Market Analysis

Real Estate Comps: How to Pull the Right Comparables for Any Property

Pulling comps wrong leads to overpriced listings that sit, or underpriced offers that cost buyers money. The agents who price with precision win more listings and close more deals.

June 28, 2026·9 min read
90 days
ideal comp window in a stable market
10–15%
maximum allowable size variance in a comp
1 mile
ideal comp radius in suburban markets
$25/sq ft
typical adjustment for finished basement space

The Foundation: What Makes a Valid Comp

A comparable sale must be similar in property type (single-family to single-family, not condo to SFR), location (same neighborhood, similar street character), size (within 10–15% of subject gross living area), age (within 10–20 years unless heavily updated), and condition. Sale date matters: in a rapidly appreciating or declining market, a 6-month-old sale may require a time adjustment of 0.5–1% per month to reflect current conditions. Distressed sales — foreclosures and short sales — should generally be excluded unless the subject property is also distressed, because they pull value downward in ways that don't reflect open-market behavior. One metric most agents overlook is the list-to-sale ratio of the comps. A ratio of 101% signals bidding wars and buyer competition; a ratio of 96% tells you negotiation room exists and that aggressive pricing will create resistance. Always pull this figure alongside the sale price — it provides critical context about the micro-market the comp was sold in, and it tells your seller what to realistically expect when their home lists at your recommended price.

Where to Pull Comps (and What Each Source Misses)

The MLS is the gold standard for comp data. It provides the most complete sold records, including days on market, list-to-sale ratios, original list price history, and agent remarks about condition — details that raw transaction data can never capture. Public records through the county assessor fill in private sales and non-MLS-listed transactions, but they often lag 30–60 days behind actual closings and strip out condition context entirely. Zillow and Redfin are useful for quick reference and can surface properties you missed, but their AVM (Automated Valuation Model) outputs frequently miss property-specific adjustments — never present a Zestimate as a CMA in a listing appointment. CoreLogic, RPR (REALTORS Property Resource), and Black Knight provide deeper analytics for agents with access, including distressed sale flags and neighborhood trend overlays. For luxury properties or unique homes where valid comps are scarce, go one step further: call the listing agent on each comp directly. Verbal insight about buyer competition, inspection issues, and the seller's motivation is often more valuable than any data field in the MLS, and it gives you intelligence that your competitors don't have.

Making Adjustments: The Grid Method

The adjustment grid is the analytical backbone of any professional CMA. List each comparable sale in a column, with the subject property in a reference column on the left. For every characteristic that differs between a comp and the subject, apply a dollar adjustment to the comp — adding value when the comp is inferior, subtracting when it is superior. If the subject has a pool and comp #1 does not, add pool value to comp #1 ($10,000–$40,000 depending on market and pool type). If comp #2 has a 3-car garage versus the subject's 2-car, subtract $8,000–$15,000 from comp #2. Common adjustment categories and typical ranges: gross living area ($75–$150/sq ft above grade depending on market); bedroom count ($3,000–$8,000 per bedroom difference); bathroom count ($5,000–$15,000 per full bath); garage bays ($5,000–$12,000 per bay); lot size (negligible in dense urban markets, significant in rural or view-lot markets); view and location premiums ($0–$50,000 based on quality and market demand); condition and updates, particularly kitchen and bath remodels ($5,000–$30,000 per material renovation). Any comp where net adjustments exceed 15% of the sale price is too dissimilar to anchor your value opinion — discard it and find one that requires less correction. The integrity of the grid depends on using comps that are genuinely comparable before adjustment, not on adjusting your way out of a poor selection.

Presenting Comps to Sellers Who Disagree

The most common CMA conflict: sellers who believe their home is worth more than the data supports because of emotional attachment or a neighbor's bragging price. The single biggest mistake agents make is arguing with the seller about the data. Instead, present three pricing scenarios and let the market data speak. Scenario one — the aggressive price — shows what happens when a home lists above market: statistically, homes that sit more than 21 days without an accepted offer receive final sale prices 2–4% below what a correctly priced home would have closed at. Show them DOM data from the last six months for listings at that price tier that required price reductions. Scenario two — the market price — is based on your adjusted comps, and represents the highest probability of attracting multiple offers within 14 days. Scenario three — the below-market price — can generate a bidding war in competitive markets but risks leaving money on the table if buyer demand is softer than expected. For each scenario, show actual comparable listings from the past 90 days that followed that pricing path and document their outcome. Then use a phrase that repositions you as an advisor: "The market will set the price — this data just predicts what it will say." That framing removes you from the adversarial role and aligns you with the seller against an external force: the market itself.

How AI and Automation Fit Into the CMA Process

The CMA is the front door to most listing appointments. The agent who delivers a fast, data-rich CMA gets the meeting; the agent who delivers it with a polished presentation wins the listing. But before any of that happens, the lead has to be captured and contacted quickly. LeadLocker AI can trigger an automated CMA request sequence the moment a homeowner submits a "What's my home worth?" inquiry — capturing the lead in the system, sending an immediate acknowledgment that sets expectations, and scheduling a follow-up call for the agent at the optimal time. Research consistently shows that agents who respond to inbound CMA requests within 5 minutes convert at 3–5x the rate of those who call the next day. That speed advantage compounds: first contact establishes rapport before any competitor reaches them. LeadLocker AI handles the lead capture and initial sequence so the agent can focus their energy where it matters — pulling accurate comps, building a compelling presentation, and walking into the appointment prepared to win the business.

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Key Takeaways

  • Valid comps must match on property type, location, size (within 10–15%), age, and condition — distressed sales should generally be excluded
  • Use MLS as the primary data source; public records and RPR fill gaps but miss condition context that MLS agent remarks provide
  • Apply the grid adjustment method for every difference between subject and comp — net adjustments over 15% disqualify the comp
  • List-to-sale ratio reveals market temperature: above 100% indicates competition, below 97% indicates negotiating room
  • Present sellers with three price scenarios with supporting DOM data to make the case for accurate pricing over emotional pricing
  • Automate "What's my home worth?" lead capture to ensure CMA requests get a response in under 5 minutes

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