Zillow reigns supreme in the U.S. real estate website landscape, attracting a staggering ***** million monthly visits in 2024. This figure dwarfs its closest competitor, Realtor.com, which garnered less than half of Zillow's traffic. Online platforms are extremely popular, with the majority of homebuyers using a mobile device during the buying process. The rise of Zillow Founded in 2006, the Seattle-headquartered proptech Zillow has steadily grown over the years, establishing itself as the most popular U.S. real estate website. In 2023, the listing platform recorded about *** million unique monthly users across its mobile applications and website. Despite holding an undisputed position as a market leader, Zillow's revenue has decreased since 2021. A probable cause for the decline is the plummeting of housing transactions and the negative housing sentiment. Performance and trends in the proptech market The proptech market has shown remarkable performance, with companies like Opendoor and Redfin experiencing significant stock price increase in 2023. This growth is particularly notable in the residential brokerage segment. Meanwhile, major players in proptech fundraising, such as Fifth Wall and Hidden Hill Capital, have raised billions in direct investment, further fueling the sector's development. As technology continues to reshape the real estate industry, online platforms like Zillow are likely to play an increasingly crucial role in how people search for and purchase homes. (1477916, 1251604)

The online residential home sale listings industry is experiencing significant changes in its dynamics because of the increased number of homes for sale. The growth in listings is because of various factors, including a climb in the number of homeowners choosing to sell, the easing of the mortgage rate lock-in effect, and economic concerns driving the sale of investment properties. These conditions and the shift from a seller's market towards a more balanced, or even a buyer's market, translate into increased traffic and engagement on home sale platforms. This presents an opportunity for these online platforms to enhance their user experience, refine search tools and offer data analytics to help buyers navigate the increased options. By the end of 2025, industry revenue has climbed at a CAGR of 3.0% and is expected to total $2.2 billion in 2025. In 2025, revenue is expected to strengthen by an estimated 4.2%. Despite enjoying growth, the industry faces challenges with the elevated mortgage rates reducing demand for home purchases, leading to a market freeze. Despite the gain in home listings, actual transaction volumes have remained subdued, creating a challenging environment for the online residential home sale listing platforms. To stay competitive, these platforms are pivoting to offer enhanced tools for price comparisons, real-time mortgage calculators and in-depth educational content to help buyers understand the increased cost of borrowing and also navigate the high inventory but low turnover market. Industry profit has climbed as revenue has outpaced wage growth through the end of 2025. Through the end of 2030, online platforms must position themselves for demographic shifts and changing consumer preferences. Gen Z and younger millennials, who are entering homebuying age, are demanding a more tech-driven, seamless and mobile-first experience. The industry will also continue to see online platforms transform into comprehensive, one-stop digital destinations offering integrated services for every stage of the housing journey. Embracing changes such as artificial intelligence and data analytics to enhance user experience, streamlining listings uploads and offering real-time communication between buyers, sellers, and agents will be crucial for future success. Platforms that offer user-friendly, one-stop experiences and are equipped to provide advanced, feature-rich mobile experiences are set to capture greater market share. Overall, industry revenue will gain at a CAGR of 3.3% through 2030 to total $2.6 billion.

Hello my fellow data enthusiasts! I'm back!

My journey into the world of real estate data has been nothing short of exciting, and I’m thrilled to share the fruits of that adventure with you all. After spending a few weeks tinkering with APIs, parsing responses, and structuring data into something meaningful, I'm excited to present the CLEANEST Zillow Dataset you've every seen!

Analysts will be able to get actionable insights and a structured view into the fascinating world of property data.

Here’s the story behind the dataset: Zillow’s data provides a treasure trove of information, but raw responses can be messy with nested structures, and scattered details. So, I rolled up my sleeves and built a robust pipeline to extract key data points from each response. From property details to price history, every piece of information was carefully categorized and mapped into logical fields. My goal was to create a dataset that feels as polished and user-friendly as the apps we rely on daily.

What Makes This Dataset Special?

• Structured & Clean Data: Every property in the dataset has been meticulously processed, cleaned, and formatted to make analysis seamless.
• Comprehensive Coverage: Whether you're analyzing trends in property values or studying features that drive price differences, this dataset has you covered.
• Accessible Layout: Tables are structured logically, with relationships that make sense for analysts at every level. This dataset is more than just numbers – it’s a toolkit for anyone looking to dive into real estate analysis, build predictive models, or simply explore trends in the housing market.

