Zillow.com was the most-visited real estate website worldwide in 2024, with an average of ************* visits per month during the measured period. Leboncoin.fr ranked second, with ***** million monthly visits, while Carigslist.org ranked third, with ***** million average accesses.

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)

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

The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

We have made it as simple as possible to collect data from websites

Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

Success.ai’s Commercial Real Estate Dataset for the US and Canada covers brokers, agents, developers, and investors across the property ecosystem. Whether you’re selling software, leasing tools, investment services, or lead generation tools—this is your go-to dataset for North American real estate.

What You Get:
- Work email and phone (where available)
- Job title (e.g., Broker, Agent, Analyst, Developer)
- Company name, website, size, and real estate focus
- LinkedIn URLs and regional data

Use Cases:
- PropTech & CRM sales
- Real estate investment tools outreach
- Lead generation for listings & marketplaces
- Commercial financing or insurance sales

Snapshot img

US Real Estate Brokerage Software Market Size 2024-2028

The US real estate brokerage software market size is forecast to increase by USD 989.1 million at a CAGR of 9.33% between 2023 and 2028.

The real estate brokerage software market In the US is witnessing significant growth due to several key trends. Residential real estate is continually seeking ways to enhance operational efficiency and client services. companies are responding by introducing innovative real estate software solutions, such as cloud-based deployment, omnichannel communications, and predictive analytics. Furthermore, the availability of open-source real estate brokerage software solutions is providing more options for brokers, enabling them to choose solutions that best fit their business requirements. These trends are driving the growth of the market and are expected to continue shaping its future trajectory.
Cloud-based brokerage software is a popular choice due to its flexibility, scalability, and cost-effectiveness. ROI is a key consideration for brokerages, making software technologies that offer blockchain technology, smart contracts, and contract management software attractive. Internet and smartphone usage continues to rise, driving the demand for user-friendly, mobile-responsive software. The market is expected to grow, offering significant opportunities for companies providing innovative, efficient, and secure solutions.

What will be the size of the US Real Estate Brokerage Software Market during the forecast period?

Request Free Sample

The real estate brokerage industry In the US is experiencing significant digital transformation, with an increasing adoption of software solutions to streamline operations and enhance customer experiences. Digital technologies, including CRM, transaction management, marketing automation, property listing management, and lead generation tools, are becoming essential for real estate brokerages to remain competitive. The complexity of real estate transactions necessitates smart solutions that offer centralized data management, security, and automation.

How is this market segmented and which is the largest segment?

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

Type

  Customer relationship management
  Transaction management
  Lead generation
  Property management
  Others


Deployment

  Cloud based
  On-premises


Application

  Residential
  Commercial
  Industrial


Geography

  US

By Type Insights

The customer relationship management segment is estimated to witness significant growth during the forecast period.

Real Estate Customer Relationship Management (CRM) software In the US market is a vital tool for brokers and agents to manage client interactions and streamline business processes. CRM systems facilitate lead tracking, client data management, and automated communication workflows, allowing real estate professionals to analyze customer data, schedule follow-ups, and personalize engagement. The increasing importance of customer experience and personalized service In the competitive real estate sector is driving the growth of CRM software.

Additionally, remote work and cloud-based solutions, data analytics, integration with other tools, and emerging technologies like Augmented Reality (AR), Virtual Reality (VR), Machine Learning (ML), and Artificial Intelligence (AI) are enhancing the functionality and efficiency of CRM software In the real estate industry. Enhanced data security features are also crucial for protecting sensitive client information.

Get a glance at the market share of various segments Request Free Sample

The customer relationship management segment was valued at USD 401.70 million in 2018 and showed a gradual increase during the forecast period.

Market Dynamics

Our researchers analyzed the data with 2023 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.

What are the key market drivers leading to the rise in the adoption of US Real Estate Brokerage Software Market?

The increasing focus of real estate brokers on enhancing operational efficiency and client services is the key driver of the market.

