100+ datasets found
  1. d

    Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing &...

    • datarade.ai
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    AutoScraping, Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing & Market Insights [Dataset]. https://datarade.ai/data-products/autoscraping-s-zillow-usa-real-estate-data-10m-listings-wit-autoscraping
    Explore at:
    .json, .csv, .xls, .sqlAvailable download formats
    Dataset authored and provided by
    AutoScraping
    Area covered
    United States
    Description

    Autoscraping's Zillow USA Real Estate Data is a comprehensive and meticulously curated dataset that covers over 10 million property listings across the United States. This data product is designed to meet the needs of professionals across various sectors, including real estate investment, market analysis, urban planning, and academic research. Our dataset is unique in its depth, accuracy, and timeliness, ensuring that users have access to the most relevant and actionable information available.

    What Makes Our Data Unique? The uniqueness of our data lies in its extensive coverage and the precision of the information provided. Each property listing is enriched with detailed attributes, including but not limited to, full addresses, asking prices, property types, number of bedrooms and bathrooms, lot size, and Zillow’s proprietary value and rent estimates. This level of detail allows users to perform in-depth analyses, make informed decisions, and gain a competitive edge in their respective fields.

    Furthermore, our data is continually updated to reflect the latest market conditions, ensuring that users always have access to current and accurate information. We prioritize data quality, and each entry is carefully validated to maintain a high standard of accuracy, making this dataset one of the most reliable on the market.

    Data Sourcing: The data is sourced directly from Zillow, one of the most trusted names in the real estate industry. By leveraging Zillow’s extensive real estate database, Autoscraping ensures that users receive data that is not only comprehensive but also highly reliable. Our proprietary scraping technology ensures that data is extracted efficiently and without errors, preserving the integrity and accuracy of the original source. Additionally, we implement strict data processing and validation protocols to filter out any inconsistencies or outdated information, further enhancing the quality of the dataset.

    Primary Use-Cases and Vertical Applications: Autoscraping's Zillow USA Real Estate Data is versatile and can be applied across a variety of use cases and industries:

    Real Estate Investment: Investors can use this data to identify lucrative opportunities, analyze market trends, and compare property values across different regions. The detailed pricing and valuation data allow for comprehensive due diligence and risk assessment.

    Market Analysis: Market researchers can leverage this dataset to track real estate trends, evaluate the performance of different property types, and assess the impact of economic factors on property values. The dataset’s nationwide coverage makes it ideal for both local and national market studies.

    Urban Planning and Development: Urban planners and developers can use the data to identify growth areas, plan new developments, and assess the demand for different property types in various regions. The detailed location data is particularly valuable for site selection and zoning analysis.

    Academic Research: Universities and research institutions can utilize this data for studies on housing markets, urbanization, and socioeconomic trends. The comprehensive nature of the dataset allows for a wide range of academic applications.

    Integration with Our Broader Data Offering: Autoscraping's Zillow USA Real Estate Data is part of our broader data portfolio, which includes various datasets focused on real estate, market trends, and consumer behavior. This dataset can be seamlessly integrated with our other offerings to provide a more holistic view of the market. For example, combining this data with our consumer demographic datasets can offer insights into the relationship between property values and demographic trends.

    By choosing Autoscraping's data products, you gain access to a suite of complementary datasets that can be tailored to meet your specific needs. Whether you’re looking to gain a comprehensive understanding of the real estate market, identify new investment opportunities, or conduct advanced research, our data offerings are designed to provide you with the insights you need.

  2. c

    Redfin usa properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
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    Crawl Feeds (2025). Redfin usa properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-usa-properties-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Area covered
    United States
    Description

    Explore the Redfin USA Properties Dataset, available in CSV format. This extensive dataset provides valuable insights into the U.S. real estate market, including detailed property listings, prices, property types, and more across various states and cities. Perfect for those looking to conduct in-depth market analysis, real estate investment research, or financial forecasting.

    Key Features:

    • Comprehensive Property Data: Includes essential details such as listing prices, property types, square footage, and the number of bedrooms and bathrooms.
    • Geographic Coverage: Encompasses a wide range of U.S. states and cities, providing a broad view of the national real estate market.
    • Historical Trends: Analyze past market data to understand price movements, regional differences, and market trends over time.
    • Geo-Location Details: Enables spatial analysis and mapping by including precise geographical coordinates of properties.

    Who Can Benefit From This Dataset:

    • Real Estate Investors: Identify lucrative opportunities by analyzing property values, market trends, and regional price variations.
    • Market Analysts: Gain a deeper understanding of the U.S. housing market dynamics to inform research and reporting.
    • Data Scientists and Researchers: Leverage detailed real estate data for modeling, urban studies, or economic analysis.
    • Financial Analysts: Utilize the dataset for financial modeling, helping to predict market behavior and assess investment risks.

