24 datasets found
  1. d

    B2C Database

    • directdatasquad.com
    Updated Jul 9, 2025
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    (2025). B2C Database [Dataset]. https://directdatasquad.com/b2c-data/
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    Dataset updated
    Jul 9, 2025
    Description

    Our B2C database totals over 12 million consumer records. This database includes multi-faceted information that can be used for various campaigns. Records may vary depending on the lead generation source and purpose; however, all will come with at least contact information. In addition to this, homeowner status, insurance information, and appliance information are often collected.

  2. p

    Homeowners' Associations in United Kingdom - 79 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 24, 2025
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    Poidata.io (2025). Homeowners' Associations in United Kingdom - 79 Verified Listings Database [Dataset]. https://www.poidata.io/report/homeowners-association/united-kingdom
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    csv, json, excelAvailable download formats
    Dataset updated
    Jul 24, 2025
    Dataset provided by
    Poidata.io
    Area covered
    United Kingdom
    Description

    Comprehensive dataset of 79 Homeowners' associations in United Kingdom as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  3. s

    Home ownership

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Apr 7, 2025
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    Race Disparity Unit (2025). Home ownership [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/housing/owning-and-renting/home-ownership/latest
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    csv(58 KB)Available download formats
    Dataset updated
    Apr 7, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    70% of White British households owned their own homes – the highest percentage out of all ethnic groups.

  4. Share of homeowners in England 2024, by age

    • statista.com
    • ai-chatbox.pro
    Updated Mar 6, 2025
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    Statista (2025). Share of homeowners in England 2024, by age [Dataset]. https://www.statista.com/statistics/321065/uk-england-home-owners-age-groups/
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    Dataset updated
    Mar 6, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2023 - Mar 2024
    Area covered
    England, United Kingdom
    Description

    About 36 percent of homeowners in England were aged 65 and above, which contrasts sharply with younger age groups, particularly those under 35. Young adults between 25 and 35, made up 15 percent of homeowners and had a dramatically lower homeownership rate. The disparity highlights the growing challenges faced by younger generations in entering the property market, a trend that has significant implications for wealth distribution and social mobility. Barriers to homeownership for young adults The path to homeownership has become increasingly difficult for young adults in the UK. A 2023 survey revealed that mortgage affordability was the greatest obstacle to property purchase. This represents a 39 percent increase from 2021, reflecting the impact of rising house prices and mortgage rates. Despite these challenges, one in three young adults still aspire to get on the property ladder as soon as possible, though many have put their plans on hold. The need for additional financial support from family, friends, and lenders has become more prevalent, with one in five young adults acknowledging this necessity. Regional disparities and housing supply The housing market in England faces regional challenges, with North West England and the West Midlands experiencing the largest mismatch between housing supply and demand in 2023. This imbalance is evident in the discrepancy between new homes added to the housing stock and the number of new households formed. London, despite showing signs of housing shortage, has seen the largest difference between homes built and households formed. The construction of new homes has been volatile, with a significant drop in 2020, a rebound in 2021 and a gradual decline until 2024.

  5. T

    United Kingdom Home Ownership Rate

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, United Kingdom Home Ownership Rate [Dataset]. https://tradingeconomics.com/united-kingdom/home-ownership-rate
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    xml, csv, excel, jsonAvailable download formats
    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
    Dec 31, 2005 - Dec 31, 2023
    Area covered
    United Kingdom
    Description

    Home Ownership Rate in the United Kingdom decreased to 64.50 percent in 2023 from 64.70 percent in 2022. This dataset provides the latest reported value for - United Kingdom Home Ownership Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  6. Homeowner distribution in England 2024, by home financing and age

    • statista.com
    Updated Mar 5, 2025
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    Statista (2025). Homeowner distribution in England 2024, by home financing and age [Dataset]. https://www.statista.com/statistics/321097/distribution-of-home-owners-in-england-uk-by-type-of-home-financing-and-age/
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    Dataset updated
    Mar 5, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 2023 - Mar 2024
    Area covered
    England, United Kingdom
    Description

    The distribution of all owner-occupier households in England in 2024 varied per age group, as well as the type of home financing. The older the age group, the larger the share of owner-occupier homeowners who purchased their home outright. A share of 2.1 percent of own outright homeowners were between the ages of 25 to 34, whereas a share of 62.1 percent of own outright homeowners were aged 65 and over. Although this is the case, the largest share of homeowners who purchased their house with a mortgage was in the age range of 35 to 44 years old.