If you have any questions, feedback, or just want to geek out about data, don’t hesitate to connect with me on LinkedIn or here on Kaggle. Let’s build something awesome together!

NOTES: I use Google's Cloud Composer to request this data and due to costs, I'm only grabbing data for properties that were recently put up for sale or sold within the day of execution. If you're looking for historical data, please reach out!

Disclaimer: This dataset is intended for non-commercial, academic purposes and does not infringe upon Zillow's intellectual property rights. For full details on Zillow's terms, please visit Zillow's Terms of Use.

Dive in, explore, and let me know what you think. Happy analyzing!

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Context

Zillow's Economic Research Team collects, cleans and publishes housing and economic data from a variety of public and proprietary sources. Public property record data filed with local municipalities -- including deeds, property facts, parcel information and transactional histories -- forms the backbone of our data products, and is fleshed out with proprietary data derived from property listings and user behavior on Zillow.

The large majority of Zillow's aggregated housing market and economic data is made available for free download at zillow.com/data.

Content

Variable Availability:

Zillow Home Value Index (ZHVI): A smoothed seasonally adjusted measure of the median estimated home value across a given region and housing type. A dollar denominated alternative to repeat-sales indices. Find a more detailed methodology here: http://www.zillow.com/research/zhvi-methodology-6032/

Zillow Rent Index (ZRI): A smoothed seasonally adjusted measure of the median estimated market rate rent across a given region and housing type. A dollar denominated alternative to repeat-rent indices. Find a more detailed methodology here: http://www.zillow.com/research/zillow-rent-index-methodology-2393/

For-Sale Listing/Inventory Metrics: Zillow provides many variables capturing current and historical for-sale listings availability, generally from 2012 to current. These variables include median list prices and inventory counts, both by various property types. Variables capturing for-sale market competitiveness including share of listings with a price cut, median price cut size, age of inventory, and the days a listing spend on Zillow before the sale is final.

Home Sales Metrics: Zillow provides data on sold homes including median sale price by various housing types, sale counts (methodology here: http://www.zillow.com/research/home-sales-methodology-7733/), and a normalized view of sale volume referred to as turnover. The prevalence of foreclosures is also provided as ratio of the housing stock and the share of all sales in which the home was previously foreclosed upon.

For-Rent Listing Metrics: Zillow provides median rents prices and median rent price per square foot by property type and bedroom count.

Housing type definitions:

All Homes: Zillow defines all homes as single-family, condominium and co-operative homes with a county record. Unless specified, all series cover this segment of the housing stock.

Condo/Co-op: Condominium and co-operative homes.

Multifamily 5+ units: Units in buildings with 5 or more housing units, that are not a condominiums or co-ops.

Duplex/Triplex: Housing units in buildings with 2 or 3 housing units.

Tiers: By metro, we determine price tier cutoffs that divide the all homes housing stock into thirds using the full distribution of estimated home values. We then estimate real estate metrics within the property sets, Bottom, Middle, and Top, defined by these cutoffs. When reported at the national level, all Bottom Tier homes defined at the metro level are pooled together to form the national bottom tier. The same holds for Middle and Top Tier homes.

Regional Availability:

Zillow metrics are reported for common US geographies including Nation, State, Metro (2013 Census Defined CBSAs), County, City, ZIP code, and Neighborhood.

We provide a crosswalk between colloquial Zillow region names and federally defined region names and linking variables such as County FIPS codes and CBSA codes. Cities and Neighborhoods do not match standard jurisdictional boundaries. Zillow city boundaries reflect mailing address conventions and so are often visually similar to collections of ZIP codes. Zillow neighborhood boundaries can be found here.

Suppression Rules: To ensure reliability of reported values the Zillow Economic Research team applies suppression rules triggered by low sample sizes and excessive volatility. These rules are customized to the metric and region type and explain most missingness found in the provided datasets.

