Data on resident owners who are persons occupying one of their residential properties: sex, age, total income, the type and the assessment value of the owner-occupied property, as well as the number and the total assessment value of residential properties owned.

Data about the local area where a property is located. The product includes a variety of data: - Demographics (Population, employment, ethnicity, etc) Data is aggregated and available at the following geos: U.S. National, States, Counties, County Subdivisions, Core Based Statistical Areas (CBSA), Combined Statistical Areas (CSA), Incorporated Places, Census Designated Places (CDP), Tracts, Block Groups, Postal Cities, Zip Codes, Neighborhoods and Residential Subdivisions

Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).

Real Estate Market size was valued at USD 79.7 Trillion in 2024 and is projected to reach USD 103.6 Trillion by 2031, growing at a CAGR of 5.1% during the forecasted period 2024 to 2031

Global Real Estate Market Drivers

Population Growth and Urbanization: In order to meet the demands of businesses, housing needs, and infrastructure development, there is a constant need for residential and commercial properties as populations and urban areas rise.

Low Interest Rates: By making borrowing more accessible, low interest rates encourage both individuals and businesses to make real estate investments. Reduced borrowing costs result in reduced mortgage rates, opening up homeownership and encouraging real estate investments and purchases.

Economic Growth: A thriving real estate market is a result of positive economic growth indicators like GDP growth, rising incomes, and low unemployment rates. Robust economies establish advantageous circumstances for real estate investment, growth, and customer assurance in the housing sector. Job growth and income increases: As more people look for rental or purchase close to their places of employment, housing demand is influenced by these factors. The housing market is driven by employment opportunities and rising salaries, which in turn drive home buying, renting, and property investment activity. Infrastructure Development: The demand and property values in the surrounding areas can be greatly impacted by investments made in infrastructure projects such as public facilities, utilities, and transportation networks. Accessibility, convenience, and beauty are all improved by improved infrastructure, which encourages real estate development and investment.

Government Policies and Incentives: Tax breaks, subsidies, and first-time homebuyer programs are a few examples of government policies and incentives that can boost the real estate market and homeownership. Market stability and growth are facilitated by regulatory actions that promote affordable housing, urban redevelopment, and real estate development.

Foreign Investment: Foreign capital can be used to stimulate demand, diversify property portfolios, and pump capital into the real estate market through direct property purchases or real estate investment funds. Foreign investors are drawn to the local real estate markets by favorable exchange rates, stable political environments, and appealing returns.

Demographic Trends: Shifting demographic trends affect housing preferences and demand for various property kinds. These trends include aging populations, household formation rates, and migration patterns. It is easier for real estate developers and investors to match supply with changing market demand when they are aware of demographic fluctuations.

Technological Innovations: New technologies that are revolutionizing the marketing, transactions, and management of properties include digital platforms, data analytics, and virtual reality applications. In the real estate industry, technology adoption increases market reach, boosts customer experiences, and increases operational efficiency.

Environmental Sustainability: Decisions about real estate development and investment are influenced by the growing knowledge of environmental sustainability and green building techniques. Market activity in environmentally aware real estate categories is driven by demand for eco-friendly neighborhoods, sustainable design elements, and energy-efficient buildings.

Success.ai’s Commercial Real Estate Data and B2B Contact Data for Global Real Estate Professionals is a comprehensive dataset designed to connect businesses with industry leaders in real estate worldwide. With over 170M verified profiles, including work emails and direct phone numbers, this solution ensures precise outreach to agents, brokers, property developers, and key decision-makers in the real estate sector.

Utilizing advanced AI-driven validation, our data is continuously updated to maintain 99% accuracy, offering actionable insights that empower targeted marketing, streamlined sales strategies, and efficient recruitment efforts. Whether you’re engaging with top real estate executives or sourcing local property experts, Success.ai provides reliable and compliant data tailored to your needs.

Key Features of Success.ai’s Real Estate Professional Contact Data

• Comprehensive Industry Coverage Gain direct access to verified profiles of real estate professionals across the globe, including:

1. Real Estate Agents: Professionals facilitating property sales and purchases.
2. Brokers: Key intermediaries managing transactions between buyers and sellers.
3. Property Developers: Decision-makers shaping residential, commercial, and industrial projects.
4. Real Estate Executives: Leaders overseeing multi-regional operations and business strategies.
5. Architects & Consultants: Experts driving design and project feasibility.