    Download the Redfin USA Properties Dataset to access essential information on the U.S. housing market, ideal for professionals in real estate, finance, and data analytics. Unlock key insights to make informed decisions in a dynamic market environment.

    Looking for deeper insights or a custom data pull from Redfin?
    Send a request with just one click and explore detailed property listings, price trends, and housing data.
    🔗 Request Redfin Real Estate Data

  3. d

    Real Estate Data | Property Listing, Sold Properties, Rankings, Agent...

    • datarade.ai
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    Grepsr, Real Estate Data | Property Listing, Sold Properties, Rankings, Agent Datasets | Global Coverage | For Competitive Property Pricing and Investment [Dataset]. https://datarade.ai/data-products/real-estate-property-data-grepsr-grepsr
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    Grepsr
    Area covered
    Malaysia, Kazakhstan, Holy See, Australia, Spain, South Sudan, Tonga, Congo (Democratic Republic of the), Iraq, Kuwait
    Description

    Extract detailed property data points — address, URL, prices, floor space, overview, parking, agents, and more — from any real estate listings. The Rankings data contains the ranking of properties as they come in the SERPs of different property listing sites. Furthermore, with our real estate agents' data, you can directly get in touch with the real estate agents/brokers via email or phone numbers.

    A. Usecase/Applications possible with the data:

    1. Property pricing - accurate property data for real estate valuation. Gather information about properties and their valuations from Federal, State, or County level websites. Monitor the real estate market across the country and decide the best time to buy or sell based on data

    2. Secure your real estate investment - Monitor foreclosures and auctions to identify investment opportunities. Identify areas within special economic and opportunity zones such as QOZs - cross-map that with commercial or residential listings to identify leads. Ensure the safety of your investments, property, and personnel by analyzing crime data prior to investing.

    3. Identify hot, emerging markets - Gather data about rent, demographic, and population data to expand retail and e-commerce businesses. Helps you drive better investment decisions.

    4. Profile a building’s retrofit history - a building permit is required before the start of any construction activity of a building, such as changing the building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Use building permits to profile a city’s building retrofit history.

    5. Study market changes - New construction data helps measure and evaluate the size, composition, and changes occurring within the housing and construction sectors.

    6. Finding leads - Property records can reveal a wealth of information, such as how long an owner has currently lived in a home. US Census Bureau data and City-Data.com provide profiles of towns and city neighborhoods as well as demographic statistics. This data is available for free and can help agents increase their expertise in their communities and get a feel for the local market.

    7. Searching for Targeted Leads - Focusing on small, niche areas of the real estate market can sometimes be the most efficient method of finding leads. For example, targeting high-end home sellers may take longer to develop a lead, but the payoff could be greater. Or, you may have a special interest or background in a certain type of home that would improve your chances of connecting with potential sellers. In these cases, focused data searches may help you find the best leads and develop relationships with future sellers.

    How does it work?

    • Analyze sample data
    • Customize parameters to suit your needs
    • Add to your projects
    • Contact support for further customization
  4. o

    Zillow Properties Listing Information Dataset

    • opendatabay.com
    .undefined
    Updated Jun 26, 2025
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    Bright Data (2025). Zillow Properties Listing Information Dataset [Dataset]. https://www.opendatabay.com/data/premium/0bdd01d7-1b5b-4005-bb73-345bc710c694
    Explore at:
    .undefinedAvailable download formats
    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Bright Data
    Area covered
    Urban Planning & Infrastructure
    Description

    Zillow Properties Listing dataset to access detailed real estate listings, including property prices, locations, and features. Popular use cases include market analysis, property valuation, and investment decision-making in the real estate sector.

    Use our Zillow Properties Listing Information dataset to access detailed real estate listings, including property features, pricing trends, and location insights. This dataset is perfect for real estate agents, investors, market analysts, and property developers looking to analyze housing markets, identify investment opportunities, and assess property values.

    Leverage this dataset to track pricing patterns, compare property features, and forecast market trends across different regions. Whether you're evaluating investment prospects or optimizing property listings, the Zillow Properties dataset offers essential information for making data-driven real estate decisions.

