Just a small share of renters in the United States were homeowner ready in 2022. In El Paso, TX, the percentage of renters who could afford to buy a home with a seven percent mortgage was the highest at about ** percent. Homeownership in Urban Honolulu, HI, San Diego, CA, and Los Angeles, CA, was most out of reach, with less than **** percent who could afford to buy a home.

Graph and download economic data for Homeownership Rate in the United States (RHORUSQ156N) from Q1 1965 to Q2 2025 about homeownership, housing, rate, and USA.

The homeownership rate in the United States declined slightly in 2023 and remained stable in 2024. The U.S. homeownership rate was the highest in 2004 before the 2007-2009 recession hit and decimated the housing market. In 2024, the proportion of households occupied by owners stood at **** percent in 2024, *** percentage points below 2004 levels. Homeownership since the recession The rate of homeownership in the U.S. fell in the lead up to the recession and continued to do so until 2016. Despite this trend, the share of Americans who perceived homeownership as part of their personal American dream remained relatively stable. This suggests that the financial hardship caused by the recession led to the fall in homeownership, rather than a change in opinion about the importance of homeownership itself. What the future holds for homeownership Homeownership trends vary from generation to generation. Homeownership among Americans over 65 years old is declining, whereas most Millennial renters plan to buy a home in the near future. This suggests that homeownership will remain important in the future, as Millennials are forecast to head most households over the next two decades.

This graph shows the results of a survey on the most important factors influencing homeowners in the United States to buy or build a green home. As of October 2013, some ** percent strongly agree that durability is a key factor to buy or build a green home.

Home Ownership Rate in the United States decreased to 65 percent in the second quarter of 2025 from 65.10 percent in the first quarter of 2025. This dataset provides the latest reported value for - United States Home Ownership Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The homeownership rate was the highest among Americans in their early 70s and the lowest among people in their early 20s in 2024. In that year, approximately **** percent of individuals aged 70 to 74 resided in a residence they owned, compared to approximately ** percent among individuals under the age of 25. On average, **** percent of Americans lived in an owner-occupied home. The homeownership rate was the highest in 2004 but has since declined.

Get homeowner contact info so you can target the right prospects. With Cole you have access to hyperlocal homeowner data that pinpoints the right prospects in exactly the right area.

Since 1947, Cole Information has helped real estate, insurance, and home service professionals reach the homeowners who need their help.

We started with reverse-look-up phone books used by door-to-door broom sellers, and we’ve evolved along the way into a software company with sophisticated tools that help people like you generate leads that help them serve homeowners.

Cole’s products help professionals create effective prospecting strategies in real estate, insurance, and home services.

Homeowners’ insurers have experienced a substantial increase in demand for their services in recent years, though there have been significant challenges due to high revenue volatility. Escalating climate change has led to more frequent and severe disasters, driving a surge in demand for homeowners’ insurance as households seek financial protection from property losses. Major events, such as the 2021 Texas winter storm and Hurricane Ian in 2022, as well as widespread tornadoes and floods, have led to higher claims and more comprehensive policy purchases, boosting revenue in 2023 and 2024. Economic swings and high volatility have pressured smaller insurers, leading to exits and fewer new entrants, which has raised top providers’ market share since 2020. Meanwhile, high interest rates between 2022 and 2024 have improved investment returns, but expected rate cuts in 2025–2026 will likely slow income growth through fewer opportunities with these investment vehicles. Overall, revenue for homeowners’ insurance businesses has surged at a CAGR of 6.6% in the past five years, reaching $175.1 billion in 2025. This includes a 2.0% rise in revenue in that year. Providers will face new opportunities and challenges moving forward. In 2025, new tariffs increased goods prices and input costs, reducing household spending power and threatening a recession. This pressured demand for homeowners’ insurance has led to forecasts of slower revenue growth and increased market consolidation through mergers and acquisitions among large insurers. Despite this, long-term prospects for the industry are positive. As productivity rises, disposable incomes are expected to recover, supporting home purchases and sustained demand for insurance through 2030. Climate change will drive more severe natural disasters, encouraging households to buy comprehensive policies and further boost revenue. Yet, high housing costs will constrain homeownership rates, limiting the pool of potential customers insurers have access to. Increased government intervention will keep insurers afloat, boosting their profit and reducing barriers to entry. Overall, revenue for homeowners’ insurers is forecast to expand at a CAGR of 3.1% over the next five years, reaching $203.7 billion in 2030.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner by Age: from Age 25 to 34 (CXUHOMEOWNLB0403M) from 1990 to 2023 about consumer unit, age, homeownership, 25 years +, percent, and USA.