Additional Data Products

The following data products and more are available for free download exclusively at [Zillow.com/Data][1]:

• Zillow Home Value Forecast
• Zillow Rent Forecast
• Negative Equity (the share of mortgaged properties worth less than mortgage balance)
• Zillow Home Price Expectations Survey
• Zillow Housing Aspirations Report
• Zillow Rising Sea Levels Research
• Cash Buyers Time Series
• Buy vs. Rent Breakeven Horizon
• Mortgage Affordability, Rental Affordability, Price-to-Income Ratio
• Conventional 30-year Fixed Mortgage Rate, Weekly Time Series
• Jumbo 30-year Fixed Mortgage Rates, Weekly Time Series

Acknowledgements

The mission of the Zillow Economic Research Team is to be the most open, authoritative source for timely and accurate housing data and unbiased insight. We...

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The global Property Technology (PropTech) market, valued at $27 billion in 2025, is projected to experience robust growth, driven by increasing urbanization, the rise of smart homes, and the growing adoption of digital technologies across the real estate sector. A Compound Annual Growth Rate (CAGR) of 4.6% from 2025 to 2033 suggests a significant expansion to approximately $38 billion by 2033. Key drivers include the increasing demand for efficient property management solutions, the need for enhanced customer experience through online platforms, and the integration of data analytics for better investment decisions. The market is segmented by application (hospitality, retail, manufacturing, construction, others) and property type (residential, commercial, others). The hospitality and residential segments currently dominate, fueled by platforms like Airbnb and Zillow, respectively. However, increasing technological advancements within the construction and manufacturing sectors promise significant future growth for these segments. Geographic distribution shows North America and Asia Pacific holding the largest market shares, driven by substantial investment in innovative PropTech startups and established players. The ongoing digital transformation within the real estate sector, combined with the continuous development of cutting-edge technologies like VR/AR for virtual property tours and AI-driven property valuations, positions the PropTech market for sustained expansion in the coming years. The competitive landscape is highly dynamic, with both established players (Zillow Group, Redfin, CoStar Group) and rapidly growing innovative startups (Airbnb, OYO, WeWork) vying for market share. Increased competition is likely to spur further technological innovation and drive down prices, making PropTech solutions more accessible to a wider range of consumers and businesses. While challenges exist, such as regulatory hurdles and data security concerns, the overall positive market outlook is largely driven by the undeniable benefits offered by PropTech solutions - enhanced transparency, streamlined processes, cost reduction, and improved efficiency across the real estate lifecycle. Future growth will depend on addressing these challenges effectively and adapting to the evolving technological landscape. Continued investment in research and development and strategic partnerships will be crucial for market participants to maintain competitiveness and capitalize on emerging opportunities.

The Multiple Listing Service (MLS) Software market is poised for robust expansion, projected to reach a substantial market size of approximately $5,500 million by 2025, with a compelling Compound Annual Growth Rate (CAGR) of 12.5% anticipated throughout the forecast period from 2025 to 2033. This significant growth is fueled by the increasing digitization of real estate transactions and the rising demand for efficient property listing and management solutions among real estate professionals. The market is experiencing a strong surge driven by the need for streamlined workflows, enhanced data accuracy, and improved client engagement tools within the real estate industry. Cloud-based solutions are dominating the market due to their scalability, accessibility, and cost-effectiveness, offering a distinct advantage over traditional on-premises systems. The competitive landscape is characterized by the presence of key players like Zillow, Crexi, News Corp, and CoStar Group, who are continually innovating to offer comprehensive features such as advanced search functionalities, virtual tour integrations, and robust CRM capabilities. The market is segmented by application into Large Enterprises and Small and Medium-sized Enterprises (SMEs), with both segments demonstrating a growing appetite for advanced MLS software to gain a competitive edge. Geographically, North America, particularly the United States, remains a dominant region, while the Asia Pacific region is expected to witness the fastest growth due to its burgeoning real estate markets and increasing adoption of technology. Despite the positive outlook, challenges such as data security concerns and the initial cost of implementation for smaller entities could pose some restraints, but the overwhelming benefits of enhanced productivity and market reach are expected to outweigh these hurdles.

VITAL SIGNS INDICATOR
Home Prices (EC7)

FULL MEASURE NAME
Home Prices

LAST UPDATED
December 2022

DESCRIPTION
Home prices refer to the cost of purchasing one’s own house or condominium. While a significant share of residents may choose to rent, home prices represent a primary driver of housing affordability in a given region, county or city.

