Almost every real estate number that matters — offer price, ARV, expected rent — traces back to comps: recent sales of similar nearby properties. Get your comps right and the rest of the analysis stands on solid ground. Get them wrong and every downstream number is off, usually in the optimistic direction.
What makes a good comp
- Recency: prefer sales within the last three to six months; older sales reflect a different market.
- Proximity: same neighborhood is ideal — ideally within about a mile, and on the same side of any major dividing line like a highway or school boundary.
- Similarity: comparable square footage, bed/bath count, age, lot size, and condition.
- Actual sales, not listings: what a property sold for is evidence; what it's listed for is a hope.
Adjust for the differences
No two properties are identical, so good comping means adjusting. If a comp has an extra bathroom, a finished basement, or a two-car garage the subject lacks, subtract value; if the subject is nicer, add. The goal is to answer a single question: what would this comp have sold for if it were as similar to your property as possible? A few well-adjusted comps beat a dozen raw ones.
Mistakes that inflate your ARV
The most common error is cherry-picking the highest sales and ignoring the rest, which produces an ARV that appraisers and buyers won't support. Others include using comps from a better neighborhood, leaning on stale sales from a hotter market, and treating a fully renovated comp as equivalent to your as-is property. Conservative comping costs you nothing; optimistic comping can cost you the whole deal.
Let the data do the first pass
Pulling and adjusting comps by hand is slow, which is why PropIntel can look them up for you: enter a US address and it returns recent comparable sales, an estimated ARV, market rent, and property facts sourced from county records and MLS data, then pre-fills them into your analysis. Verify the ones that matter, but let the tool do the gathering.