Data Science

Our Methodology

ListingReels blends listing data, agent-style weighting, and AI guidance to make every CMA explainable and client-ready.

Sold-led
Weighting
Sold comps anchor value; pending and active comps show momentum and competition.
Condition-aware
Adjustments
Beds, baths, square footage, lot size, age, and user/AI condition inputs adjust the comp set.
Distance + recency
Filters
Tight radius and time decay keep comps relevant to the subject property.
AI guidance
Explainability
Pricing scenarios, strategy notes, and appraisal risk are generated alongside the numbers.

What We Measure in Every CMA

Core fields
Property Characteristics
Bedrooms, bathrooms, square footage, lot size, year built
Sold + pending + active
Comp Set
Similarity scoring with distance and recency filters
Trend metrics
Market Indicators
Days on market, sale-to-list ratio, inventory, price change
Strategy notes
AI Guidance
Pricing scenarios, leverage points, and appraisal risk

How It Works

Step 1

Data Collection

We pair listing data with Google Places for address validation and maps.

  • Listing sources for sold, pending, and active listings
  • Google Places + Static/Street View for address confidence
  • User-provided condition notes and optional photos
  • Market trend feeds for price, DOM, and inventory
Step 2

Comparable Selection

We search nearby listings and filter down to the closest matches before weighting.

  • Proximity and time filters tuned for agents
  • Similarity scoring on beds, baths, square footage, lot size, and style
  • Sold comps prioritized, pending and active used for momentum and competition
  • Distance and recency decay to avoid stale or far comps
Step 3

Adjustment Calculation

Adjustments blend price-per-foot with condition inputs and market momentum.

  • Price-per-foot benchmarks with similarity weighting
  • Condition adjustments from user input or AI photo review
  • Lot size, beds/baths, age, and proximity factors
  • Market trend signals (sale-to-list, YoY change) folded into risk
Step 4

Value Reconciliation

We return a transparent valuation plus guidance you can explain to clients.

  • Weighted blend of adjusted comps and price-per-foot
  • Scenario ranges (aggressive, market, conservative)
  • Appraisal risk call-outs with gap estimates
  • Shareable PDF and link exports with the comps you selected

Data Sources

SourceDescriptionType
Listing providerSold, pending, active listings plus trends and rentalsPrimary
Google Places & MapsAddress validation, map tiles, and Street View imagerySupporting
User InputsCondition notes, photo uploads, and verified property detailsAgent-supplied
Derived Market SignalsSale-to-list ratio, days on market, and price momentumDerived

Important Disclaimer

ListingReels generates Comparative Market Analyses (CMAs) for real estate marketing purposes only. CMAs are not appraisals and should not be used for lending, legal, tax, or insurance purposes. Property values are estimates based on available market data and may vary from actual sale prices. For official property valuations required by lenders or for legal purposes, please consult a licensed, certified appraiser.

Accuracy metrics are based on internal testing comparing ListingReels estimates to actual sale prices within 6 months of generation. Past performance does not guarantee future results. Market conditions, property condition, and other factors may affect actual sale prices.

Ready to Experience the Accuracy?

Try ListingReels free and see the difference data-driven valuations can make.