The Real Estate Brokerage Software Market In the US is witnessing significant growth due to the implementation of digital solutions that streamline operations and enhance customer service. These software solutions cater to the unique requirements of real estate brokerages by offering features such as Customer Relationship Management (CRM), Transaction Management, Marketing Automation, Property Listing Management, and Lead Generation. BoomTown offers an all-in-one plat

In the realm of real estate data solutions, BatchData Property Data Search API emerges as a technical marvel, tailored for product and engineering leadership seeking robust and scalable solutions. This purpose-built API seamlessly integrates diverse datasets, offering over 600 data points, to provide a holistic view of property characteristics, valuation, homeowner information, listing data, county assessor details, photos, and foreclosure information. With state-of-the-art infrastructure and performance features, BatchData sets the standard for efficiency, reliability, and developer satisfaction.

Unraveling the Technical Prowess of BatchData Property Data Search API:

State-of-the-Art Infrastructure: At the heart of BatchData lies a state-of-the-art infrastructure that leverages the latest technologies available. Our systems are engineered to handle increased loads and growing datasets with ease, ensuring optimal performance without significant degradation. This commitment to technological advancement ensures that our data infrastructure and API systems operate at peak efficiency, even in the face of evolving demands and complexities.

Integration Capabilities: BatchData boasts integration capabilities that are second to none, thanks to our innovative data lake house architecture. This architecture empowers us to seamlessly integrate our data with any data platforms or pipelines in a matter of minutes. Whether it's connecting with existing data systems, third-party applications, or internal pipelines, our API offers limitless integration possibilities, enabling product and engineering teams to unlock the full potential of property data with minimal effort.

Developer Documentation: One of the hallmarks of BatchData is our clear and comprehensive developer documentation, which developers love. We understand the importance of providing developers with the resources they need to integrate our API seamlessly into their projects. Our documentation offers detailed guides, code samples, API reference materials, and best practices, empowering developers to hit the ground running and leverage the full capabilities of BatchData with confidence.

Performance Features: BatchData Property Search API is engineered for performance, delivering lightning-fast response times and seamless scalability. Our API is designed to efficiently handle increased loads and growing datasets, ensuring that users experience minimal latency and maximum reliability. Whether it's retrieving property data, conducting complex queries, or accessing real-time updates, our API delivers exceptional performance, empowering product and engineering teams to build high-performance applications and systems with ease. BatchData's APIs work for both residential real estate data and commercial real estate data.

Common Use Cases for BatchData Property Data Search API:

Powering Data-Driven Applications: Product and engineering teams can leverage BatchData Property Data Search API to power data-driven applications tailored for the real estate industry. Whether it's building real estate websites, mobile applications, or internal tools, our API offers comprehensive property data that can drive informed decision-making, enhance user experiences, and streamline operations.

Enabling Advanced Analytics: With BatchData, product and engineering leaders can unlock the power of advanced analytics and reporting capabilities. Our API provides access to rich property data, enabling analysts and researchers to uncover insights, identify trends, and make data-driven recommendations with confidence. Whether it's analyzing market trends, evaluating investment opportunities, or conducting competitive analysis, BatchData empowers teams to derive actionable insights from vast property datasets.

Optimizing Data Infrastructure: BatchData Property Data Search API can play a pivotal role in optimizing data infrastructure within organizations. By seamlessly integrating our API with existing data platforms and pipelines, product and engineering teams can streamline data workflows, improve data accessibility, and enhance overall data infrastructure efficiency. Our API's integration capabilities and performance features ensure that organizations can leverage property data seamlessly across their data ecosystem, driving operational excellence and innovation.

Conclusion: BatchData Property Data Search API stands at the forefront of real estate data solutions, offering product and engineering leaders a comprehensive, scalable, and high-performance API for accessing property data. With state-of-the-art infrastructure, seamless integration capabilities, clear developer documentation, and exceptional performance features, BatchData empowers teams to build data-driven applications, optimize data infrastructure, and unlock actionable insights with ease. As the real estate industry continues to evolve, BatchData remains committed to delivering innovative sol...

Graph and download economic data for Housing Inventory: Active Listing Count in Boston-Cambridge-Newton, MA-NH (CBSA) (ACTLISCOU14460) from Jul 2016 to Aug 2025 about Boston, NH, MA, active listing, listing, and USA.

BatchData provides comprehensive home ownership data for 87 million owners of residential homes in the US. We specialize in providing accurate contact information for owners of specific properties, trusted by some of the largest real estate companies for our superior capabilities in accurately unmasking owners of properties that may be hidden behind LLCs and corporate veils.