• Verified and Continuously Updated Data

AI-Powered Validation: All profiles are verified using cutting-edge AI to ensure up-to-date accuracy. Real-Time Updates: Our database is refreshed continuously to reflect the most current information. Global Compliance: Fully aligned with GDPR, CCPA, and other regional regulations for ethical data use.

• Customizable Data Delivery Tailor your data access to align with your operational goals:

API Integration: Directly integrate data into your CRM or project management systems for seamless workflows. Custom Flat Files: Receive detailed datasets customized to your specifications, ready for immediate application.

Why Choose Success.ai for Real Estate Contact Data?

• Best Price Guarantee Enjoy competitive pricing that delivers exceptional value for verified, comprehensive contact data.

• Precision Targeting for Real Estate Professionals Our dataset equips you to connect directly with real estate decision-makers, minimizing misdirected efforts and improving ROI.

• Strategic Use Cases

  Lead Generation: Target qualified real estate agents and brokers to expand your network. Sales Outreach: Engage with property developers and executives to close high-value deals. Marketing Campaigns: Drive targeted campaigns tailored to real estate markets and demographics. Recruitment: Identify and attract top talent in real estate for your growing team. Market Research: Access firmographic and demographic data for in-depth industry analysis.

• Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 30M Company Profiles 700M Global Professional Profiles

• Powerful APIs for Enhanced Functionality

  Enrichment API Ensure your contact database remains relevant and up-to-date with real-time enrichment. Ideal for businesses seeking to maintain competitive agility in dynamic markets.

Lead Generation API Boost your lead generation with verified contact details for real estate professionals, supporting up to 860,000 API calls per day for robust scalability.

• Use Cases for Real Estate Contact Data

1. Targeted Outreach for New Projects Connect with property developers and brokers to pitch your services or collaborate on upcoming projects.

2. Real Estate Marketing Campaigns Execute personalized marketing campaigns targeting agents and clients in residential, commercial, or industrial sectors.

3. Enhanced Sales Strategies Shorten sales cycles by directly engaging with decision-makers and key stakeholders.

4. Recruitment and Talent Acquisition Access profiles of highly skilled professionals to strengthen your real estate team.

5. Market Analysis and Intelligence Leverage firmographic and demographic insights to identify trends and optimize business strategies.

• What Makes Us Stand Out? >> Unmatched Data Accuracy: Our AI-driven validation ensures 99% accuracy for all contact details. >> Comprehensive Global Reach: Covering professionals across diverse real estate markets worldwide. >> Flexible Delivery Options: Access data in formats that seamlessly fit your existing systems. >> Ethical and Compliant Data Practices: Adherence to global standards for secure and responsible data use.

Success.ai’s B2B Contact Data for Global Real Estate Professionals delivers the tools you need to connect with the right people at the right time, driving efficiency and success in your business operations. From agents and brokers to property developers and executiv...

Number of residents owners who are persons occupying one of their residential properties, as well as the total assessment value of owned properties, total family income, family size, by sex, family type, and age.

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Residential property price statistics from different countries. Contains property price indicators (real series are the nominal price series deflated by the consumer price index), both in levels and in growth rates. Can be used for property market analysis.

Data

This data comes from Bank For International Settlements BIS.

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.

1. Customers File (customers.csv)

• Description: This file contains information about clients involved in real estate transactions. It includes personal details such as name, surname, birth date, gender, and country, along with transaction-specific information like the purpose of the deal and the satisfaction level.
• Key Columns:
  • customerid: Unique identifier for the customer.
  • entity: Type of client, whether an individual or a company.
  • name and surname: First and last name of the customer.
  • birth_date: Customer's date of birth.
  • sex: Gender of the customer (Male/Female).
  • country and state: The country and state the customer is associated with.
  • purpose: Purpose of the transaction (e.g., Home purchase or Investment).
  • deal_satisfaction: Customer's satisfaction level with the transaction, ranging from 1 to 5.
  • mortgage: Indicates whether the transaction involved a mortgage (Yes/No).
  • source: How the customer was acquired (e.g., Website or Agency).

2. Properties File (properties.csv)

• Description: This file contains information about the properties sold, including building details, property type, area, price, and sale status.
• Key Columns:
  • id: Unique identifier for the property.
  • building: Number of the building where the property is located.
  • date_sale: The date when the property was sold.
  • type: Type of property (e.g., Apartment).
  • property#: The property number within the building.
  • area: Area of the property in square feet.
  • price: Sale price of the property.
  • status: Status of the sale (e.g., Sold).
  • customerid: The unique identifier of the customer associated with the property.