    Dataset Features

    • zpid: Unique property identifier assigned by Zillow.
    • city: The name of the city where the property is located.
    • state: The state in which the property is located.
    • homeStatus: Indicates the current status of the property
    • address: The full address of the property, including street, city, and state.
    • isListingClaimedByCurrentSignedInUser: This field shows if the current Zillow user has claimed ownership of the listing.
    • isCurrentSignedInAgentResponsible: This field indicates whether the currently signed-in real estate agent is responsible for the listing.
    • bedrooms: Number of bedrooms in the property.
    • bathrooms: Number of bathrooms in the property.
    • price: Current asking price of the property.
    • yearBuilt: The year the home was originally constructed.
    • streetAddress: Specific street address (usually excludes city/state/zip).
    • zipcode: The postal ZIP code of the property.
    • isCurrentSignedInUserVerifiedOwner: This field indicates if the signed-in user has verified ownership of the property on Zillow.
    • isVerifiedClaimedByCurrentSignedInUser: Indicates whether the user has claimed and verified the listing as the current owner.
    • listingDataSource: The original source of the listing. Important for data lineage and trustworthiness.
    • longitude: The longitudinal geographic coordinate of the property.
    • latitude: The latitudinal geographic coordinate of the property.
    • hasBadGeocode: This indicates whether the geolocation data is incorrect or problematic.
    • streetViewMetadataUrlMediaWallLatLong: A URL or reference to the Street View media wall based on latitude and longitude.
    • streetViewMetadataUrlMediaWallAddress: A similar URL reference to the Street View, but based on the property’s address.
    • streetViewServiceUrl: The base URL to Google Street View or similar services. Enables interactive visuals of the property’s surroundings.
    • livingArea: Total internal living area of the home, typically in square feet.
    • homeType: The category/type of the home.
    • lotSize: The size of the entire lot or land the home is situated on.
    • lotAreaValue: The numerical value representing the lot area is usually tied to a measurement unit.
    • lotAreaUnits: Units in which the lot area is measured (e.g., sqft, acres).
    • livingAreaValue: The numeric value of the property's interior living space.
    • livingAreaUnitsShort: Abbreviated unit for living area (e.g., sqft), useful for compact displays.
    • isUndisclosedAddress: Boolean indicating if the full property address is hidden, typically used for privacy reasons.
    • zestimate: Zillow’s estimated market value of the home, generated via its proprietary model.
    • rentZestimate: Zillow’s estimated rental price per month, is helpful for rental market analysis.
    • currency: Currency used for price, Zestimate, and rent estimate (e.g., USD).
    • hideZestimate: Indicates whether the Zestimate is hidden from public view.
    • dateSoldString: The date when the property was last sold, in string format (e.g., 2022-06-15).
    • taxAssessedValue: The most recent assessed value of the property for tax purposes.
    • taxAssessedYear: The year in which the property was last assessed.
    • country: The country where the property is located.
    • propertyTaxRate: The most recent tax rate.
    • photocount: This column provides a photo count of the property.
    • isPremierBuilder: Boolean indicating whether the builder is listed as a premier (trusted) builder on Zillow.
    • isZillowOwned: Indicates whether the property is owned or managed directly by Zillow.
    • ssid: A unique internal Zillow identifier for the listing (not to be confused with network SSID).
    • hdpUrl: URL to the home’s detail page on Zillow (Home Details Page).
    • tourViewCount: Number of times users have viewed the property tour.
    • hasPublicVideo: This
  5. F

    Median Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
    + more versions
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    (2025). Median Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/MSPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q1 2025 about sales, median, housing, and USA.

  6. R

    Real Estate Services Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Mar 3, 2025
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    Archive Market Research (2025). Real Estate Services Report [Dataset]. https://www.archivemarketresearch.com/reports/real-estate-services-48438
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    ppt, pdf, docAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global real estate services market is experiencing robust growth, driven by factors such as increasing urbanization, rising disposable incomes, and the growing popularity of online real estate platforms. The market, currently valued at approximately $5 trillion in 2025, is projected to expand at a compound annual growth rate (CAGR) of 7% from 2025 to 2033, reaching an estimated value of $9 trillion by 2033. This growth is fueled by both the residential and commercial sectors, with significant contributions from various service types, including trading and rental services. The increasing demand for professional real estate services, particularly in emerging markets, further contributes to this expansion. Technological advancements, such as the integration of artificial intelligence and big data analytics, are transforming the industry, leading to increased efficiency and improved customer experiences. Key players are adopting innovative strategies like virtual tours and property management software to cater to the evolving needs of clients. Segmentation analysis reveals a significant share held by the residential sector within the application segment, while trading services constitute a larger portion of the overall service type segment. North America and Asia-Pacific currently dominate the market, but emerging economies in regions like South America and Africa are showing promising growth potential. The market's growth, however, is not without its challenges. Regulatory changes, economic fluctuations, and the cyclical nature of the real estate market pose potential restraints. Despite these challenges, the overall outlook for the real estate services market remains positive, with consistent growth projected throughout the forecast period. The increasing adoption of technology and the growing demand for specialized services across diverse geographical areas continue to drive market expansion. The industry is undergoing a transformation, and companies are adapting their strategies to remain competitive in this dynamic landscape. Successful businesses are effectively leveraging data analytics, enhancing customer engagement, and building strategic partnerships to capitalize on emerging opportunities and maintain a robust market position.

  7. d

    Realtor.com Dataset | Property Listings | MLS Data | Real Estate Data |...