  7. Data from: Stakeholder Workshop on Encouraging Energy Retrofit among UK...

    • beta.ukdataservice.ac.uk
    Updated 2021
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    Yekatherina Bobrova (2021). Stakeholder Workshop on Encouraging Energy Retrofit among UK Homeowners, 2021 [Dataset]. http://doi.org/10.5255/ukda-sn-855219
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    Dataset updated
    2021
    Dataset provided by
    UK Data Servicehttps://ukdataservice.ac.uk/
    DataCitehttps://www.datacite.org/
    Authors
    Yekatherina Bobrova
    Area covered
    United Kingdom
    Description

    The Fast-tracking Low-Energy Use via Retrofit (FLEUR) project is based on a recent UCL-led research project on the adoption process of low-carbon home retrofit among UK homeowners, which made use of realistic psychological models of household decision-making regarding domestic energy retrofit. Out of this work came several novel insights that the FLEUR project aimed to translate into plausible policy suggestions for impact in the real world, in order to help the UK housing sector to reach net zero carbon targets by 2050. This aim of the FLEUR project was met through a project workshop with various stakeholders interested to advance low-energy retrofit in the UK, such as demand and supply side actors in energy retrofit industry, governmental actors, intermediary organisations that operate to advance change towards sustainability and academics that specialise in low-carbon home retrofit. The workshop was successfully carried out on 25th May 2021 with 36 participants. It provided the opportunity to discuss, validate and enrich the research-based insights, as well as reach out to and communicate research findings to relevant beneficiaries (workshop stakeholders). The workshop participants were encouraged to think about the familiar topic of domestic energy retrofit from a novel perspective with the intend to internalise research findings and integrate them, where possible, in their organisational activities. The data related to the project workshop is deposited here. The collected data include: - A record of answers to open ended questions in the pre-workshop survey - 10 transcripts of breakout sessions in 10 Zoom break out rooms. - One transcript for the plenary session. - A record of the workshop chat, which took place via Zoom

  8. Likelihood of home buyers considering a green home in the UK 2022

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Likelihood of home buyers considering a green home in the UK 2022 [Dataset]. https://www.statista.com/statistics/1339711/likelihood-of-uk-home-buyers-to-consider-green-homes/
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United Kingdom
    Description

    About ** percent of first-time and ** percent of second-time buyers were likely to consider a green home in the United Kingdom in 2022. A small share of both groups was unlikely to consider a green home: *** percent were second-time and **** percent were first-time buyers. The most important reason for home buyers purchasing a green home was the homes being better for the environment.

  9. m

    Homeownership rate in the UK

    • data.mendeley.com
    Updated Jun 27, 2025
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    Jalal Siddiki (2025). Homeownership rate in the UK [Dataset]. http://doi.org/10.17632/yx7gpntzwn.3
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    Dataset updated
    Jun 27, 2025
    Authors
    Jalal Siddiki
    License

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

    Area covered
    United Kingdom
    Description

    These data files are used for the empirical analyses of the article entitled "Homeownership in the UK: The Role of Wealth Inequality and Family Life Cycles" Updated 26 June 2025

  10. Homeowners Insurance Market Analysis North America, Europe, APAC, South...

    • technavio.com
    Updated Jul 15, 2024
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    Technavio (2024). Homeowners Insurance Market Analysis North America, Europe, APAC, South America, Middle East and Africa - US, Japan, UK, China, Germany - Size and Forecast 2024-2028 [Dataset]. https://www.technavio.com/report/homeowners-insurance-market-analysis
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    Dataset updated
    Jul 15, 2024
    Dataset provided by
    TechNavio
    Authors
    Technavio
    Time period covered
    2021 - 2025
    Area covered
    China, Japan, United States, Germany, United Kingdom, Global
    Description

    Snapshot img

    Homeowners Insurance Market Size 2024-2028

    The homeowners insurance market size is forecast to increase by USD 65.9 billion at a CAGR of 4.6% between 2023 and 2028.