Suggested Analysis and Tasks

1 Customer Insights: - Customer Segmentation: Group customers based on demographics, purpose, or deal satisfaction to understand different customer profiles. - Satisfaction Analysis: Investigate what factors (e.g., property price, area, or mortgage involvement) influence customer satisfaction levels. - Source Effectiveness: Analyze which acquisition sources (e.g., website or agency) yield the highest deal satisfaction.

2 Property Market Analysis: - Price Trends: Analyze how property prices vary over time or by location to identify market trends. - Demand Analysis: Determine which types of properties (e.g., apartments vs. houses) are most popular based on sales data. - Area vs. Price: Explore the relationship between property area and price to develop pricing models or evaluate property value.

3 Predictive Modeling: - Price Prediction: Build models to predict property prices based on features like area, type, and location. - Satisfaction Prediction: Create models to predict customer satisfaction using transaction details and demographics. - Likelihood of Sale: Develop a model to predict the likelihood of a property being sold based on its attributes and market conditions.

4 Geographical Analysis: - Heatmaps: Create heatmaps to visualize property sales and identify high-demand areas. - Country and State Trends: Examine how real estate trends differ between countries and states.

5 Mortgage Impact Study: - Mortgage vs. Non-Mortgage Analysis: Compare transactions that involved a mortgage to those that didn’t to study the impact on price, satisfaction, and deal closure speed.

6 Time Series Analysis: - Sales Over Time: Analyze property sales over different periods to identify seasonal trends or patterns. - Customer Birth Date Analysis: Study any correlations between customers’ birth years and their purchasing behavior.

Frequency: OccasionalTable: 46-10-0038-01Release date: 2022-04-12Geography: Province or territory, Census subdivision, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partSymbol legend:.. / not available for a specific reference periodx / suppressed to meet the confidentiality requirements of the Statistics ActA / data quality: excellentThe footnotes in the table are represented in brackets.1) The universe of this table is restricted to individual resident owners who occupy a residential property. An owner's geographic location is determined by the location of the occupied property for both single- and multiple-property owners. A residential property refers to all land and structures intended for private occupancy whether on a permanent or a temporary basis.2) The geographic boundaries used in this table are the 2016 census subdivisions boundaries.3) Previous reference period estimates are subject to revision.4) The Composite Quality Indicator (CQI) shown in this table is created by combining many individual quality indicators, each one representing the quality of different Canadian Housing Statistics Program (CHSP) data processing steps (for example: coding, geocoding, linkage and imputation) and includes the following values: A - Excellent: All domain variables and the variable of interest are of excellent quality. B - Very good: All domain variables and the variable of interest are of very good to excellent quality. C - Good: The quality of some of the domain variables or the variable of interest is considered good while all the other variables are of very good to excellent quality. D - Acceptable: The quality of some of the domain variables or the variable of interest is considered acceptable while all the other variables are of good to excellent quality. E - Use with caution: Several domain variables or the variable of interest are of poor quality. F - Too unreliable to be published. The CQIs are available starting with the reference period of 2020, except for the Northwest Territories where they are available from 2019 reference period.5) Property type" refers to property characteristics and/or dwelling configuration on which there can be one or more residential structures. Property types include single-detached houses, on which there can be one or more residential structures. Property types include single-detached houses, condominium apartments, mobile homes, other property types, properties with multiple residential units, and vacant land."6) Estimates by property type in Newfoundland and Labrador are only available in the census subdivision of St. John’s.7) Estimates by property type in Northwest Territories are not available.8) Estimates by property type in Nunavut are not available.9) The number of properties owned by the property owner is limited to residential properties that are within a given province.10) Newfoundland and Labrador estimates are not available at the provincial level and for the category “Outside of census metropolitan areas (CMAs) and census agglomerations (CAs)”.11) Northwest Territories estimates are only available in the census agglomeration of Yellowknife.12) Counts undergo random rounding, a process that transforms all raw counts into randomly rounded counts. This reduces the possibility of identifying individuals in the tabulations. All percentages are derived from rounded counts, subtotals and totals may not exactly equal the sum of components due to system rounding.13) The number of property owners estimates are not available for the 2018 reference period.14) The number of owners should be used with caution outside of census metropolitan areas (CMAs) and census agglomerations (CAs), as well as the proportion of owners by geography. This note does not apply to Nunavut.15) Assessment value" refers to the assessed value of the property for the purposes of determining property taxes. It is important to note that the assessed value does not necessarily represent the market value. Given that different provinces and territories have their own assessment periods and duration of the valuation roll, it is difficult to make accurate comparisons of similar properties from one province or territory to another. For properties that are being utilized for both residential and non-residential purposes, only the residential portion's value has been taken into account. The reference years of the assessment values by province or territory are available here: Canadian Housing Statistics Program (CHSP)."16) For Nunavut, the property use indicator is not available, the universe of this table includes all individual resident owners. For owners with multiple properties, the geographic location and type of property are from the residential property with the highest assessment value.

