Most hosts price based on their own calendar. We price based on what every comparable listing in your neighborhood is doing—in real time.
You can’t optimize what you can’t see.
When you’re managing pricing on your own, you’re working with maybe 5–10 data points: your booking pace, last year’s performance, a few comps you check manually. You adjust rates when you remember to check the calendar. You might browse a couple nearby listings to see what they’re charging.
Meanwhile, there are 47 other short-term rentals within a half-mile of your property. Three of them just dropped their rates for next weekend. Two went offline for renovations. One raised prices after landing a corporate contract. Another hasn’t updated their calendar in six weeks and is losing bookings to overpricing.
That’s not hypothetical—that’s what we see every day in markets like Denver and Portland, where supply density is high and occupancy swings month to month.
The gap between reactive and predictive pricing
Most dynamic pricing tools adjust based on your booking velocity. That’s reactive. If you’re not getting bookings, they drop your price. That works, but it’s slow—you’ve already lost days you can’t get back.
Competitor-based pricing is predictive. If we see five comparable properties in Nashville’s Germantown neighborhood drop their weekend rates from $310 to $265, we know demand is soft before your calendar goes dark. We adjust proactively, capture bookings early, and avoid the last-minute discount spiral.
The inverse matters just as much. When a competitor with similar specs to your Seattle Capitol Hill unit books solid for a festival weekend at $425/night, and you’re still listed at $340, we know there’s ceiling room. We test higher. We capture the upside.
What we’re actually tracking
Our data layer monitors:
- Pricing changes across comparable properties (updated daily)
- Availability gaps — when competitors block calendars or go offline, creating demand overflow
- Booking velocity — how fast similar listings are filling relative to lead time
- Permit status — we track enforcement activity and know when supply contracts in regulated markets like LA and San Diego
In one Chicago Lincoln Park case, we identified that 11 nearby units went offline during a permit crackdown. We raised rates 18% over the next 45 days and still hit 89% occupancy. The hosts who weren’t monitoring competitor supply left money on the table.
Why manual comp checks don’t scale
You could do this yourself. Log into Airbnb every morning, check 15–20 comparable listings, note price changes, cross-reference availability, adjust your calendar accordingly.
That’s about 40 minutes a day. Over a month, it’s 20 hours—and you still won’t catch intraday changes or have a historical dataset to identify patterns.
We built the pipeline because no host should have to become a data analyst to run a profitable property.
Want to see what competitors near your property are actually doing?
We’ll pull a free comp report for your address—no pitch, just the numbers.
