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 = (Zillow × 0.40) + (HUD_50pct × 0.25) + (AptList × 0.20) + (Census × 0.15)

Data Sources

Zillow ZORI

40%Monthly

Zillow's Observed Rent Index tracks actual asking rents for units listed on Zillow. It is a repeat-rent index that controls for changes in the composition of available rentals — making it one of the most reliable signals of current market-rate rent.

Coverage: Metros & ZIP codes

HUD 50th Percentile Rents

25%Annual

HUD 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)

Apartment List

20%Monthly

Apartment List's monthly national rent report tracks asking rents using a hedonic regression model that controls for unit characteristics. Particularly useful for tracking month-over-month market trends.

Coverage: Cities & metros

Census ACS (B25031)

15%Annual (5-year estimates)

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 Zillow data

Zillow 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 Zillow 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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