    The market is experiencing significant growth due to several key factors. The increasing number of natural disasters and man-made hazards has led to a higher demand for comprehensive insurance coverage. New technological developments In the home insurance industry, such as the use of drones for property inspections and smart home systems for risk mitigation, are transforming the market. Additionally, the vulnerability to cybercrimes, including identity theft and hacking, is driving insurers to offer cyber insurance policies as part of their homeowners packages. These trends are shaping the future of the market and are expected to continue influencing its growth.
    

    What will be the Size of the Homeowners Insurance Market During the Forecast Period?

    Request Free Sample

    The market is a significant segment of the global casualty insurance sector, providing financial protection for homeowners against various risks. Homeowners, as key asset holders, rely on insurance companies to safeguard their financial security against potential losses from incidents such as natural disasters, theft, and property damage. Insurers employ advanced risk assessment tools to evaluate and price policies based on factors like location, property values, and historical claims data. Recent market trends include increasing concerns over catastrophic risks, driven by both natural disasters and pandemic-related losses. The low-interest-rate environment has also influenced the market, affecting loss reserves and policyholder surplus.
    Moreover, insurance companies continue to navigate the challenges posed by financial market losses and the legal responsibility to policyholders for covered damages. Asset prices and loss reserves remain crucial indicators of market stability, with property insurance and household/private property insurance being the primary types of coverage sought by homeowners.
    

    How is this Homeowners Insurance Industry segmented and which is the largest segment?

    The homeowners insurance industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

    Type
    
      Fire and theft
      House damage
      Floods and earthquake
      Others
    
    
    Source
    
      Captive
      Independent agent
      Direct response
    
    
    Geography
    
      North America
    
        US
    
    
      Europe
    
        Germany
        UK
    
    
      APAC
    
        China
        Japan
    
    
      South America
    
    
    
      Middle East and Africa
    

    By Type Insights

    The fire and theft segment is estimated to witness significant growth during the forecast period.
    

    The market growth is driven by the increasing prevalence of natural disasters and theft incidents, leading homeowners to seek additional coverage beyond standard property insurance policies. Fire insurance, a significant segment, protects against losses caused by fire, with many homeowners opting for additional coverage to offset costs exceeding their base policy limits. Policies exclude certain perils, such as war and nuclear risks. Theft insurance, another essential component, safeguards against financial losses resulting from theft or vandalism. Advanced risk assessment tools enable insurance firms to customize policies based on clients' risk profiles and underwriting guidelines, offering premium payment flexibility and virtual interactions.

    Get a glance at the Homeowners Insurance Industry report of share of various segments Request Free Sample

    The fire and theft segment was valued at USD 80.90 billion in 2018 and showed a gradual increase during the forecast period.

    Regional Analysis

    North America is estimated to contribute 40% to the growth of the global market during the forecast period.
    

    Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

    For more insights on the market share of various regions, Request Free Sample

    The North American market will experience steady growth due to the high frequency of natural disasters, leading to an increased demand for reinsurance policies. Catastrophic events, such as hurricanes, tornados, and tsunamis, can cause significant damage to residential properties, resulting in substantial insurance claims. Reinsurers provide capital to primary insurers when the number of claims is high, ensuring financial security for policyholders. Despite the challenges, reinsurance firms have managed to maintain consistent revenue streams. Property values, homeowners, assets, and liability coverage are integral components of homeowners insurance policies. Insurance providers offer customized policies for various risks, including natural disasters,

  11. Private registered provider social housing stock and rents in England 2022...

    • gov.uk
    Updated Aug 21, 2024
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    Regulator of Social Housing (2024). Private registered provider social housing stock and rents in England 2022 to 2023 [Dataset]. https://www.gov.uk/government/statistics/private-registered-provider-social-housing-stock-and-rents-in-england-2022-to-2023
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    Dataset updated
    Aug 21, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Regulator of Social Housing
    Area covered
    England
    Description

    This statistical release presents the National Statistics on the stock owned and managed by private registered providers in England in 2022/23. Based on data from the Regulator of Social Housing’s Statistical Data Return, it provides details of private registered providers’ owned and managed stock, details rents reported for low cost rental stock (social and Affordable Rents) and provides an overview of the private registered providers’ sector including details of stock movement and vacancies.