DATA SOURCE
Zillow: Zillow Home Value Index (ZHVI) - http://www.zillow.com/research/data/
2000-2021

California Department of Finance: E-4 Historical Population Estimates for Cities, Counties, and the State - https://dof.ca.gov/forecasting/demographics/estimates/
2000-2021

US Census Population and Housing Unit Estimates - https://www.census.gov/programs-surveys/popest.html
2000-2021

Bureau of Labor Statistics: Consumer Price Index - http://data.bls.gov
2000-2021

US Census ZIP Code Tabulation Areas (ZCTAs) - https://www.census.gov/programs-surveys/geography/guidance/geo-areas/zctas.html
2020 Census Blocks

CONTACT INFORMATION
vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator)
Housing price estimates at the regional-, county-, city- and zip code-level come from analysis of individual home sales by Zillow based upon transaction records. Zillow Home Value Index (ZHVI) is a smoothed, seasonally adjusted measure of the typical home value and market changes across a given region and housing type. It reflects the typical value for homes in the 35th to 65th percentile range. ZHVI is computed from public record transaction data as reported by counties. All standard real estate transactions are included in this metric, including REO sales and auctions. Zillow makes a substantial effort to remove transactions not typically considered a standard sale. Examples of these include bank takeovers of foreclosed properties, title transfers after a death or divorce and non arms-length transactions. Zillow defines all homes as single-family residential, condominium and co-operative homes with a county record. Single-family residences are detached, which means the home is an individual structure with its own lot. Condominiums are units that can be owned in a multi-unit complex, such as an apartment building. Co-operative homes are slightly different from condominiums in that the homeowners own shares in the corporation that owns the building, not the actual units themselves.

For metropolitan area comparison values, the Bay Area metro area’s median home sale price is the population-weighted average of the nine counties’ median home prices. Data is adjusted for inflation using Bureau of Labor Statistics metropolitan statistical area (MSA)-specific series. Inflation-adjusted data are presented to illustrate how home prices have grown relative to overall price increases; that said, the use of the Consumer Price Index (CPI) does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of the CPI itself.

Discover the latest market analysis on estate agent fees, revealing a $272.2 million market in 2025 projected for significant growth. Explore key drivers, trends, and regional variations impacting this dynamic sector, featuring insights from top players like Zillow, RE/MAX, and CBRE.

Market Analysis of Generative AI in Real Estate The global market for generative AI in the real estate industry is burgeoning, anticipated to grow from USD 0.48 billion in 2025 to USD 26.44 billion by 2033, registering a colossal CAGR of 86.14% throughout the forecast period. This exponential growth is primarily driven by the increasing adoption of generative AI technologies to enhance property listings, provide virtual property tours, analyze market trends, and automate real estate contracts. Additionally, the growing prevalence of digitalization in the real estate sector and the rising demand for personalized customer experiences are further fueling market expansion. The generative AI market for real estate is segmented by type and application. Image generation dominates the type segment, enabling the creation of realistic property images for virtual tours and property listings. Text generation ranks second, facilitating the automated generation of property descriptions, marketing materials, and market analysis reports. The application segment is led by property listing enhancement, followed by virtual property tours, market analysis and forecasting, and real estate contract automation. Real estate agents, developers, investors, and homebuyers constitute the primary end-users of these solutions. North America, Europe, and the Asia Pacific account for the majority of the market share, with companies like Berkshire Hathaway HomeServices, Opendoor Technologies, and Zillow Group leading the pack. Key drivers for this market are: AIpowered property valuation and appraisal Virtual property viewings and walkthroughs Automated content generation for real estate listings Predictive analytics for real estate investment and development Personalized property recommendations for buyers and renters. Potential restraints include: Growing demand for personalization Increasing adoption of AI in real estate Emergence of new technologies Need for faster and more efficient processes. Growing investments by real estate companies.

The PropTech market is booming, projected to reach $37.67 billion by 2033 with a 4.4% CAGR. This in-depth analysis explores market drivers, trends, and key players like Zillow, Airbnb, and Compass, covering residential, commercial, and other segments across North America, Europe, and Asia Pacific. Discover the future of real estate technology.