Our home ownership data is commonly used to fuel targeted marketing campaigns, generating real estate insights, powering websites/applications with real estate intelligence, and enriching sales and marketing databases with accurate homeowner contact information and surrounding intelligence to improve segmentation and targeting.

Home ownership data that is linked to a given property includes: - Homeowner Name(s) - Homeowner Cell Phone Number - Homeowner Email Address - Homeowner Mailing Address - Addresses of Properties Owned - Homeowner Portfolio Equity - Total Number of Properties Owned - Property Characteristics of Properties Owned - Homeowner sales, loan, and mortgage information - Property Occupancy Status of Properties Owned - Property Valuation & ARV information of Properties Owned - Ownership Length - Ownership History - Homeowner Age - Homeowner Marital Status - Homeowner Income - and more!

BatchService is both a data and technology company helping companies in and around the real estate ecosystem achieve faster growth. BatchService specializes in providing accurate B2B and B2C contact data for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, consolidate their data providers, and power their products and services.

Data, statistics and adopted local options related to property taxes

Property-Plant-and-Equipment-Gross Time Series for Shutterstock. Shutterstock, Inc. provides platform to connect brands and businesses to high quality content in North America, Europe, and internationally. The company offers image services consisting of photographs, vectors, and illustrations, which is used in visual communications, such as websites, digital and print marketing materials, corporate communications, books, publications, and others; footage services, including video clips, filmed by industry experts and cinema grade video effects in HD and 4K formats that are integrated into websites, social media, marketing campaigns, and cinematic productions; and music services comprising music tracks and sound effects, which are used to complement images and footage. It also provides 3 dimensional models consisting of 3D models used in various industries, such as advertising, media and video production, gaming, retail, education, design, and architecture; and generative AI content comprising images generated from algorithms trained with ethically sourced content. In addition, the company operates a collection of graphics interchange format visuals and stickers that supplies casual conversational content. It offers its services under the Shutterstock, Envato, Pond5, TurboSquid, PicMonkey, PremiumBeat, Splash News, Backgrid, Bigstock, and Offset brand names. The company serves corporate professionals and organizations, media and broadcast companies, and small and medium-sized businesses, and individual creators through digital, live sales, services, and client management channels. Shutterstock, Inc. was founded in 2003 and is headquartered in New York, New York.

--- DATASET OVERVIEW --- This dataset captures detailed information about each vacation rental property listing across multiple OTAs. This report provides performance metrics and ranking insights that help users benchmark their rental properties and key in on performance drivers across all global vacation markets Key Data has to offer.

--- KEY DATA ELEMENTS --- Our dataset includes the following core performance metrics for each property: - Property Identifiers: Unique identifiers for each property with OTA-specific IDs - Historic Performance Metrics: Revenue, ADR, guest occupancy and more over the last 12 months. - Forward Looking Performance Metrics: Revenue, ADR, guest occupancy and more over the next 6 months. - Performance Tiering and Percentile Ranking amongst peer listings within the specified performance ranking groups. --How Listings Are Grouped: Listing Source (e.g., Airbnb vs. Vrbo) Market (identified by uuid) - Market type = vacation areas Property Type (house, apartment, unique stays, etc.) Number of Bedrooms (0, 1, 2, 3, 4, 5, 6, 7, 8+)

--- USE CASES --- Market Research and Competitive Analysis: VR professionals and market analysts can use this dataset to conduct detailed analyses of vacation rental supply across different markets. The data enables identification of property distribution patterns, amenity trends, pricing strategies, and host behaviors. This information provides critical insights for understanding market dynamics, competitive positioning, and emerging trends in the short-term rental sector.

Property Management Optimization: Property managers can leverage this dataset to benchmark their properties against competitors in the same geographic area. By analyzing listing characteristics, amenity offerings and guest reviews of similar properties, managers can identify optimization opportunities for their own portfolio. The dataset helps identify competitive advantages, potential service gaps, and management optimization strategies to improve property performance.

Investment Decision Support: Real estate investors focused on the vacation rental sector can utilize this dataset to identify investment opportunities in specific markets. The property-level data provides insights into high-performing property types, optimal locations, and amenity configurations that drive guest satisfaction and revenue. This information enables data-driven investment decisions based on actual market performance rather than anecdotal evidence.