    The release comprises three briefing notes (stock, rents and sector characteristics), four dynamic look-up tools (Excel based) allowing users to view the underlying data at a PRP and Group PRP level, a range of geographies and also view five-year trend information at a range of geographies. Additional data tables, raw data from the SDR and technical documentation is also provided.

    The statistics derived from the SDR data and published as private registered provider social housing stock in England are considered by the United Kingdom Statistics Authority’s regulatory arm – the Office for Statistics Regulation – to have met the highest standards of trustworthiness, quality and public value, and are considered a national statistic. For more information see the data quality and methodology note.

    The responsible statistician for this statistical release was Amanda Hall. The lead official was Will Perry.

    These statistics are based on data from the SDR. This return collects data on stock size, types, location and rents at 31 March each year, and data on sales and acquisitions made between 1 April and 31 March. All private registered providers of social housing in England are required to complete the SDR, with those providers who own fewer than 1,000 units completing a shorter, less detailed return.

    Statistical queries on this publication should be directed to the Referrals and Regulatory Enquiries team on 0300 124 5225 or mail enquiries@rsh.gov.uk.

    Users are encouraged to provide comments and feedback on how these statistics are used and how they meet their needs either through our feedback rating icons on all published documents or through direct email contact (please send these entitled “PRP statistics feedback” to enquiries@rsh.gov.uk.

    Previous releases of these statistics are available on the Private registered provider social housing stock in England collections page.

    An accessible HTML summary of the key findings from the report has been included on this page. If you require any further information, please contact enquiries@rsh.gov.uk.

  12. Mortgage Rescue Scheme monitoring statistics: September 2010

    • gov.uk
    Updated Nov 11, 2010
    + more versions
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    Ministry of Housing, Communities & Local Government (2018 to 2021) (2010). Mortgage Rescue Scheme monitoring statistics: September 2010 [Dataset]. https://www.gov.uk/government/statistics/mortgage-rescue-scheme-monitoring-statistics-september-2010
    Explore at:
    Dataset updated
    Nov 11, 2010
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities & Local Government (2018 to 2021)
    Description

    The Mortgage Rescue Scheme monitoring statistics ‘housing live table’ gives information on the number of households approaching local authorities with mortgage difficulties and applications and acceptances for the scheme.

    The scheme has 2 elements:

    • the ‘Government Mortgage to Rent’ option which involves a RSL purchasing the homeowner’s property, enabling the household to remain in the property as a tenant on an assured short hold tenancy, paying an intermediate rent
    • the ‘Shared Equity’ option which involves a RSL providing a loan to the homeowner to enable the homeowner’s monthly mortgage payments to be reduced.

    The figures, presented by Government Office Region, are derived from Mortgage Rescue Scheme returns submitted to Communities and Local Government by local authorities, the fast-track case management system, Shelter monitoring returns and Homes and Communities Agency (HCA) management information.

    Local authority figures do not contain estimates for missing returns. Information on the local authority response rate is provided alongside the reported figures for each period.

    The fast-track team which was launched in September 2009 to centrally take referrals directly from lenders and process them through to completion, ceased taking new referrals at the end of June 2010 and closed on 31 August 2010, with all ongoing cases passed to Shelter for action. Up to and including Q2 2010 all figures on fast-track cases and completions come from the fast-track case management system.

    From Q3 2010 onwards Shelter monitoring returns have been used to provide figures on live former fast-track cases where they are carrying out the initial assessment and HCA management information has been used to provide figures on live cases referred to RSLs or with an offer from an RSL as at the end of the quarter and the number of households that have accepted an offer through the scheme during the quarter. There will therefore be a discontinuity in the fast-track figures from Q3 2010 onwards.

    Figures for different periods are shown on separate tabs in the workbook. The figures undergo validation and cross checking overseen by DCLG statisticians and are reconciled with HCA management information on the number of households that have accepted an offer through the scheme.

    The Mortgage Rescue Scheme monitoring statistics are released quarterly on the same day as statistical publications on repossessions produced by the Ministry of Justice and the Council of Mortgage Lenders.

    These figures have been pre-released in accordance with the Pre-release Access Order and the pre release access list can be found in the Downloads below.