Graph and download economic data for Consumer Unit Characteristics: Percent Homeowner without Mortgage by Housing Tenure: Home Owner (CXU980240LB1702M) from 1984 to 2023 about consumer unit, homeownership, mortgage, percent, housing, and USA.

New Homeowner Data is a subset of our comprehensive property intelligence database that can be segmented by specific property criteria, household demographics, mortgage, and real estate portfolio information.

Companies in the home services, financial products, and consumer products industries use BatchData to identify new homeowners who have purchased a property in the last 90 days and uncover their direct phone number, email, and mailing address for timely marketing of products and services new homeowners need. New homeowner data can also be segmented property type (residential real estate or commercial real estate), length of ownership, owner occupancy status, and more!

New homeowner data is available in a variety of data delivery and data enrichment modes: API (you pull data from us using an API), webhook (we push data to you using an API), AWS S3 upload (we deliver the data to you), S3 download (you download the data from our S3 bucket), SFTP.

BatchData is both a data and technology solution helping companies in and around the real estate ecosystem achieve faster growth. BatchData specializes in providing accurate contact information for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, and power their products and services.

This is a data set of homeowners in the United States. Data can be segmented and ordered based on State, City, Household income, Individual age, and length of residence (Years). Data also includes First name, Last name, email, address, city, state, zip code, and phone. You can order some or all columns. Example: If you do not need household income, we can remove the column and lower the price accordingly.

The KinderData New Mover Dataset delivers nationwide coverage of over 160 million U.S. properties, connecting verified homeowner, contact, and move-event intelligence to the most accurate property records available. Updated continuously from assessor, recorder, and address-change sources, KinderData provides a unified view of every U.S. property and homeowner—ideal for marketing, analytics, and customer acquisition.

Data Coverage

Nationwide coverage across all 50 U.S. states

160M+ residential properties with owner and contact details

Verified move-event intelligence from assessor and change-of-address data

Linked homeowner profiles including property type, ownership status, and contact enrichment

Updated daily for accuracy and recency

Use Cases

Identify and reach new movers at peak purchasing intent

Power direct mail, digital, and CRM campaigns for homeowner marketing

Target homeowners by move date, property characteristics, or location

Industries Served

Roofing & Construction

HVAC Providers

Solar Installation

Landscaping & Lawn Care

Junk Removal & Cleaning Services

Pest Control & Home Renovation

Insurance, Real Estate & Home Improvement Marketing

Why Choose KinderData

KinderData delivers enterprise-grade real estate and homeowner data sourced directly from official assessor, recorder, and registry feeds—ensuring accuracy, compliance, and unmatched coverage. Our New Mover Dataset enables service providers to connect with verified homeowners and generate high-quality leads at the exact moment they’re ready to buy.

Our US Home Ownership Data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes various data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

This service denotes the service areas for HUD's Homeownership Centers (HOCs) which help insure single family Federal Housing Administration (FHA) mortgages, and oversee the selling of HUD homes. Processing for much of the Single Family FHA mortgages is centralized into one of four Homeownership Centers (HOC) located in Atlanta, Philadelphia, Denver, and Santa Ana; each supporting specific geographic region. Although most questions are handled by the FHA Resource Center (not the HOC) for immediate acknowledgement and tracking, certain case specific issues will subsequently be referred to the appropriate center.

The number of mortgage possessions spiked in the first quarter of 2023, followed by ***** quarters of decline. Possession actions occur when a borrower fails to repay their loan on time and the lender takes possession of the property. In the fourth quarter of 2023, there were *** possessions of properties occupied by homeowners and *** possessions of buy-to-let properties.

Graph and download economic data for Homeownership Rate for Florida (FLHOWN) from 1984 to 2024 about homeownership, FL, housing, rate, and USA.

Data comes from the Home Mortgage Disclosure Act and represents home purchases secured by a first lien that are intended to be occupied by the purchaser (not investment homes). Visit https://www.consumerfinance.gov/data-research/hmda/ for more information.

Graph and download economic data for Producer Price Index by Industry: Premiums for Property and Casualty Insurance: Premiums for Homeowner's Insurance (PCU9241269241262) from Jun 1998 to Sep 2025 about property-casualty, premium, insurance, housing, PPI, industry, inflation, price index, indexes, price, and USA.

This service denotes the service areas for HUD's Homeownership Centers (HOCs) by state. Processing for much of the Single Family FHA mortgages is centralized into one of four HOCs located in Atlanta, Philadelphia, Denver, and Santa Ana; each supporting specific geographic region. Although most questions are handled by the FHA Resource Center (not the HOC) for immediate acknowledgement and tracking, certain case specific issues will subsequently be referred to the appropriate center.