Academic and Policy Research: Researchers studying the impact of short-term rentals on housing markets, urban development, and tourism trends can use this dataset to conduct quantitative analyses. The comprehensive data supports research on property distribution patterns and the relationship between short-term rentals and housing affordability in different markets.

Travel Industry Analysis: Travel industry analysts can leverage this dataset to understand accommodation trends, property traits, and supply and demand across different destinations. This information provides context for broader tourism analysis and helps identify connections between vacation rental supply and destination popularity.

--- ADDITIONAL DATASET INFORMATION --- Delivery Details: • Delivery Frequency: monthly | quarterly | annually • Delivery Method: scheduled file loads • File Formats: csv | parquet • Large File Format: partitioned parquet • Delivery Channels: Google Cloud | Amazon S3 | Azure Blob • Data Refreshes: monthly

Dataset Options: • Coverage: Global (most countries) • Historic Data: Last 12 months performance • Future Looking Data: Next 6 months performance • Point-in-Time: N/A

Contact us to learn about all options.

--- DATA QUALITY AND PROCESSING --- Our data collection and processing methodology ensures high-quality data with comprehensive coverage of the vacation rental market. Regular quality assurance processes verify data accuracy, completeness, and consistency.

The dataset undergoes continuous enhancement through advanced data enrichment techniques, including property categorization, geographic normalization, and time series alignment. This processing ensures that users receive clean, structured data ready for immediate analysis without extensive preprocessing requirements.

Convert websites into useful data Fully managed enterprise-grade web scraping service Many of the world's largest companies trust ScrapeHero to transform billions of web pages into actionable data. Our Data as a Service provides high-quality structured data to improve business outcomes and enable intelligent decision making

Join 8000+ other customers that rely on ScrapeHero

Large Scale Web Crawling for Price and Product Monitoring - eCommerce, Grocery, Home improvement, Shipping, Inventory, Realtime, Advertising, Sponsored Content - ANYTHING you see on ANY website.

Amazon, Walmart, Target, Home Depot, Lowes, Publix, Safeway, Albertsons, DoorDash, Grubhub, Yelp, Zillow, Trulia, Realtor, Twitter, McDonalds, Starbucks, Permits, Indeed, Glassdoor, Best Buy, Wayfair - any website.

Travel, Airline and Hotel Data Real Estate and Housing Data Brand Monitoring Human Capital Management Alternative Data Location Intelligence Training Data for Artificial Intelligence and Machine Learning Realtime and Custom APIs Distribution Channel Monitoring Sales Leads - Data Enrichment Job Monitoring Business Intelligence and so many more use cases

We provide data to almost EVERY industry and some of the BIGGEST GLOBAL COMPANIES

Segro PLC was the biggest real estate investment trust (REIT) trading on the London Stock Exchange as of March 2025. A real estate investment trust (REIT) is a company that owns, and in most cases operates, income-producing real estate. REITs invest in many types of commercial real estate: offices, rental apartments, industrial warehouses, as well as hospitals, hotels, and retail properties. Market cap of REITS As of March 31, 2025, Segro PLC was ranked at the high end of the scale, with approximately ****billion British pounds in market capitalization. Segro PLC operates in eight European countries and specializes in big box and urban warehousing for retailers, logistics and transport companies, manufacturers, wholesalers. The London Stock Exchange (LSE) LSE is one of the oldest stock exchanges in the world, listing approximately ***** companies with an aggregate market capitalization of approximately *** trillion British pounds in 2024.

In June 2023, carsales.com was projected to have the biggest revenue growth among the leading online classifieds worldwide, with a 2021 to 2023 compound annual growth rate (CAGR) of 48 percent. According to the study, the Australian classifieds website had also to that date one of the largest market caps among online car, property, and general classifieds globally.

During the second quarter of 2024, Wicklow was the priciest county for purchasing residential real estate in Ireland. The average list price of a house in Wicklow was more nearly ******* euros. Notably, Dublin's city center and Kildare also joined the ranks of expensive housing areas, with average listing prices surpassing ******* euros and ******* euros, respectively. In contrast, Leitrim emerged as the most affordable place to buy residential real estate, with an average list price exceeding ******* euros. House prices in many counties exhibited an annual increase, with Tipperary reporting the highest, by ** percent.