    Responsible Statistician: Laurie Thompson

    **Public enquiries: ** mortgagerescue@communities.gsi.gov.uk

    Press Enquiries: Office hours: 0303 444 1136 Out of hours: 0303 444 1201 Press.office@communities.gsi.gov.uk

  13. s

    Age of first-time buyers

    • ethnicity-facts-figures.service.gov.uk
    csv
    Updated Apr 7, 2025
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    Race Disparity Unit (2025). Age of first-time buyers [Dataset]. https://www.ethnicity-facts-figures.service.gov.uk/housing/owning-and-renting/age-of-first-time-buyers/latest
    Explore at:
    csv(17 KB)Available download formats
    Dataset updated
    Apr 7, 2025
    Dataset authored and provided by
    Race Disparity Unit
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Area covered
    England
    Description

    In the 2 years to March 2023, the average age of first-time buyers was 32 years old.

  14. Mortgage Rescue Scheme monitoring statistics: March 2011

    • gov.uk
    Updated May 12, 2011
    + more versions
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    Ministry of Housing, Communities & Local Government (2018 to 2021) (2011). Mortgage Rescue Scheme monitoring statistics: March 2011 [Dataset]. https://www.gov.uk/government/statistics/mortgage-rescue-scheme-monitoring-statistics-march-2011
    Explore at:
    Dataset updated
    May 12, 2011
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    Ministry of Housing, Communities & Local Government (2018 to 2021)
    Description

    This is the final publication of Mortgage Rescue Scheme monitoring statistics as reported by local authorities.

    The Mortgage Rescue Scheme monitoring statistics ‘housing live table’ gives information on the number of households that approached local authorities with mortgage difficulties and applications and acceptances for the scheme.

    The scheme had two elements:

    1. the ‘Government Mortgage to Rent’ option which involved a registered social landlord purchasing the homeowner’s property, enabling the household to remain in the property as a tenant on an assured short hold tenancy, paying an intermediate rent
    2. the ‘Shared Equity’ option which involved a registered social landlord providing a loan to the homeowner to enable the homeowner’s monthly mortgage payments to be reduced.

    The figures, presented by Government Office Region, are derived from Mortgage Rescue Scheme returns submitted to Communities and Local Government by local authorities, the fast-track case management system, Shelter monitoring returns and Homes and Communities Agency management information.

    Local authority figures do not contain estimates for missing returns. Information on the local authority response rate is provided alongside the reported figures for each period.

    The fast-track team which was launched in September 2009 to centrally take referrals directly from lenders and process them through to completion, ceased taking new referrals at the end of June 2010 and closed on 31 August 2010, with all ongoing cases passed to Shelter for action. Up to and including Q2 2010 all figures on fast-track cases and completions come from the fast-track case management system. From Q3 2010 onwards Shelter monitoring returns have been used to provide figures on live former fast-track cases where they are carrying out the initial assessment and Homes and Communities Agency management information has been used to provide figures on live cases referred to registered social landlords or with an offer from a registered social landlord as at the end of the quarter and the number of households that have accepted an offer through the scheme during the quarter. There will therefore be a discontinuity in the fast-track figures from Q3 2010 onwards.

    Figures for different periods are shown on separate tabs in the workbook. The figures undergo validation and cross checking overseen by DCLG statisticians and are reconciled with Homes and Communities Agency management information on the number of households that have accepted an offer through the scheme.

    These figures have been pre-released in accordance with the Pre-release Access Order and the pre release access list can be found in the Downloads below.

    Changes to the scheme from April mean that DCLG will no longer need to collect detailed data from Local authorities on live Mortgage Rescue Scheme cases and completions to manage the pipeline.

    The department will continue to collect a small amount of quarterly data on households approaching authorities with mortgage difficulties to ensure that the positive impact of Mortgage Rescue Scheme in encouraging households to come forward for money advice can be monitored and evidenced. The Homes and Communities Agency will continue to collect monitoring information from Mortgage Rescue Scheme providers on live cases and completions of cases currently in the pipeline and under the new scheme. Details of these changes have been published in the housing and homelessness annex of the draft statistics plan which is out for consultation until the 3rd June 2011, see related publications below.

    Responsible Statistician: Laurie Thompson

    **Public enquiries: ** mortgagerescue@communities.gsi.gov.uk

    Press Enquiries: Office hours: 0303 444 1136 Out of hours: 0303 444 1201 Press.office@communities.gsi.gov.uk

  15. d

    Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No...

