Use Google Sheets AI to Build a Comparable Sales Analysis Template

What This Does

Google Sheets' built-in AI helps you build a reusable comparable sales analysis template — automatically calculating price-per-sqft ratios, flagging outliers, and comparing comps to your subject property, so you spend less time doing mental math and more time on actual analysis.

Before You Start

• You have a Google account (free)
• You have Google Sheets open in your browser
• You have comp data from your MLS search ready (address, GLA, sale price, beds/baths, sale date, distance)

Steps

1. Create a new Google Sheet and set up your column headers

Open a new Google Sheet. In Row 1, create these column headers:

• A: Property
• B: Address
• C: Sale Price
• D: GLA (Sq Ft)
• E: Beds
• F: Baths
• G: Sale Date
• H: Distance from Subject
• I: Price/SqFt
• J: Days Since Sale
• K: Notes

Enter "SUBJECT" in A2 and fill in your subject property data in columns C–H.

2. Enter your comparable sales data

Starting in row 3, enter data for each comp (1 per row). Enter: address, sale price, GLA, beds, baths, sale date, approximate distance.

3. Use Smart Fill for Price/SqFt

Click cell I2 (Price/SqFt for the subject). Type =C2/D2 and press Enter. Then click I2 again — Google Sheets will recognize the pattern and offer to fill down the entire column automatically. Click the checkmark to accept.

What you should see: All rows now have a Price/SqFt value calculated automatically. The column auto-fills as you add new comps.

4. Use AI formula suggestions for Days Since Sale

Click cell J3. Start typing = then describe what you want: type =TODAY()- then click G3 (sale date). Google Sheets will suggest the correct formula. The result shows how many days ago each comp sold.

Troubleshooting: If you see a number like 45000 instead of "days," right-click the cell → Format cells → Number to convert from date format to plain number.

5. Highlight outliers with conditional formatting

Select column I (Price/SqFt). Go to Format → Conditional Formatting. Set rule: "Greater than" the subject's price-per-sqft by 15% — highlight in yellow. Set a second rule: "Less than" 15% below — highlight in orange. Now outliers jump out visually.

6. Save as your template

Go to File → Make a copy and name it "Comp Analysis Template." Each new appraisal, make a copy and paste in your new comp data.

Real Example

Scenario: You have 4 comps for a 1,650 sqft ranch that sold at various prices. You want to quickly see which comps bracket your subject's likely price-per-sqft range.

What you enter:

• Subject: 1,650 sqft, list price unknown (you're determining value)
• Comp 1: $385,000 / 1,600 sqft = $240.63/sqft
• Comp 2: $372,000 / 1,580 sqft = $235.44/sqft
• Comp 3: $398,000 / 1,720 sqft = $231.40/sqft
• Comp 4: $415,000 / 1,650 sqft = $251.52/sqft

What you get: Instant visual display showing Comp 4 is 8% above the cluster — worth a note in your comp selection rationale.

Tips

• Add a "Gross Adjustment %" column using =ABS((adjusted price - sale price)/sale price*100) — FNMA guidelines prefer comps with gross adjustments under 25%.
• Use Insert → Dropdown in the Notes column to create quick tags: "Best Comp," "Support Only," "Location Issue" — makes the report-writing phase faster.
• Share the sheet with your trainee if you have one; they can populate comp data while you're doing the inspection.

Tool interfaces change — if a button has moved, look for similar AI/magic/smart options in the same menu area.