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.

Frequency: OccasionalTable: 46-10-0038-01Release date: 2022-04-12Geography: Province or territory, Census subdivision, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partSymbol legend:.. / not available for a specific reference periodx / suppressed to meet the confidentiality requirements of the Statistics ActA / data quality: excellentThe footnotes in the table are represented in brackets.1) The universe of this table is restricted to individual resident owners who occupy a residential property. An owner's geographic location is determined by the location of the occupied property for both single- and multiple-property owners. A residential property refers to all land and structures intended for private occupancy whether on a permanent or a temporary basis.2) The geographic boundaries used in this table are the 2016 census subdivisions boundaries.3) Previous reference period estimates are subject to revision.4) The Composite Quality Indicator (CQI) shown in this table is created by combining many individual quality indicators, each one representing the quality of different Canadian Housing Statistics Program (CHSP) data processing steps (for example: coding, geocoding, linkage and imputation) and includes the following values: A - Excellent: All domain variables and the variable of interest are of excellent quality. B - Very good: All domain variables and the variable of interest are of very good to excellent quality. C - Good: The quality of some of the domain variables or the variable of interest is considered good while all the other variables are of very good to excellent quality. D - Acceptable: The quality of some of the domain variables or the variable of interest is considered acceptable while all the other variables are of good to excellent quality. E - Use with caution: Several domain variables or the variable of interest are of poor quality. F - Too unreliable to be published. The CQIs are available starting with the reference period of 2020, except for the Northwest Territories where they are available from 2019 reference period.5) Property type" refers to property characteristics and/or dwelling configuration on which there can be one or more residential structures. Property types include single-detached houses, semi-detached houses, condominium apartments, mobile homes, other property types, properties with multiple residential units and vacant land."6) Estimates by property type in Newfoundland and Labrador are only available in the census subdivision of St. John’s.7) Estimates by property type in Northwest Territories are not available.8) Estimates by property type in Nunavut are not available.9) The number of properties owned by the property owner is limited to residential properties that are within a given province.10) Newfoundland and Labrador estimates are not available at the provincial level and for the category “Outside of census metropolitan areas (CMAs) and census agglomerations (CAs)”.11) Northwest Territories estimates are only available in the census agglomeration of Yellowknife.12) Counts undergo random rounding, a process that transforms all raw counts into randomly rounded counts. This reduces the possibility of identifying individuals in the tabulations. All percentages are derived from rounded counts, subtotals and totals may not exactly equal the sum of components due to system rounding.13) The number of property owners estimates are not available for the 2018 reference period.14) The number of owners should be used with caution outside of census metropolitan areas (CMAs) and census agglomerations (CAs), as well as the proportion of owners by geography. This note does not apply to Nunavut.15) Assessment value" refers to the assessed value of the property for the purposes of determining property taxes. It is important to note that the assessed value does not necessarily represent the market value. Given that different provinces and territories have their own assessment periods and duration of the valuation roll, it is difficult to make accurate comparisons of similar properties from one province or territory to another. For properties that are being utilized for both residential and non-residential purposes, only the residential portion's value has been taken into account. The reference years of the assessment values by province or territory are available here: Canadian Housing Statistics Program (CHSP)."16) For Nunavut, the property use indicator is not available, the universe of this table includes all individual resident owners. For owners with multiple properties, the geographic location and type of property are from the residential property with the highest assessment value.17) Averages and medians are calculated using values greater than zero for the variables of interest.18) Total assessment value" represents the sum of the assessment values of all residential properties owned by an owner within a given province."19) Total income of person" refers to the total income of an individual, before deductions for income taxes, during the previous year. This income measure is the sum of market income and government transfers. Market income includes employment income, investment income, private retirement income and other income from market sources during the previous year. Government transfers refer to all cash benefits received from federal, provincial, territorial or municipal governments during the previous year."Cite: Statistics Canada. Table 46-10-0038-01 Single and multiple residential property owners: demographic data and value of properties ownedhttps://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=4610003801

The n3 Real Estate company, a prominent player in the real estate industry, is a valuable resource for those seeking information on property listings and market trends. With a focus on providing accurate and reliable data, n3 Real Estate aggregates and consolidates information from various sources to give users a comprehensive view of the real estate market.