    • datarade.ai
    Updated Nov 7, 2023
    + more versions
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    APISCRAPY (2023). Zillow Real Estate Data Extraction | Real-time Real Estate Market Data | No Infra Cost | Pre-built AI & Automation | 50% Cost Saving | Free Sample [Dataset]. https://datarade.ai/data-products/zillow-real-estate-data-extraction-real-time-real-estate-ma-apiscrapy
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Nov 7, 2023
    Dataset authored and provided by
    APISCRAPY
    Area covered
    Iceland, Bulgaria, Canada, Belgium, Croatia, Spain, Portugal, Liechtenstein, Isle of Man, Albania
    Description

    Note:- Only publicly available data can be worked upon

    APISCRAPY collects and organizes data from Zillow's massive database, whether it's property characteristics, market trends, pricing histories, or more. Because of APISCRAPY's first-rate data extraction services, tracking property values, examining neighborhood trends, and monitoring housing market variations become a straightforward and efficient process.

    APISCRAPY's Zillow real estate data scraping service offers numerous advantages for individuals and businesses seeking valuable insights into the real estate market. Here are key benefits associated with their advanced data extraction technology:

    1. Real-time Zillow Real Estate Data: Users can access real-time data from Zillow, providing timely updates on property listings, market dynamics, and other critical factors. This real-time information is invaluable for making informed decisions in a fast-paced real estate environment.

    2. Data Customization: APISCRAPY allows users to customize the data extraction process, tailoring it to their specific needs. This flexibility ensures that the extracted Zillow real estate data aligns precisely with the user's requirements.

    3. Precision and Accuracy: The advanced algorithms utilized by APISCRAPY enhance the precision and accuracy of the extracted Zillow real estate data. This reliability is crucial for making well-informed decisions related to property investments and market trends.

    4. Efficient Data Extraction: APISCRAPY's technology streamlines the data extraction process, saving users time and effort. The efficiency of the extraction workflow ensures that users can access the desired Zillow real estate data without unnecessary delays.

    5. User-friendly Interface: APISCRAPY provides a user-friendly interface, making it accessible for individuals and businesses to navigate and utilize the Zillow real estate data scraping service with ease.

    APISCRAPY provides real-time real estate market data drawn from Zillow, ensuring that consumers have access to the most up-to-date and comprehensive real estate insights available. Our real-time real estate market data services aren't simply a game changer in today's dynamic real estate landscape; they're an absolute requirement.

    Our dedication to offering high-quality real estate data extraction services is based on the utilization of Zillow Real Estate Data. APISCRAPY's integration of Zillow Real Estate Data sets it different from the competition, whether you're a seasoned real estate professional or a homeowner wanting to sell, buy, or invest.

    APISCRAPY's data extraction is a key element, and it is an automated and smooth procedure that is at the heart of the platform's operation. Our platform gathers Zillow real estate data quickly and offers it in an easily consumable format with the click of a button.

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  16. d

    HECM Single Family Portfolio Snapshot.

    • datadiscoverystudio.org
    • gimi9.com
    • +3more
    Updated Mar 15, 2015
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    (2015). HECM Single Family Portfolio Snapshot. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/b3df1e4365e849d7ae6c7ea74828a31d/html
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    Dataset updated
    Mar 15, 2015
    Description

    description: The Federal Housing Administration's HECM program is the only government-insured reverse mortgage program. The HECM program guarantees that the lender will meet its payment obligations to the homeowner, limits the borrower's loan origination costs, and insures full repayment of the loan balance to the lender up to the maximum claim amount. The loan amount is based on borrower age, home value, and current interest rates. The HECM data files provide loan-level records that will enable interested parties to explore issues regarding downpayment assistance provided to homebuyers utilizing HECM insured mortgage financing.; abstract: The Federal Housing Administration's HECM program is the only government-insured reverse mortgage program. The HECM program guarantees that the lender will meet its payment obligations to the homeowner, limits the borrower's loan origination costs, and insures full repayment of the loan balance to the lender up to the maximum claim amount. The loan amount is based on borrower age, home value, and current interest rates. The HECM data files provide loan-level records that will enable interested parties to explore issues regarding downpayment assistance provided to homebuyers utilizing HECM insured mortgage financing.

