Methodology

Built on data, not opinion.

Every score is a national percentile. Every signal has a published definition. Every location carries a confidence tier. When data is sparse, we tell you — we never hide it behind an inflated score.

The formula

The Demand Score

Each location receives a single Demand Score between 0 and 100. A score of 87 means that location is in the top 13% nationally, on the signals you weighted, in the most recent month. Higher means tighter supply and stronger rental demand.

The score is calculated by re-normalised exponential decay across the signals you ranked. Your top-ranked signal carries the most weight; each subsequent rank carries 60% of the rank above it. Signals you toggle off contribute zero. The remaining weights are renormalised to sum to 1.0 — so the score is always comparable across users with different rankings.

weight(rank n) = 0.6^(n - 1)
score = Σ ( normalised_signal × weight ) / Σ weights × 100

Each signal is converted to a 0–100 percentile using all valid US locations in the current month. That means every score is grounded in a national context — not a local one. A 90 in Spokane and a 90 in Austin are directly comparable.

What we measure

The 11 leading signals

The signals were chosen because they lead price, not lag it. They reflect the buying, listing, and renting decisions that move markets — captured at the location level for every US location with sufficient data.

Data quality

Confidence tiers

Each location carries a confidence tier reflecting how much underlying data sits behind its score. Locations with too little signal coverage are excluded entirely — we will not invent a score where one cannot be supported.

By default the app shows Very High and High tiers only. You can expand the filter to include Medium or Low — but we recommend treating those scores with corresponding caution.

Where the data comes from

Our data principles

Raw data is aggregated from a mix of free public sources and paid commercial feeds, then transformed into the leading indicators above. We do not rely on a single source for any signal — every metric is cross-checked or derived from at least two independent inputs where possible.

• Transparency: The full formula above is the entire formula. There are no hidden adjustments, no editorial overrides, no "trust us" layers.
• Coverage honesty: Locations with insufficient data are excluded from results. Their absence is reported in the footer along with the eligible count.
• Comparability: Every signal is normalised against the full US universe of locations in the current month. Local rankings are derivative of national context, not independent of it.
• Reproducibility: Given the same inputs, the same ranking produces the same scores every time. No randomness, no machine-learning black boxes.

Cadence

Updates and history

New scores publish at the start of each month. Pro users see five months of historical scores per location with the same column layout, so the previous and current months are directly comparable cell by cell. We never silently revise historical scores — what was published stays published.

The trajectory sentence shown when you expand a location explains the largest drivers of month-over-month score change. If a signal was missing in the previous month for more than 95% of locations (a common occurrence for newly added signals), the trajectory and delta are suppressed entirely to avoid misleading comparisons.

Important

Abunsh is a data and analytics tool. The Demand Score is a ranking, not a recommendation. Past performance is not indicative of future results. Abunsh does not provide investment, legal, tax, or financial advice. Always do your own due diligence and consult appropriate licensed advisors before making real-estate investment decisions.