    • datarade.ai
    .json, .csv, .txt
    Updated Oct 4, 2023
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    CrawlBee (2023). Realtor.com Dataset | Property Listings | MLS Data | Real Estate Data | Residential Data | Realtime Real Estate Market Data [Dataset]. https://datarade.ai/data-products/crawlbee-realtor-com-dataset-property-listings-mls-dat-crawlbee
    Explore at:
    .json, .csv, .txtAvailable download formats
    Dataset updated
    Oct 4, 2023
    Dataset authored and provided by
    CrawlBee
    Area covered
    United States of America
    Description

    Our Realtor.com (Multiple Listing Service) dataset represents one of the most exhaustive collections of real estate data available to the industry. It consolidates data from over 500 MLS aggregators across various regions, providing an unparalleled view of the property market.

    Features:

    Property Listings: Each listing provides comprehensive details about a property. This includes its physical address, number of bedrooms and bathrooms, square footage, lot size, type of property (e.g., single-family home, condo, townhome), and more.

    Photographs and Virtual Tours: Visuals are crucial in the property market. Most listings are accompanied by high-quality photographs and, in many cases, virtual or 3D tours that allow potential buyers to explore properties remotely.

    Pricing Information: Listings provide asking prices, and the dataset frequently updates to reflect price changes. Historical price data, which includes initial listing prices and any subsequent reductions or increases, is also available.

    Transaction Histories: For sold properties, the dataset provides information about the date of sale, the sale price, and any discrepancies between the listing and sale prices.

    Agent and Broker Information: Each listing typically has associated details about the property's real estate professional. This might include their name, contact details, and affiliated brokerage.

    Open House Schedules: Open house dates and times are listed for properties that are actively being shown to potential buyers.

    1. Analytical Insights:

    Market Trends: By analyzing the dataset over time, one can glean insights into market dynamics, such as the rate of price appreciation or depreciation in certain areas, the average time properties stay on the market, and seasonality effects.

    Neighborhood Data: With comprehensive geographical data, it becomes possible to understand neighborhood-specific trends. This is invaluable for potential buyers or real estate investors looking to identify burgeoning markets.

    Price Comparisons: Realtors and potential buyers can benchmark properties against similar listings in the same area to determine if a property is priced appropriately.

    1. Utility:

    For Industry Professionals and Analysts: Beyond buyers and sellers, the dataset is a trove of information for real estate agents, brokers, analysts, and investors. They can harness this data to craft strategies, predict market movements, and serve their clients better.

  8. US National Property Listing Data | 50+ Property & Building Characteristics...

    • datarade.ai
    .csv, .xls, .txt
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    The Warren Group, US National Property Listing Data | 50+ Property & Building Characteristics | Pricing & Real Estate Agent Information [Dataset]. https://datarade.ai/data-products/us-national-property-listing-data-50-property-building-c-the-warren-group
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset authored and provided by
    The Warren Group
    Area covered
    United States of America
    Description

    Real estate is a dynamic and ever-evolving industry that relies heavily on data to make informed decisions. One of the fundamental aspects of this industry is real estate listing data. This data encompasses detailed information about properties that are available for sale or rent in a given market. It plays a pivotal role in assisting buyers, sellers, real estate professionals, and investors in making well-informed choices. In this data brief, we will provide an overview of what real estate listing data is and highlight five key industry use cases.

    Real Estate Listings Data Includes:

    • Property Location
    • 50+ Property and Building Characteristics
    • School District Information
    • List Date
    • Listing Price - Maximum, Minimum, Sold Price
    • Listing Status
    • Number of Days on Market
    • Listing Agent and Office
  9. d

    Real Estate Sales 2001-2022 GL

    • catalog.data.gov
    • data.ct.gov
    Updated Dec 20, 2024
    + more versions
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    data.ct.gov (2024). Real Estate Sales 2001-2022 GL [Dataset]. https://catalog.data.gov/dataset/real-estate-sales-2001-2018
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    Dataset updated
    Dec 20, 2024
    Dataset provided by
    data.ct.gov
    Description

    The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

  10. F

    Housing Inventory: Median Days on Market in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 10, 2025
    + more versions
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    (2025). Housing Inventory: Median Days on Market in the United States [Dataset]. https://fred.stlouisfed.org/series/MEDDAYONMARUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 10, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Housing Inventory: Median Days on Market in the United States (MEDDAYONMARUS) from Jul 2016 to Jun 2025 about median and USA.

  11. F

    American English Call Center Data for Realestate AI

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). American English Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-english-usa
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    United States
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    This US English Call Center Speech Dataset for the Real Estate industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for English -speaking Real Estate customers. With over 30 hours of unscripted, real-world audio, this dataset captures authentic conversations between customers and real estate agents ideal for building robust ASR models.

    Curated by FutureBeeAI, this dataset equips voice AI developers, real estate tech platforms, and NLP researchers with the data needed to create high-accuracy, production-ready models for property-focused use cases.

