How it works

Methodology & Data Sources

LookupRent triangulates estimates from multiple independent public data sources, weighting each by reliability and timeliness — so investors get a defensible rent figure at the start of underwriting.

Triangulation Formula

For each ZIP code and bedroom count, LookupRent fetches data from multiple sources. A weighted average produces the p50 estimate; the p25–p75 range derives from source spread and HUD FMR bounds — giving investors a realistic rent range for underwriting.

# Weighted median estimate
p50 = (MarketIndex × 0.40) + (HUD_50pct × 0.25) + (MarketSurvey × 0.20) + (Census × 0.15)

Data Sources

Market Rent Index (Primary)

40%Monthly

A repeat-rent index that tracks actual asking rents, controlling for changes in the composition of available rentals — one of the most reliable signals of current market-rate rent. Updated monthly across major metros and ZIP codes.

Coverage: Metros & ZIP codes

HUD 50th Percentile Rents

25%Annual

The U.S. Department of Housing and Urban Development publishes 50th percentile rents by Fair Market Rent area annually, based on the American Housing Survey and ACS data. These represent the median rent paid by recently-moved-in renters in standard-condition units.

Coverage: All FMR areas (~2,600)

Market Rent Survey (Secondary)

20%Monthly

A hedonic regression model tracking asking rents that controls for unit characteristics. Particularly useful for capturing month-over-month market trends across cities and metros.

Coverage: Cities & metros

Census ACS (B25031)

15%Annual (5-year estimates)

U.S. Census Bureau American Community Survey table B25031 provides median gross rent by number of bedrooms at the census tract level — the most granular government-published rent data available. Used for geographic calibration and rural coverage.

Coverage: All census tracts

Geographic Fallback Chain

When a source lacks ZIP-level data, LookupRent falls back through a geographic hierarchy. Each fallback step applies a −15 confidence penalty, so the confidence score tells you exactly how precise the underlying data is.

ZIP Code

City

County

CBSA / Metro

State

Confidence Score

Every estimate starts at 100 and loses points for factors that reduce reliability. A score of 80+ means all four sources had direct ZIP-level data in close agreement.

−20

No primary market index data

The primary market index is the highest-quality real-time signal; its absence significantly reduces estimate quality.

−15 each

Geographic fallback (each level)

ZIP → city → county → CBSA → state fallback reduces precision with each step.

−10

Bedroom size adjustment applied

Estimate was derived from 2BR data and scaled by ratio, not directly observed.

−10

Stale market data (>6 months)

Older data may not reflect current market conditions.

−5 each

Missing source

Each absent data source reduces triangulation confidence.

Confidence scores are clamped between 5 (floor) and 100 (ceiling).

Bedroom Size Ratios

When a source only provides 2-bedroom data, other bedroom counts are estimated using HUD-derived ratios relative to the 2BR baseline:

Bedrooms	Ratio	Example (2BR = $2,000)
Studio (0BR)	0.72×	$1,440
1 Bedroom	0.83×	$1,660
2 Bedrooms	1.00×	$2,000
3 Bedrooms	1.20×	$2,400
4 Bedrooms	1.38×	$2,760

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