  17. Major features updated in kitchens in the United Kingdom (UK) 2024/2025

    • statista.com
    Updated Dec 18, 2024
    + more versions
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    Statista Research Department (2024). Major features updated in kitchens in the United Kingdom (UK) 2024/2025 [Dataset]. https://www.statista.com/topics/6389/diy-and-home-improvement-market-in-the-uk/
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    Dataset updated
    Dec 18, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    United Kingdom
    Description

    Between 2024 and 2025, in the United Kingdom (UK) the top features replaced or added during kitchen upgrades were worktops and sinks. According to a survey conducted with UK homeowners, a further 91 percent upgraded their kitchen cabinets as well.

  18. Smart home device ownership in the UK 2025

    • statista.com
    Updated Jun 27, 2025
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    Statista (2025). Smart home device ownership in the UK 2025 [Dataset]. https://www.statista.com/forecasts/997845/smart-home-device-ownership-in-the-uk
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2024 - Jun 2025
    Area covered
    United Kingdom
    Description

    When asked about "Smart home device ownership", 38 percent of UK respondents answer "Building safety / security (e.g., connected smoke detectors / cameras)". This online survey was conducted in 2025, among 5,452 consumers.

  19. T

    HOME OWNERSHIP RATE by Country in EUROPE

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
    + more versions
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    TRADING ECONOMICS (2017). HOME OWNERSHIP RATE by Country in EUROPE [Dataset]. https://tradingeconomics.com/country-list/home-ownership-rate?continent=europe
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    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    May 29, 2017
    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
    2025
    Area covered
    Europe
    Description

    This dataset provides values for HOME OWNERSHIP RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  20. Glazing in the UK - Market Research Report (2015-2030)

    • ibisworld.com
    Updated Aug 25, 2024
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    IBISWorld (2024). Glazing in the UK - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-kingdom/market-research-reports/glazing-industry/
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    Dataset updated
    Aug 25, 2024
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2014 - 2029
    Area covered
    United Kingdom
    Description

    Revenue is forecast to edge up at a compound annual rate of 0.1% over the five years through 2024-25 to £1.7 billion. The glazing industry’s revenue prospects tend to follow economic and investment trends in the wider construction sector. The pandemic led to a 14.3% plummet in construction activity in 2020 due to lockdowns, as per ONS data, significantly affecting glazing contractors, especially in the residential and commercial sectors. Despite construction activity recovering post-pandemic, output has been sluggish amid weak economic conditions and inflationary pressures, limiting glazers’ revenue growth. Following the pandemic, the glazing industry was hit with severe supply chain disruptions caused by the Russia-Ukraine conflict. Global supply issues caused input purchase costs to inflate as well as dampen consumer and business confidence. Persistent inflationary pressures have severely impacted budgets, leading to the cancellation or postponement of several commercial construction projects amid escalating costs. Homeowners are also feeling the pinch, tightening their purse strings and consequently reducing the demand for glass installation upgrades. To combat inflation, the Bank of England raised interest rates, increasing borrowing costs, which slowed housing activity. This led to reduced homeowner equity and fewer investment opportunities for commercial clients, thereby limiting tender opportunities for glazers. However, supportive government schemes, which stimulate construction activity in residential and non-residential markets, have bolstered industry revenue growth. In 2024-25, revenue is forecast to climb by 4.3%, as inflationary pressures ease and consumer and business confidence rebounds. Revenue is forecast to expand at a compound annual rate of 4.4% over the five years through 2029-30 to £2.1 billion. The government will continue to support new residential construction, aiding glazing contractors through the increased demand for their services. An economic recovery will also uplift commercial construction, as easing inflation facilitates spending and makes construction projects more attractive. Additionally, growing eco-consciousness will drive demand for energy-saving and sustainable glass installations, as homeowners and commercial clients seek to enhance the energy efficiency of their buildings.

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(2025). B2C Database [Dataset]. https://directdatasquad.com/b2c-data/

B2C Database

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9 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 9, 2025
Description

Our B2C database totals over 12 million consumer records. This database includes multi-faceted information that can be used for various campaigns. Records may vary depending on the lead generation source and purpose; however, all will come with at least contact information. In addition to this, homeowner status, insurance information, and appliance information are often collected.

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