    Speech Data

    The dataset features 30 hours of dual-channel call center recordings between native US English speakers. Captured in realistic real estate consultation and support contexts, these conversations span a wide array of property-related topics from inquiries to investment advice offering deep domain coverage for AI model development.

    Participant Diversity:
    Speakers: 60 native US English speakers from our verified contributor community.
    Regions: Representing different provinces across United States of America to ensure accent and dialect variation.
    Participant Profile: Balanced gender mix (60% male, 40% female) and age range from 18 to 70.
    Recording Details:
    Conversation Nature: Naturally flowing, unscripted agent-customer discussions.
    Call Duration: Average 5–15 minutes per call.
    Audio Format: Stereo WAV, 16-bit, recorded at 8kHz and 16kHz.
    Recording Environment: Captured in noise-free and echo-free conditions.

    Topic Diversity

    This speech corpus includes both inbound and outbound calls, featuring positive, neutral, and negative outcomes across a wide range of real estate scenarios.

    Inbound Calls:
    Property Inquiries
    Rental Availability
    Renovation Consultation
    Property Features & Amenities
    Investment Property Evaluation
    Ownership History & Legal Info, and more
    Outbound Calls:
    New Listing Notifications
    Post-Purchase Follow-ups
    Property Recommendations
    Value Updates
    Customer Satisfaction Surveys, and others

    Such domain-rich variety ensures model generalization across common real estate support conversations.

    Transcription

    All recordings are accompanied by precise, manually verified transcriptions in JSON format.

    Transcription Includes:
    Speaker-Segmented Dialogues
    Time-coded Segments
    Non-speech Tags (e.g., background noise, pauses)
    High transcription accuracy with word error rate below 5% via dual-layer human review.

    These transcriptions streamline ASR and NLP development for English real estate voice applications.

    Metadata

    Detailed metadata accompanies each participant and conversation:

    Participant Metadata: ID, age, gender, location, accent, and dialect.
    Conversation Metadata: Topic, call type, sentiment, sample rate, and technical details.

    This enables smart filtering, dialect-focused model training, and structured dataset exploration.

    Usage and Applications

    This dataset is ideal for voice AI and NLP systems built for the real estate sector:

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  12. d

    Premium Residential | MLS Property Listing Data | USA Real Estate...

    • datarade.ai
    .json
    Updated Jun 7, 2025
    + more versions
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    REdistribute (2025). Premium Residential | MLS Property Listing Data | USA Real Estate Transaction Data | 750k+ On-Market Records [Dataset]. https://datarade.ai/data-products/premium-residential-access-redistribute-s-direct-source-mls-realchemy
    Explore at:
    .jsonAvailable download formats
    Dataset updated
    Jun 7, 2025
    Dataset authored and provided by
    REdistribute
    Area covered
    United States of America
    Description

    Unlock access to premium residential listing data, with a comprehensive set of fields designed to empower your business with deeper insights and the most up-to-date information.

    Key features: • Residential Data Type: Access to high-quality residential data to enhance your business analysis • Comprehensive Fields: A wide array of fields (800+) that offer a thorough view of residential property data • Fast & Fresh: Updated daily with data sourced directly from MLSs

    The sample data covers one listing in JSON format. For access to a broader set of sample listings (10,000+), reach out to the REdistribute sales contact.

    ABOUT REDISTRIBUTE

    REdistribute aims to modernize real estate data accessibility, fostering innovation and transparency through direct access to the most reliable MLS data. Our commitment to data integrity and direct MLS involvement guarantees the freshest, most accurate insights, empowering businesses across industries to drive innovation and make informed decisions.

  13. c

    Redfin properties dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 13, 2025
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    Crawl Feeds (2025). Redfin properties dataset [Dataset]. https://crawlfeeds.com/datasets/redfin-properties-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    Our dataset features comprehensive housing market data, extracted from 250,000 records sourced directly from Redfin USA. Our Crawl Feeds team utilized proprietary in-house tools to meticulously scrape and compile this valuable data.

    Key Benefits of Our Housing Market Data:

    • In-Depth Market Analysis: Gain insights into the real estate market with up-to-date data on recently sold properties.

    • Price Trend Identification: Track and analyze price trends across different cities.

    • Accurate Price Estimation: Estimate property values based on key factors such as area, number of beds and baths, square footage, and more.

    • Detailed Real Estate Statistics: Access detailed statistics segmented by zip code, area, and state.

    Unlock the Power of Redfin Data for Real Estate Professionals

    Leveraging our Redfin properties dataset allows real estate professionals to make data-driven decisions. With detailed insights into property listings, sales history, and pricing trends, agents and investors can identify opportunities in the market more effectively. The data is particularly useful for comparing neighborhood trends, understanding market demand, and making informed investment decisions.

