Affordability research built on rent data that holds up in policy reports
Get historical, jurisdiction-specific asking rents sourced directly from property management systems for housing research and policy you can trust.
No scraped listings • No self-reported surveys • Jurisdiction-bounded by state, MSA or ZIP
Trusted by Leading Brands
A grant report can’t cite a number it can’t defend.
The numbers a study actually depends on
Rent burden studies require actual final asking rents at the unit level, not community averages padded by survey lag. Researchers need a defensible baseline for measuring cost burden against area income.
Most public rent data doesn’t hold up
Scraped listings carry duplication and legal ambiguity. Self-reported surveys are infrequent and already stale by the time they’re published. Neither gives a policy team a number that survives peer review or public scrutiny.
A dataset scoped to your jurisdiction
Dwellsy IQ data rolls up cleanly to ZIP code, city, MSA, and state boundaries from the same unit-level source, pulled straight from the PMS and reliable to cite plainly in a methodology section.
What makes Dwellsy IQ’s housing data different
Rent data that can be defended in a public report
Dwellsy IQ’s data originates in Dwellsy’s rental marketplace, which connects directly with 30+ property management systems—the software where rents and availability are managed.
The only accurate alternative for rental data
Unlike lead-driven rental marketplaces, our marketplace does not get paid for generating leads. Because the marketplace is free for renters and property managers, there is no incentive to preserve stale, duplicated, or misleading inventory.
One source, bounded to the jurisdiction being studied
Dwellsy IQ can support studies at the ZIP-code, city, MSA, state or national level without combining unrelated jurisdictions or relying on broad regional averages.
Historical coverage for measuring how affordability changed
Track rent trajectories from January 2020 through the pandemic-era shock, rapid rent growth and subsequent market normalization.
Unit-level evidence behind affordability calculations
Analyze final asking rents alongside 50+ other attributes, including bedrooms, square footage and photos, and 250+ amenities.
One-time, project-scoped delivery
Data can be purchased as a one-time historical snapshot or delivered on an ongoing basis, scoped to the study’s time range and geography.
How policy and affordability teams use Dwellsy IQ
State & Federal Agencies
Rent burden calculations
Ground cost-to-income ratio studies in actual final asking rents at the unit level, not community averages padded by survey lag.
Grant reporting
Cite a documented, direct-sourced dataset in grant reports and public filings without qualifying where the numbers came from.
Jurisdiction-bounded studies
Scope data to exactly the state, county, or MSA a report covers, nothing broader, nothing that has to be filtered down after the fact.
County & Regional Planning Commissions
Affordability threshold studies
Measure local affordability against real, current rents instead of a lagging federal survey average.
Historical trend analysis
Study how rent burden has shifted in a specific jurisdiction since January 2020, covering the COVID-era shock and the recovery that followed.
Budget-friendly, project-scoped access
Purchase a one-time dataset scoped to a single study or grant cycle, rather than committing to an ongoing subscription.
Academic Researchers
Peer-review-ready sourcing
Cite a data source with documented, direct-to-PMS provenance in a methodology section, not an anonymous scrape or a self-reported estimate.
Longitudinal housing studies
Use historical, unit-level data spanning a full market cycle to study displacement, rent burden, or housing policy over time.
No data science lift required
Work from a clean, exportable dataset that drops directly into analysis, no pipeline or parsing needed before a study begins.
Dwellsy is one of the most accurate and reliable data comps tools we've used. As an investor, having clean, factual, and real-time comps is a game-changer. It helps us more efficiently and effectively do our work, and we love the product.
See a study built on our data
Get an example of a completed research study using Dwellsy IQ data, so your team can see how it’s structured, scoped, and cited before committing to your own.
Scope your study to your jurisdiction
Tell us the geography, time range, and asset class your research needs. We’ll scope a historical dataset to fit your study and your budget.
FAQ
What geography can this data be scoped to?
Dwellsy IQ data rolls up to ZIP code, city, MSA, state, or nationwide from the same unit-level source. A dataset can be bounded to a single county, state, or MSA, exactly the jurisdiction a study requires, nothing broader or more expensive.
Do we need a data science team to use this?
Although we do offer customizable products, having a data science team is preferable if you want to get the most out of a more tailored dataset.
How far back does the historical data go?
Back to January 2020, which covers the COVID-era rent shock and the post-pandemic normalization period, a critical window for most affordability and policy research.
Why should I choose Dwellsy IQ over scraped or survey data?
Scraped data carries duplication and legal exposure since most sites’ terms of service prohibit it. Survey data is self-reported, infrequent, and often months old by the time it’s published. Dwellsy IQ avoids both problems: it’s compliant, continuously updated, and reliable to cite directly in a report.
Can we purchase a one-time dataset instead of a subscription?
Yes. Most policy and affordability research is grant-funded or tied to a single project, not an ongoing budget line. Data can be purchased as a one-time historical snapshot scoped to your study.
Will this data hold up in a peer-reviewed paper or public report?
Absolutely. Because the data is directly captured where the rent is actually set with documented provenance, it can be described plainly in a methodology section, unlike scraped data, which carries duplication and legal ambiguity, or survey data, which is self-reported and infrequent.
Does this cover both single-family rentals and multifamily?
Yes. Coverage spans SFR and multifamily in the same dataset, which matters for affordability studies that need to account for the full rental housing stock in a jurisdiction, not just one asset type.
We don’t have grant funding approved yet, can we still talk?
Yes. Many research and policy teams explore data before funding is confirmed. Reach out and we’ll scope a dataset and price so you can plan for it in your next budget cycle. Our data is also available through Dewey, if that’s an easier path for your procurement process.
How is this different from HUD or Census rental data?
Federal survey data is valuable for broad trends but is collected infrequently and at high levels of aggregation. Dwellsy IQ is unit-level, continuously updated, and can be scoped to a specific jurisdiction with far more granularity and recency.
Equal Housing Opportunity