As a leading real estate data provider, n3 Real Estate offers a vast repository of information, covering everything from property listings and market analytics to sales trends and demographic data. The company's extensive database and robust tools enable users to gain insights into the real estate market, making it an essential resource for real estate professionals, investors, and homeowners alike. With its commitment to quality and accuracy, n3 Real Estate has established itself as a trusted authority in the real estate industry.

Number of residents owners who are persons occupying one of their residential properties, as well as the assessment value of owned properties, total income, age, by type of occupied property, total number of residential properties, and sex.

The Analyst Pro is a leading analysis and marketing platform for commercial real estate professionals, providing a comprehensive suite of tools for investment modeling, demographic analysis, and property marketing. With The Analyst Pro, users can easily create sophisticated reports, offering memorandums, flyers, and brochures, as well as analyze properties and make informed investment decisions.

The company offers a range of innovative features, including investment analysis, demographic analysis, location risk analysis, and more. These features enable commercial real estate professionals to gain a competitive edge in their market, streamline their workflow, and provide exceptional services to their clients. With The Analyst Pro, users can quickly and easily analyze properties, identify trends, and make data-driven decisions with confidence.

Data on resident buyers who are persons that purchased a residential property in a market sale and filed their T1 tax return form: number of and incomes of residential property buyers, sale price, price-to-income ratio by the number of buyers as part of a sale, age groups, first-time home buyer status, buyer characteristics (sex, family type, immigration status, period of immigration, admission category).

HousingCatalyst is a prominent real estate consultancy that provides in-depth market analysis and insights to investors, developers, and policymakers. With a focus on data-driven decision-making, the company's expertise spans market research, economic modeling, and strategic planning. Their online presence offers a treasure trove of information on the residential and commercial property markets, including demographic trends, housing affordability, and market forecasts.

By delving into HousingCatalyst's online repository, users can expect to find valuable data on emerging trends, market fluctuations, and regulatory changes that impact the real estate industry. The company's extensive research library is a goldmine of information for industry professionals, academics, and policymakers seeking to stay abreast of the latest developments in the sector. With a strong reputation for expertise and accuracy, HousingCatalyst's online presence is a go-to resource for those seeking insights to inform their real estate decisions.

The US Consumer Residential Property/Real Estate file has 140 million+ records of 98% accuracy which include home details, site details, and purchase details on residential properties. This file includes both owners and renters with linkages to Consumer Demographics.

We have developed this file to be tied to our Consumer Demographics Database so additional demographics can be applied as needed. Each record is ranked by confidence and only the highest quality data is used. This file contains over 120 million records.

Note - all Consumer packages can include necessary PII (address, email, phone, DOB, etc.) for merging, linking, and activation of the data. Also, the datasets include more information than the one provided in the sample, don't hesitate to contact us to receive a full layout. The sample was shortened for reading convenience.

BigDBM Privacy Policy: https://bigdbm.com/privacy.html

A global database of Real Estate Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.

Leverage up-to-date urban planning data with population trends for real estate, market research, audience targeting, and sales territory mapping.

Self-hosted commercial real estate dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The Urban Planning Data is standardized, unified, and ready to use.

Use cases for the Global Population Database (Urban Planning Data)

• Ad targeting

• B2B Market Intelligence

• Customer analytics

• Real Estate Data Estimations

• Marketing campaign analysis

• Demand forecasting

• Sales territory mapping

• Retail site selection

• Reporting

• Audience targeting

Demographic data export methodology

Our location data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Historical population data (55 years)

• Changes in population density

• Urbanization Patterns

• Accurate at zip code and administrative level

• Optimized for easy integration

• Easy customization

• Global coverage

• Updated yearly

• Standardized and reliable

• Self-hosted delivery

• Fully aggregated (ready to use)

• Rich attributes

Why do companies choose our Real Estate databases

• Standardized and unified demographic data structure

• Seamless integration in your system

• Dedicated location data expert

Note: Custom population data packages are available. Please submit a request via the above contact button for more details.

Comprehensive demographic dataset for Pacific Properties, Commerce City, CO, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.