    Enhance Your Real Estate Research with Custom Filters and Analysis

    Our Redfin dataset is not only extensive but also customizable, allowing users to apply filters based on specific criteria such as property type, listing status, and geographic location. This flexibility enables researchers and analysts to drill down into the data, uncovering patterns and insights that can guide strategic planning and market entry decisions. Whether you're tracking the performance of single-family homes or exploring multi-family property trends, this dataset offers the depth and accuracy needed for thorough analysis.

    Looking for deeper insights or a custom data pull from Redfin?
    Send a request with just one click and explore detailed property listings, price trends, and housing data.
    🔗 Request Redfin Real Estate Data

  14. T

    United States Existing Home Sales

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 22, 2025
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    TRADING ECONOMICS (2025). United States Existing Home Sales [Dataset]. https://tradingeconomics.com/united-states/existing-home-sales
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    May 22, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1968 - May 31, 2025
    Area covered
    United States
    Description

    Existing Home Sales in the United States increased to 4030 Thousand in May from 4000 Thousand in April of 2025. This dataset provides the latest reported value for - United States Existing Home Sales - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  15. F

    Rest of the World; Foreign Direct Investment in U.S. Real Estate Business...

    • fred.stlouisfed.org
    json
    Updated Jun 12, 2025
    + more versions
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    (2025). Rest of the World; Foreign Direct Investment in U.S. Real Estate Business (Market Value); Asset, Revaluation [Dataset]. https://fred.stlouisfed.org/series/BOGZ1FR265014003A
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 12, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Rest of the World; Foreign Direct Investment in U.S. Real Estate Business (Market Value); Asset, Revaluation (BOGZ1FR265014003A) from 1946 to 2024 about FDI, revaluation, real estate, assets, and USA.

  16. F

    Average Sales Price of Houses Sold for the United States

    • fred.stlouisfed.org
    json
    Updated Apr 23, 2025
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    (2025). Average Sales Price of Houses Sold for the United States [Dataset]. https://fred.stlouisfed.org/series/ASPUS
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 23, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Average Sales Price of Houses Sold for the United States (ASPUS) from Q1 1963 to Q1 2025 about sales, housing, and USA.

  17. Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North...

    • technavio.com
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    Technavio, Residential Real Estate Market Analysis, Size, and Forecast 2025-2029: North America (US, Canada, and Mexico), Europe (France, Germany, and UK), APAC (Australia, Japan, and South Korea), South America (Brazil), and Rest of World (ROW) [Dataset]. https://www.technavio.com/report/residential-real-estate-market-analysis
    Explore at:
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    Europe, Japan, United Kingdom, Mexico, Germany, Canada, United States, Global
    Description

    Snapshot img

    Residential Real Estate Market Size 2025-2029

    The residential real estate market size is forecast to increase by USD 485.2 billion at a CAGR of 4.5% between 2024 and 2029.

    The market is experiencing significant growth, fueled by increasing marketing initiatives that attract potential buyers and tenants. This trend is driven by the rising demand for housing solutions that cater to the evolving needs of consumers, particularly in urban areas. However, the market's growth trajectory is not without challenges. Regulatory uncertainty looms large, with changing policies and regulations posing a significant threat to market stability. Notably, innovative smart home technologies, such as voice-activated assistants and energy-efficient appliances, are gaining traction, offering enhanced convenience and sustainability for homeowners.
    As such, companies seeking to capitalize on the opportunities presented by the growing the market must navigate these challenges with agility and foresight. The residential construction industry's expansion is driven by urbanization and the rising standard of living in emerging economies, including India, China, Thailand, Malaysia, and Indonesia. By staying abreast of regulatory changes and implementing innovative marketing strategies, they can effectively meet the evolving needs of consumers and maintain a competitive edge. These regulatory shifts can impact everything from property prices to financing options, making it crucial for market players to stay informed and adapt quickly.
    

    What will be the Size of the Residential Real Estate Market during the forecast period?

    Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
    Request Free Sample

    In the dynamic housing market analysis, small flats continue to be a popular choice for both investors and first-time homebuyers, driven by affordability and urban growth. International investment in housing projects, including apartments and condominiums, remains strong, offering attractive investment returns. Real estate syndication and property management software facilitate efficient property ownership and management. Real estate loans, property insurance, and urban planning are essential components of the housing market, ensuring the development of affordable housing and addressing the needs of the middle class and upper middle class. Property disputes, property tax assessments, and real estate litigation are ongoing challenges, requiring careful attention from stakeholders.
    Property search engines streamline the process of finding the perfect property, from studio apartments to luxury homes. Real estate auctions, land banking, and nano apartments are innovative solutions in the market, while property flipping and short sales provide opportunities for savvy investors. Urban growth and community development are key trends, with a focus on sustainable, planned cities and the integration of technology, such as real estate blockchain, into the industry. Developers secure building permits, review inspection reports, and manage escrow accounts during real estate transactions. Key services include contract negotiation, dispute resolution, and tailored investment strategies for portfolio management. Financial aspects cover tax implications, estate planning, retirement planning, taxdeferred exchanges, capital gains, tax deductions, and maintaining positive cash flow for sustained returns.
    

