 5yr changes, peak-to-current drawdown, pandemic surge, post-peak decline), rent dynamics (ZORI), supply (months of supply, days on market, building permits), affordability (income-to-home ratio), labor (BLS QCEW employment + wage growth, industry HHI), and demographics (population growth, migration inflow, education, amenity score). BoomTown Score is deliberately excluded from the clustering — profiles describe character, score forecasts future price.

We use hierarchical agglomerative clustering with Ward linkage. The number of profiles (k=8) was chosen via silhouette score and dendrogram-gap analysis. Each county's assignment was validated with 100 bootstrap resamples — counties whose profile assignment was stable in ≥70% of resamples get a "clean" classification; counties stable in 50-69% are "leans toward"; counties below 50% — or whose BoomTown Score deviates more than 30 points from the profile mean — are reported as idiosyncratic.

Full methodology →