Affordable Housing Market Analysis The global affordable housing market is projected to reach $1,983.52 billion by 2033, exhibiting a CAGR of 4.71% from 2025 to 2033. The rising population, urbanization, affordability crisis, and supportive government policies are the primary drivers fueling market growth. The increasing demand for affordable single-family homes, multi-family units, and townhouses, coupled with the adoption of innovative construction methods like prefabrication, 3D printing, and sustainable construction, are key trends shaping the market. The market faces restraints such as escalating land and construction costs, regulatory challenges, and the shortage of skilled labor. Nevertheless, the emergence of crowdfunding platforms and non-profit organizations providing financial assistance, as well as government subsidies and tax incentives, are expected to mitigate these constraints. The market is segmented based on housing type, funding source, construction method, and target demographics. D.R. Horton, Taylor Morrison, PulteGroup, Zillow, Hovnanian Enterprises, and Lennar Corporation are notable companies in the global affordable housing market, with operations in key regions like North America, Europe, and Asia Pacific. Recent developments include: Recent developments in the Affordable Housing Market have highlighted the urgent need for innovative housing solutions as governments and organizations strive to address the growing housing crisis exacerbated by economic challenges and population growth. Various nations are prioritizing policies that encourage public-private partnerships to stimulate investment in affordable housing initiatives. Additionally, the integration of sustainable building practices and smart technologies is gaining traction as stakeholders aim to improve energy efficiency while reducing construction costs. Recent collaborations among international entities and local governments focus on leveraging funding for housing projects, particularly in urban areas where demand is surging. Moreover, rising material costs and labor shortages are prompting stakeholders to explore alternative building materials and methods, including modular construction and 3D printing, to streamline processes. These trends underscore a collective commitment to creating equitable housing opportunities while navigating the complexities of market dynamics, aiming for significant progress by 2032. Overall, this evolving landscape reflects a concerted effort to promote affordability, sustainability, and accessibility in housing worldwide.. Key drivers for this market are: Green building technologies adoption Public-private partnerships expansion Innovative financing solutions development Urban regeneration projects implementation Digital platforms for housing access. Potential restraints include: rising urbanization, government initiatives; increasing housing demand; socioeconomic disparities; affordable financing options.

📝 Dataset Description: This synthetic dataset contains 3,000 residential property listings modeled after real U.S. house sales data (in a Zillow-style format). It is designed for use in real estate analysis, machine learning, data visualization, and web scraping practice.

Each row represents a unique property and includes 16 key features commonly used by real estate agents, investors, and analysts. The data spans multiple U.S. states and cities, with realistic values for price, square footage, bedroom/bathroom count, property type, and more.

✅ Included Fields: Price – Listing price (in USD)

Address, City, State, Zipcode – U.S. formatted property location

Bedrooms, Bathrooms, Area (Sqft) – Core home specs

Lot Size, Year Built, Days on Market

Property Type, MLS ID, Listing Agent, Status

Listing URL – Mock Zillow-style property link

⚙️ Use Cases: Exploratory data analysis (EDA)

Regression/classification model training

Feature engineering and preprocessing

Real estate dashboards and web app mockups

Practice with BeautifulSoup, Pandas, or Power BI

The global estate agent fees market is a substantial sector, reaching a value of $214.7 million in 2025. This market is projected to experience steady growth, with a compound annual growth rate (CAGR) of 3.4% from 2025 to 2033. Several factors contribute to this growth. Increasing urbanization and population growth globally fuel demand for real estate, driving up the need for estate agents and consequently, their fees. The rise of online real estate platforms, while creating some competition, also contributes to market expansion by increasing market transparency and attracting more buyers and sellers. Furthermore, the diversification of services offered by estate agents beyond simple brokerage, including property management and investment advice, contributes to higher fee generation. Segmentation within the market reveals significant activity in both residential and commercial real estate, with buyer and seller charges representing distinct revenue streams. This creates opportunities for specialized firms catering to specific market segments.
The geographical distribution of the market shows significant activity across North America, Europe, and Asia Pacific. North America, with its mature real estate markets and established agent networks, likely holds a significant market share. However, rapidly developing economies in Asia Pacific present substantial growth potential due to their expanding middle classes and burgeoning real estate sectors. Europe's diverse markets and regulatory landscapes present varied opportunities and challenges for estate agents. While some established players dominate the market, the presence of regional and niche agencies points to a dynamic competitive landscape. The future growth of the market will depend on broader economic conditions, government policies impacting real estate, and the ongoing evolution of technological advancements in the real estate sector. The continued focus on providing value-added services and leveraging technology will be key for success in this evolving market.

zillow.com is ranked #39 in US with 245.44M Traffic. Categories: Online Services, Real Estate. Learn more about website traffic, market share, and more!

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