    How is this Residential Real Estate Industry segmented?

    The residential real estate industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

    Mode Of Booking
    
      Sales
      Rental or lease
    
    
    Type
    
      Apartments and condominiums
      Landed houses and villas
    
    
    Location
    
      Urban
      Suburban
      Rural
    
    
    End-user
    
      Mid-range housing
      Affordable housing
      Luxury housing
    
    
    Geography
    
      North America
    
        US
        Canada
        Mexico
    
    
      Europe
    
        France
        Germany
        UK
    
    
      APAC
    
        Australia
        Japan
        South Korea
    
    
      South America
    
        Brazil
    
    
      Rest of World (ROW)
    

    By Mode Of Booking Insights

    The sales segment is estimated to witness significant growth during the forecast period. The sales segment dominates the global residential real estate market and will continue to dominate during the forecast period. The sales segment includes the sale of any property that is majorly used for residential purposes, such as single-family homes, condos, cooperatives, duplexes, townhouses, and multifamily residences. With the growing population and urbanization, the demand for homes is also increasing, which is the major factor driving the growth of the sales segment. Moreover, real estate firms work with developers to sel

  18. F

    US Spanish Call Center Data for Realestate AI

    • futurebeeai.com
    wav
    Updated Aug 1, 2022
    + more versions
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    FutureBee AI (2022). US Spanish Call Center Data for Realestate AI [Dataset]. https://www.futurebeeai.com/dataset/speech-dataset/realestate-call-center-conversation-spanish-usa
    Explore at:
    wavAvailable download formats
    Dataset updated
    Aug 1, 2022
    Dataset provided by
    FutureBeeAI
    Authors
    FutureBee AI
    License

    https://www.futurebeeai.com/policies/ai-data-license-agreementhttps://www.futurebeeai.com/policies/ai-data-license-agreement

    Area covered
    United States
    Dataset funded by
    FutureBeeAI
    Description

    Introduction

    This US Spanish Call Center Speech Dataset for the Real Estate industry is purpose-built to accelerate the development of speech recognition, spoken language understanding, and conversational AI systems tailored for Spanish -speaking Real Estate customers. With over 30 hours of unscripted, real-world audio, this dataset captures authentic conversations between customers and real estate agents ideal for building robust ASR models.

    Curated by FutureBeeAI, this dataset equips voice AI developers, real estate tech platforms, and NLP researchers with the data needed to create high-accuracy, production-ready models for property-focused use cases.

    Speech Data

    The dataset features 30 hours of dual-channel call center recordings between native US Spanish speakers. Captured in realistic real estate consultation and support contexts, these conversations span a wide array of property-related topics from inquiries to investment advice offering deep domain coverage for AI model development.

    Participant Diversity:
    Speakers: 60 native US Spanish speakers from our verified contributor community.
    Regions: Representing different provinces across USA to ensure accent and dialect variation.
    Participant Profile: Balanced gender mix (60% male, 40% female) and age range from 18 to 70.
    Recording Details:
    Conversation Nature: Naturally flowing, unscripted agent-customer discussions.
    Call Duration: Average 5–15 minutes per call.
    Audio Format: Stereo WAV, 16-bit, recorded at 8kHz and 16kHz.
    Recording Environment: Captured in noise-free and echo-free conditions.

    Topic Diversity

    This speech corpus includes both inbound and outbound calls, featuring positive, neutral, and negative outcomes across a wide range of real estate scenarios.

    Inbound Calls:
    Property Inquiries
    Rental Availability
    Renovation Consultation
    Property Features & Amenities
    Investment Property Evaluation
    Ownership History & Legal Info, and more
    Outbound Calls:
    New Listing Notifications
    Post-Purchase Follow-ups
    Property Recommendations
    Value Updates
    Customer Satisfaction Surveys, and others

    Such domain-rich variety ensures model generalization across common real estate support conversations.

    Transcription

    All recordings are accompanied by precise, manually verified transcriptions in JSON format.

    Transcription Includes:
    Speaker-Segmented Dialogues
    Time-coded Segments
    Non-speech Tags (e.g., background noise, pauses)
    High transcription accuracy with word error rate below 5% via dual-layer human review.

    These transcriptions streamline ASR and NLP development for Spanish real estate voice applications.

    Metadata

    Detailed metadata accompanies each participant and conversation:

    Participant Metadata: ID, age, gender, location, accent, and dialect.
    Conversation Metadata: Topic, call type, sentiment, sample rate, and technical details.

    This enables smart filtering, dialect-focused model training, and structured dataset exploration.

