How does BNBCalc choose comparable listings?

Which listings can be a comp

A nearby listing has to pass every one of these checks before it counts toward your estimate:

• It's an entire home, so private rooms, shared rooms and hotel listings are out.
• It was bookable for at least 90 nights over the past 12 months, and for at least 40% of the days BNBCalc tracked it, which keeps part-time listings from dragging the numbers down.
• Its bedroom count matches yours or is one higher or lower. For a studio, that means listings recorded as having zero bedrooms, not ones where the bedroom count is missing.
• Its rates, booked nights and revenue are complete, and it's priced in US dollars.

When the same home is listed on two sites, BNBCalc usually counts it once and keeps the Airbnb copy. If it knows your property's own Airbnb listing, that's left out too, so your home is never compared with itself.

How far BNBCalc looks

BNBCalc prefers close, exact matches and only widens the search when it has to. It works down this list and stops at the first step that has enough homes:

1. Homes with your exact bedroom count within 5 km (about 3 miles), if there are at least 30 of them.
2. Exact matches plus homes with one bedroom more or fewer, still within 5 km, if together they reach 30.
3. Homes with your exact bedroom count within 16 km (about 10 miles), if there are at least 20.
4. Otherwise, exact matches plus one-bedroom-either-side homes within 16 km.

Exact bedroom matches always come first, nearest first, and BNBCalc keeps up to 50 comps. It never scales a smaller or larger home's revenue to fit your bedroom count, so a two-bedroom comp shows what that two-bedroom earned.

When there aren't enough homes nearby

An analysis needs at least 10 comps from that search. In quieter areas where BNBCalc can't find 10, it falls back to a backup comp source that looks within about 10 miles. Those comps show their revenue over the past 12 months, and the estimate is the median of the top-earning half.

The backup source also covers most properties outside the US, where nearby listings are usually priced in a local currency and don't pass the US-dollar check. If no source returns comps at all, the analysis can't be created and you'll see "Something went wrong creating your analysis". When that happens, try a nearby address or a different bedroom count.

What the comp search doesn't look at

The search matches on location, home type and bedrooms. It doesn't weigh amenities, finishes, views or review scores, and it doesn't drop listings for unusually high or low rates, so the set starts out wide. That's why you'll often want to tighten it yourself:

• open Filters to keep only houses or apartments, homes with a pool, hot tub or pets allowed, or listings rated 4.8 or 4.9 stars and up;
• untick any comp that isn't a fair comparison, after checking how far away it is on the map;
• or, for a US property, run AI Underwriter, which reviews each comp's photos, layout and amenities against yours and keeps about five of the closest matches.

How do I filter, include or exclude comps? has the step-by-step version.

Reading the comps table

Each row is one comp, sorted with the highest revenue first, and you can click any column heading to re-sort. These are the columns you'll use most:

Click a listing's name to open it on Airbnb, Vrbo or Booking.com. A big gap between Potential and Actual usually means the host blocks off a lot of nights, so it's worth a closer look before you lean on that comp.