Housing Market Insights

Housing Market Insights
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At Nomad Data we help you find the right dataset to address these types of needs and more. Sign up today and describe your business use case and you'll be connected with data vendors from our nearly 3000 partners who can address your exact need.


The housing market and home improvement sector have always been dynamic areas of interest for investors, homeowners, and industry professionals alike. Historically, gaining insights into these areas was a challenge, with reliance on antiquated methods such as manual surveys, word-of-mouth information, and limited public records. Before the digital age, understanding trends in new homes, renovations, and home furnishing demand involved piecing together fragmented information, often leading to delayed and less accurate decision-making.

Before the advent of modern data collection methods, stakeholders had to wait weeks or even months to understand changes in the housing market. This delay in information could lead to missed opportunities or misguided investments. The older types of data people used included printed sales listings, local government records on new construction permits, and rudimentary sales reports from furniture and home improvement retailers.

However, the proliferation of sensors, the internet, and connected devices, along with the widespread adoption of software in various processes, has revolutionized data collection and analysis. The sudden move toward storing every event in databases has made it easier to track and understand the housing market in real-time. This digital transformation has provided stakeholders with the ability to make more informed decisions quickly.

The importance of data in understanding the housing market cannot be overstated. With the advent of detailed real estate and risk data, professionals can now track sales, inventory, and leading indicators with unprecedented precision. This shift towards data-driven insights has illuminated previously dark corners of the market, allowing for real-time adjustments and strategic planning.

Let's delve into how specific categories of datasets can provide better insights into the housing market and home improvement sector, focusing on the types of data that can help business professionals better understand sales, inventory, leading indicators, and more.

Risk Data

Understanding Construction Trends through Risk Data

Risk data has become an invaluable resource for tracking construction trends, including new constructions and remodels. With the nation's largest database of construction permits, risk data providers offer insights at a state or zip code level, categorizing data by residential or non-residential new construction, remodels, electrical, HVAC, pool, roof, solar, and battery packs, among others.

History and Evolution: The collection of risk data has evolved significantly with technology advances. Initially, construction permits and related data were collected manually from local government offices. However, the digitalization of records and the development of sophisticated data aggregation tools have streamlined this process, making it possible to access and analyze data more efficiently.

Examples of Risk Data: Examples include detailed records of construction permits, categorized by job type such as new construction, remodels, and additions. This data is crucial for understanding where and what type of construction activities are taking place, which in turn, provides insights into housing market trends.

Roles and Industries: Risk data is particularly useful for investors, real estate developers, contractors, and market researchers. These stakeholders use the data to identify market trends, assess risks, and make informed decisions regarding property investments and development projects.

Accelerating Data Volume: The volume of risk data is accelerating, thanks to the continuous digitalization of records and the increasing number of construction projects. This growth in data volume offers more granular insights into construction trends, enabling more precise market analysis.

Specific Uses: Risk data can be used to:

  • Track construction trends at a local or national level.
  • Identify emerging markets for new homes and renovations.
  • Assess risk associated with specific types of construction projects.
  • Forecast demand for home furnishing and improvement products.

Real Estate Data

Gaining Insights into Home Sales and Market Dynamics

Real estate data providers offer comprehensive insights into new construction home sales, property characteristics, sales, listings, and more. This data is crucial for understanding the dynamics of the housing market, including sales prices, physical characteristics of properties, and neighborhood trends.

History and Evolution: The collection and analysis of real estate data have transformed with the advent of online listings, digital property records, and advanced analytics platforms. This evolution has made it possible to access up-to-date information on home sales, listings, and property characteristics across the US.

Examples of Real Estate Data: Examples include data on new construction home sales, property characteristics (e.g., beds, baths, square footage), and building permits classified into various job types. This data provides a comprehensive view of the housing market, enabling stakeholders to make informed decisions.

Roles and Industries: Real estate data is essential for real estate agents, developers, investors, and market researchers. These professionals rely on accurate and timely data to track market trends, evaluate property values, and identify investment opportunities.

Accelerating Data Volume: The volume of real estate data is growing rapidly, driven by the increasing number of transactions and the digitalization of property records. This growth enables more detailed and accurate market analysis.

Specific Uses: Real estate data can be used to:

  • Analyze market trends and property values.
  • Identify investment opportunities in new constructions and renovations.
  • Evaluate neighborhood and community dynamics, including school data.
  • Forecast demand for housing and home improvement products.


The importance of data in understanding the housing market and home improvement sector cannot be overstated. Access to risk and real estate data has revolutionized how business professionals track sales, inventory, and leading indicators. This data-driven approach enables stakeholders to make informed decisions in real-time, adapting to market changes with agility.

As organizations become more data-driven, the discovery and utilization of relevant data will be critical to staying competitive. The ability to monetize useful data, created over decades, opens new avenues for insights into the housing market. Future advancements in data collection and analysis, including the potential use of AI, promise to unlock even more value from existing and new data sources.

The housing market and home improvement sector are prime examples of how data can transform industries, providing clarity and direction in an otherwise complex landscape. As we look to the future, the continued evolution of data collection and analysis methods will undoubtedly provide even deeper insights into these vital areas of the economy.


Industries and roles that benefit from housing market and home improvement data include investors, consultants, insurance companies, market researchers, and more. These stakeholders face various challenges, such as identifying market trends, assessing property values, and forecasting demand for products and services. Data has transformed these industries by providing actionable insights, enabling more strategic decision-making.

The future of data in the housing market and home improvement sector is bright, with AI and machine learning poised to unlock the value hidden in decades-old documents and modern government filings. This technological advancement will further enhance the ability of professionals to analyze trends, predict market movements, and make informed decisions, driving the industry forward.

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