    Usage and Applications

    This dataset is ideal for voice AI and NLP systems built for the real estate sector:

  19. T

    United States Nahb Housing Market Index

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated Jun 17, 2025
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    TRADING ECONOMICS (2025). United States Nahb Housing Market Index [Dataset]. https://tradingeconomics.com/united-states/nahb-housing-market-index
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1985 - Jun 30, 2025
    Area covered
    United States
    Description

    Nahb Housing Market Index in the United States decreased to 32 points in June from 34 points in May of 2025. This dataset provides the latest reported value for - United States Nahb Housing Market Index - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. United States House Prices Growth

    • ceicdata.com
    Updated Nov 27, 2021
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    CEICdata.com (2021). United States House Prices Growth [Dataset]. https://www.ceicdata.com/en/indicator/united-states/house-prices-growth
    Explore at:
    Dataset updated
    Nov 27, 2021
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    United States
    Description

    Key information about House Prices Growth

    • US house prices grew 5.2% YoY in Dec 2024, following an increase of 5.4% YoY in the previous quarter.
    • YoY growth data is updated quarterly, available from Mar 1992 to Dec 2024, with an average growth rate of 5.4%.
    • House price data reached an all-time high of 17.7% in Sep 2021 and a record low of -12.4% in Dec 2008.

    CEIC calculates House Prices Growth from quarterly House Price Index. Federal Housing Finance Agency provides House Price Index with base January 1991=100.

Share
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Click to copy link
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AutoScraping, Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing & Market Insights [Dataset]. https://datarade.ai/data-products/autoscraping-s-zillow-usa-real-estate-data-10m-listings-wit-autoscraping

Autoscraping | Zillow USA Real Estate Data | 10M Listings with Pricing & Market Insights

Explore at:
.json, .csv, .xls, .sqlAvailable download formats
Dataset authored and provided by
AutoScraping
Area covered
United States
Description

Autoscraping's Zillow USA Real Estate Data is a comprehensive and meticulously curated dataset that covers over 10 million property listings across the United States. This data product is designed to meet the needs of professionals across various sectors, including real estate investment, market analysis, urban planning, and academic research. Our dataset is unique in its depth, accuracy, and timeliness, ensuring that users have access to the most relevant and actionable information available.

What Makes Our Data Unique? The uniqueness of our data lies in its extensive coverage and the precision of the information provided. Each property listing is enriched with detailed attributes, including but not limited to, full addresses, asking prices, property types, number of bedrooms and bathrooms, lot size, and Zillow’s proprietary value and rent estimates. This level of detail allows users to perform in-depth analyses, make informed decisions, and gain a competitive edge in their respective fields.

Furthermore, our data is continually updated to reflect the latest market conditions, ensuring that users always have access to current and accurate information. We prioritize data quality, and each entry is carefully validated to maintain a high standard of accuracy, making this dataset one of the most reliable on the market.

Data Sourcing: The data is sourced directly from Zillow, one of the most trusted names in the real estate industry. By leveraging Zillow’s extensive real estate database, Autoscraping ensures that users receive data that is not only comprehensive but also highly reliable. Our proprietary scraping technology ensures that data is extracted efficiently and without errors, preserving the integrity and accuracy of the original source. Additionally, we implement strict data processing and validation protocols to filter out any inconsistencies or outdated information, further enhancing the quality of the dataset.

Primary Use-Cases and Vertical Applications: Autoscraping's Zillow USA Real Estate Data is versatile and can be applied across a variety of use cases and industries:

Real Estate Investment: Investors can use this data to identify lucrative opportunities, analyze market trends, and compare property values across different regions. The detailed pricing and valuation data allow for comprehensive due diligence and risk assessment.

Market Analysis: Market researchers can leverage this dataset to track real estate trends, evaluate the performance of different property types, and assess the impact of economic factors on property values. The dataset’s nationwide coverage makes it ideal for both local and national market studies.

Urban Planning and Development: Urban planners and developers can use the data to identify growth areas, plan new developments, and assess the demand for different property types in various regions. The detailed location data is particularly valuable for site selection and zoning analysis.

Academic Research: Universities and research institutions can utilize this data for studies on housing markets, urbanization, and socioeconomic trends. The comprehensive nature of the dataset allows for a wide range of academic applications.

Integration with Our Broader Data Offering: Autoscraping's Zillow USA Real Estate Data is part of our broader data portfolio, which includes various datasets focused on real estate, market trends, and consumer behavior. This dataset can be seamlessly integrated with our other offerings to provide a more holistic view of the market. For example, combining this data with our consumer demographic datasets can offer insights into the relationship between property values and demographic trends.

By choosing Autoscraping's data products, you gain access to a suite of complementary datasets that can be tailored to meet your specific needs. Whether you’re looking to gain a comprehensive understanding of the real estate market, identify new investment opportunities, or conduct advanced research, our data offerings are designed to provide you with the insights you need.

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