How to Use an AI Home Valuation Tool

Step 1 · Address

Enter your full property address

Start with the exact street address, city, state, and ZIP. The valuation needs a precise location because home values can change block by block, especially in urban areas and neighborhoods with mixed housing types.

Use the autocomplete suggestions if they appear. Selecting a verified address helps the tool geocode the property correctly and pull comparable sales from the right area.

• Use the full street address, not just a ZIP code
• Select a verified address from autocomplete when possible
• Double-check the city and state if you live near a border

Step 2 · Estimate

Review the estimated value and price range

The AI returns a single estimated value plus a low-to-high range. Treat the single number as a midpoint, not a guarantee. The range represents the spread of likely sale prices based on recent comparable sales.

If the range is wide, the property is unusual for the area, the comps are sparse, or the local market is shifting quickly. A narrow range usually means the home is similar to many recent sales.

Step 3 · Comps

Study the comparable sales

Comparable sales are the foundation of the estimate. The tool shows recent closed sales near your property, typically sorted by proximity, size, beds, baths, and date of sale.

For each comp, look at the sale price, price per square foot, days on market, and how similar it is to your home. A 2,000-square-foot ranch with a pool is not a perfect comp for a 2,000-square-foot colonial without one — the price per square foot helps bridge that gap.

Step 4 · Adjust

Adjust for condition, upgrades, and lot

The AI valuation has no way to see inside your home, so it assumes average condition for the age and style of the property. A recently renovated kitchen, new roof, or updated HVAC should push your expected price above the midpoint. Deferred maintenance or an outdated layout should pull it below.

Lot size, views, garage parking, finished basements, and outdoor space also matter. If the comps lack these features and your home has them, the estimate is likely conservative.

• Add value for recent renovations and mechanical updates
• Subtract for needed repairs, dated finishes, or functional issues
• Consider lot size, parking, and outdoor space compared to comps

Step 5 · Market

Compare active and pending listings

Closed sales show what buyers actually paid. Active listings show what sellers are asking right now. Pending listings show the market in transition — the list price that attracted a buyer recently.

If most active listings are priced above your estimate, the market may be rising. If listings are sitting and cutting prices, the market may be cooling. Use this context to decide whether to price at, above, or below the estimate.

Step 6 · Report

Download a CMA report

A Comparative Market Analysis report packages the estimate, range, and selected comps into a document you can share with a broker, attorney, or co-owner. It is useful when you need a printed summary or want to compare the AI output against a professional opinion.

On FlatFeeMLS.ai, the report is generated from the same data you just reviewed and can be downloaded as a PDF after the valuation runs.

Step 7 · Price

Set a strategic list price

Your list price is a marketing decision, not just a math output. Price at the estimate if you want balanced traffic and a typical timeline. Price slightly above if you have standout features and can afford a longer marketing period. Price slightly below if you need a fast sale or want to attract multiple offers.

The first 7–14 days after listing are the most important. A price that feels high relative to the comps will suppress showings and force a later price cut, which signals weakness to buyers.

Step 8 · Confirm

Verify before you list

Before your listing goes live, confirm the price with your listing broker or a local real estate professional. A human can factor in details the AI cannot see — curb appeal, floor plan flow, neighborhood noise, school boundaries, and current buyer demand.

This step is especially important in hot, cooling, or thin markets where automated models lag behind real-time buyer behavior.