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.

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.

Multiple advantages with Home Owner Data Set: Increase campaign ROI with personalized and targeted engagements. Utilize predictive real estate data attributes such as home value, purchase date, property descriptors, and mortgage information. Focus resources on high-value prospects and their preferences Maximize conversions with personalized marketing campaigns featuring relevant real estate intelligence. Engage your target audience with messaging tailored to their interests and needs.

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.

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.

BatchData provides comprehensive home ownership data for 87 million owners of residential homes in the US. We specialize in providing accurate contact information for owners of specific properties, trusted by some of the largest real estate companies for our superior capabilities in accurately unmasking owners of properties that may be hidden behind LLCs and corporate veils.

Our home ownership data is commonly used to fuel targeted marketing campaigns, generating real estate insights, powering websites/applications with real estate intelligence, and enriching sales and marketing databases with accurate homeowner contact information and surrounding intelligence to improve segmentation and targeting.

Home ownership data that is linked to a given property includes: - Homeowner Name(s) - Homeowner Cell Phone Number - Homeowner Email Address - Homeowner Mailing Address - Addresses of Properties Owned - Homeowner Portfolio Equity - Total Number of Properties Owned - Property Characteristics of Properties Owned - Homeowner sales, loan, and mortgage information - Property Occupancy Status of Properties Owned - Property Valuation & ARV information of Properties Owned - Ownership Length - Ownership History - Homeowner Age - Homeowner Marital Status - Homeowner Income - and more!

BatchService is both a data and technology company helping companies in and around the real estate ecosystem achieve faster growth. BatchService specializes in providing accurate B2B and B2C contact data 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, consolidate their data providers, and power their products and services.

Home Ownership Rate in the United States decreased to 65.10 percent in the first quarter of 2025 from 65.70 percent in the fourth quarter of 2024. 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 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.

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.

Find people who have recently purchased a home in any neighborhood anywhere in the USA. This covers only homeowners - not renters. Filter by people who moved in-state or out-of-state, in-city or out-of-city, in-zip-code or out-of-zip-code. Also filter by dwelling type and recency of their move.

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.

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.

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.

Graph and download economic data for Homeownership Rate for California (CAHOWN) from 1984 to 2024 about homeownership, CA, housing, rate, and USA.

Set Up We’ll help ensure you’re set up to get the data you need, how you need it. We’ll help you through provisioning the extraction, enrichment, formatting, delivery/update schedule, and reporting around your data. With hundreds of unique data points available, the information you need to find leads fast is at your fingertips - new homeowner data, home ownership data, B2C contact data and more, built for professional services companies.

Custom Development We provide technical resources to support integration and delivery requirements specific to your business needs, augmenting developer resources to keep your team focused on other tasks.

Enrichment Services Enrichment services improve the accuracy, completeness, and depth of your dataset by regularly filling in blank values, and updating outdated records. We’ll help ensure that the specific data points, update candances, and replacement rules fit your GTM strategy.

Analysis Healthcheck We’ll audit your organization’s data health and usage strategy, and make sure you’re focused on the right KPIs and performance metrics.

Implementation Support From technical architecture to scheduled and flexible delivery of data in multiple formats, we make it easy to realize the value of better data.

Data Blending & Enhancement Combine multiple data sources to create a single, new dataset to standardize operations and enable better reporting.

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.

In 2022, three in four millennials who had given up on homeownership said that they would most probably always rent because they think they cannot afford to buy a home. Approximately one 26 percent of millennials did not plan to become a homeowner because of the flexibility associated with renting. In the past years, the share of millennials that expect to always rent has been increasing.

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.

Home Ownership Rate in Denmark increased to 60.90 percent in 2024 from 60 percent in 2023. This dataset provides the latest reported value for - Denmark Home Ownership Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.