Single-family rental data
Single-family rentals move differently than multifamily, priced unit by unit, managed by a fragmented mix of operators, and historically the hardest asset class to get clean data on. Get first-party data, sourced directly from the property management systems where those rents are actually set.
First party • All SFR property types • Unit-level
SFR data has always been the hardest to get right
Single-family rentals don’t run through one system the way multifamily buildings often do. A national portfolio, a regional operator, and an individual landlord renting out one house each set and manage rent differently. That fragmentation is exactly what other sources struggle to capture consistently, since there’s no single place to pull a complete picture.
Not all sources are reliable
Most data buyers default to whatever source is already familiar, without checking whether it was ever built for single-family rentals in the first place.
The rental housing industry has a problem
Most listing platforms make money when a lead is generated, not when a listing is accurate. That incentive rewards keeping a unit listed long after it’s filled, since a stale listing can still generate a lead. Nobody on the platform’s side is incentivized to go back and clean it up.
MLS data is a problem too
MLS data is built for home sales, not rentals, and barely covers the SFR market at all — less than 5%. Rents in MLS are a self-reported number, with initial asking rent entered by real estate agents. An accurate final asking rent is entirely up to the agent’s diligence in making that update.
Scraping just inherits the same problem
Scraped listings inherit duplication and staleness from the sites they’re pulled from, along with the compliance risk that comes from pulling data without authorization from the source.
Surveys were never fast enough to fix it
Surveyed data is self-reported and collected too infrequently to catch what’s happening in real time.
The Census’s sample size compounds the problem
The ACS surveys roughly 3.5 million households a year, about 2–3% of US households, selected at random and self-reported, then extrapolated to estimate the rest. It’s published only in annual releases, with smaller geographies limited to 5-year estimates, and it misses the individual home entirely, working at the unit-type level instead.
The only reliable source is PMS
First-party data, captured directly from the systems where a rent is actually set and updated, is the only sourcing model built to reflect what’s happening at an individual home. Dwellsy IQ is sourced directly from the property management systems used to run single-family rental portfolios, capturing final asking rent at the individual home.
Built for how houses get rented
No monetization tied to lead volume
Dwellsy IQ’s data comes from Dwellsy, our free rental marketplace. Renters don’t pay to inquire and property managers don’t pay to list, so there’s no lead-based monetization creating an incentive to keep a stale or fake listing up.
Actually built for rentals
Real single-family rental coverage, not a figure repurposed from a sales-focused source. Full range of bedrooms, captured at the individual unit level, across every SFR property type.
No duplication, no compliance risk
Every unit carries a Unique Rental Unit Identifier (URU) that never changes, so the same home never gets counted twice across owners, listings, or re-rentals.
Continuously updated
Data updates the moment it comes in from the source, not on a monthly or quarterly survey cycle. A number reflects what’s happening in the market right now.
Individual units, not just unit-type averages
Attribute-level detail, 50+ attributes and 250+ amenities, captured at the individual unit rather than rolled into a unit-type average the way survey-based sources report it. That same detail can still be aggregated up to whatever average or benchmark a use case calls for.
Every geography, not just the easy markets
SFR data rolls up cleanly to ZIP code, city, MSA, state, and national views, all from the same underlying source, including the smaller counties and low-population geographies the ACS publishes least often and least reliably.
Flexible delivery
Available via API, AWS S3, SFTP, Azure, or Google Cloud Drive, and MCP IQ for agent-based workflows, delivered in CSV, TSV, JSON, or Parquet.
How teams use Dwellsy IQ’s SFR data
Our single-family rental data supports different workflows depending on who’s using it. See how teams across each industry put Dwellsy IQ’s SFR data to work.
Explore by industryObvious or not, we’ve got it covered
Some use cases have an obvious answer, like validating a rent roll or pricing a renewal. Others don’t, and the breadth and depth of Dwellsy IQ’s data covers both. Check out the Use Cases page to see where it fits.
Explore use casesGet single-family rental data scoped to your market
Tell us the geography and use case, and we’ll scope SFR data that fits your needs.
FAQ
What counts as single-family rental data in this dataset?
Every SFR property type, standalone homes, townhomes, condos, and more, of all bedroom counts, captured at the individual unit level.
How current is this data?
Our data is updated continuously at the source. Actual refresh frequency for your specific use case depends on delivery method.
How far back does historical SFR data go?
January 2020 to present, covering the COVID-era rent shock and post-pandemic normalization period.
What geographic coverage is available?
16,000+ ZIP codes and 800+ MSAs nationwide, rolling up from unit-level data to ZIP, city, MSA, state, and national views.
Can we get SFR and multifamily data together, or does it need to be purchased separately?
Both. SFR and multifamily data live in the same underlying dataset and can be purchased together or scoped to a single asset class depending on your use case.
What attributes are included per listing?
Each listing includes 50+ standardized attributes and 250+ amenities, covering unit characteristics, photos, and property features, in addition to final asking rent.
How is this data delivered?
Available via API, AWS S3 bulk delivery, SFTP, Azure, Google Cloud Drive, or MCP IQ for agent-based workflows, in CSV, TSV, JSON, or Parquet.
Is any of this data private or personally identifiable?
No. The dataset is public, owner-disclosed listing data at the unit level. There is no PII and no private data involved.
What’s the best SFR data provider?
Dwellsy IQ. With 17M+ listings sourced first-party and final asking rent captured directly from property management systems it’s the most reliable rental data in the market.
Equal Housing Opportunity