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Rensselaer, New York short-term rental listings & supply

Updated By The AirDNA Data Team

Rensselaer, New York has 15 active short-term rental listings, tracked across Airbnb, Vrbo, and Booking.com.

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Total active listings
15
-25.0% YoY
Most popular size
1BR
46.7% of all active listings
AirDNA tracks daily performance across 10M+ Airbnb, Vrbo, and Booking.com listings in 120K+ global markets. How we collect this data →10M+ listings across Airbnb, Vrbo & Booking.com in 120K+ markets. How we collect →

Rensselaer, New York short-term rental listings

Rensselaer has 15 active short-term rental listings as of July 2026, tracked across Airbnb, Vrbo, and Booking.com. Active supply is down 25.0% from July 2025 to July 2026. Here's how the market breaks down:

  • By property type: 73.3% entire homes, 26.7% private rooms.
  • By size: 46.7% 1-bedroom, 40% 2-bedroom, 6.7% 3-bedroom, and 6.7% 5+ bedroom.
  • By channel: 73.3% Airbnb-only, 26.7% cross-listed.
  • By availability: 60% full-time (271–365), 26.7% part-time (91–180 nights), 6.7% seasonal (1–90 nights), and 6.7% most of year (181–270).
  • By minimum stay: 33.3% 7–29 nights, 33.3% 30+ nights, 20% 2 nights, and 13.3% 3 nights.
  • By cancellation policy: 45.5% flexible, 45.5% moderate and 9.1% strict.
69
Rental demand score
Full Rensselaer market overview How Market Score is calculated
Analyst's take

Rensselaer's Rental Demand score: 69 out of 100.

Rensselaer's Rental Demand subscore is 69 out of 100, one of five inputs to its overall Market Score of 0.

Rental Demand combines two inputs: annual occupancy (65% in Rensselaer) and year-over-year listing growth (active supply down 25.0% from July 2025 to July 2026).

It is benchmarked against other short-term rental markets in the same country with at least 15 active listings.

The Market Score is a starting point, not an investment decision.

Market-level averages hide wide variation. Here's how to go deeper in the app:

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Key definitions

How AirDNA defines these metrics

Active listings
Active listings are the short-term rentals on Airbnb, Vrbo, and Booking.com that were available or booked in the trailing 12 months. AirDNA de-duplicates the same home across channels, and the count refreshes monthly.How AirDNA counts active listings →
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Active listings over timeIllustrative preview

How Rensselaer's active short-term rental supply has trended over the past year.

Oct '25Dec '25Feb '26Apr '26Jun '26Aug '26
See Rensselaer's month-by-month supply trend in the AirDNA app.

Listing mix

Four ways to slice Rensselaer's 15 listings

Property type

Entire home leads at 73.3%

  • Entire home73.3%
  • Private room26.7%

Bedrooms

1BR leads at 46.7%

  • 1BR46.7%
  • 2BR40%
  • 3BR6.7%
  • 5BR+6.7%

Channel

Airbnb only leads at 73.3%

  • Airbnb only73.3%
  • Multi-platform26.7%

Availability

Full-time (271–365) leads at 60%

  • Seasonal (1–90 nights)6.7%
  • Part-time (91–180 nights)26.7%
  • Most of year (181–270)6.7%
  • Full-time (271–365)60%

Listings by minimum stay

Share of Rensselaer active supply by host-set minimum stay

2 nights
20%
3 nights
13.3%
7–29 nights
33.3%
30+ nights
33.3%

Listings by cancellation policy

Share of Rensselaer active supply by host cancellation policy

Flexible
45.5%
Moderate
45.5%
Strict
9.1%

This is the tip of the iceberg

Go deeper on Rensselaer supply in the app.

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Explore more Rensselaer data

Keep digging into Rensselaer

Rensselaer market overview

The full Rensselaer market: 15 listings, $16.5K average revenue, 65% occupancy, $142 ADR. Topline metrics and the AirDNA Market Score.

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Revenue

Annual earnings, revenue by property type, and daily rates by segment.

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Seasonality

Occupancy, RevPAR, peak and trough months, seasonality score.

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Property Managers

The largest property managers operating in Rensselaer.

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Explore more markets

Other short-term rental markets in New York

Frequently asked

Common questions about Rensselaer

Get more in the app

There's a lot more inside the AirDNA app.

  • Custom comp sets
  • Neighborhood data
  • Deep filters
  • Heat maps
  • For Sale by yield
  • Export the data
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