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.

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

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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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 Property Group is a leading real estate organization that provides expert guidance throughout the home buying and selling process. With a strong presence in Little Rock, Arkansas, the company has established itself as a trusted partner for individuals and families seeking to buy, sell, or rent properties. The Property Group's expert agents are well-versed in local market trends, ensuring that clients receive tailored solutions to their unique needs.

Through their user-friendly website, The Property Group offers a range of resources and tools for homebuyers, including exclusive property listings, neighborhood information, and real-time market reports. Whether buying or selling a home, clients can rely on the company's dedicated professionals to navigate the complex process with ease. With a focus on transparency, efficiency, and personalized attention, The Property Group has earned a reputation as a top choice for those seeking a seamless and stress-free real estate experience.

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

Our US Home Ownership Data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes various data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

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

These National Statistics provide monthly estimates of the number of residential and non-residential property transactions in the UK and its constituent countries. National Statistics are accredited official statistics.

England and Northern Ireland statistics are based on information submitted to the HM Revenue and Customs (HMRC) Stamp Duty Land Tax (SDLT) database by taxpayers on SDLT returns.

Land and Buildings Transaction Tax (LBTT) replaced SDLT in Scotland from 1 April 2015 and this data is provided to HMRC by https://www.revenue.scot/">Revenue Scotland to continue the time series.

Land Transaction Tax (LTT) replaced SDLT in Wales from 1 April 2018. To continue the time series, the https://gov.wales/welsh-revenue-authority">Welsh Revenue Authority (WRA) have provided HMRC with a monthly data feed of LTT transactions since July 2021.

LTT figures for the latest month are estimated using a grossing factor based on data for the most recent and complete financial year. Until June 2021, LTT transactions for the latest month were estimated by HMRC based upon year on year growth in line with other UK nations.

LTT transactions up to the penultimate month are aligned with LTT statistics.

Go to Stamp Duty Land Tax guidance for the latest rates and information.

Go to Stamp Duty Land Tax rates from 1 December 2003 to 22 September 2022 and Stamp Duty: rates on land transfers before December 2003 for historic rates.

The latest release was published 09:30 29 August 2025 and was updated with provisional data from completed transactions during July 2025.

The next release will be published 09:30 30 September 2025 and will be updated with provisional data from completed transactions during July 2025.

https://webarchive.nationalarchives.gov.uk/ukgwa/20240320184933/https://www.gov.uk/government/statistics/monthly-property-transactions-completed-in-the-uk-with-value-40000-or-above">Archive versions of the Monthly property transactions completed in the UK with value of £40,000 or above are available via the UK Government Web Archive, from the National Archives.

August 2025

The NYC Department of City Planning’s (DCP) Housing Database contains all NYC Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. It includes the three primary construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. Records in the Housing Database Project-Level Files are geocoded to the greatest level of precision possible, subject to numerous quality assurance and control checks, recoded for usability, and joined to other housing data sources relevant to city planners and analysts.

Data are updated semiannually, at the end of the second and fourth quarters of each year.

Please see DCP’s annual Housing Production Snapshot summarizing findings from the 21Q4 data release here. Additional Housing and Economic analyses are also available.

The NYC Department of City Planning’s (DCP) Housing Database Unit Change Summary Files provide the net change in Class A housing units since 2010, and the count of units pending completion for commonly used political and statistical boundaries (Census Block, Census Tract, City Council district, Community District, Community District Tabulation Area (CDTA), Neighborhood Tabulation Area (NTA). These tables are aggregated from the DCP Housing Database Project-Level Files, which is derived from Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions. These files can be used to determine the change in legal housing units across time and space.

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

NZ Parcel Boundaries Wireframe provides a map of land, road and other parcel boundaries, and is especially useful for displaying property boundaries.
This map service is for visualisation purposes only and is not intended for download. You can download the full parcels data from the NZ Parcels dataset.
This map service provides a dark outline and transparent fill, making it perfect for overlaying on our basemaps or any map service you choose.
Data for this map service is sourced from the NZ Parcels dataset which is updated weekly with authoritative data direct from LINZ’s Survey and Title system. Refer to the NZ Parcel layer for detailed metadata.
To simplify the visualisation of this data, the map service filters the data from the NZ Parcels layer to display parcels with a status of 'current' only.
This map service has been designed to be integrated into GIS, web and mobile applications via LINZ’s WMTS and XYZ tile services. View the Services tab to access these services.
See the LINZ website for service specifications and help using WMTS and XYZ tile services and more information about this service.

Publication Date: April 2025 2024 Parcel Data. Updated annually, or as needed. The data can be downloaded here: https://gis.ny.gov/parcels#data-download. This feature service has two layers: 1) NYS Tax Parcels Public, and 2) NYS Tax Parcels Public Footprint which contains polygons representing counties for which tax parcel polygons are available in the NYS Tax Parcels Public layer. County footprint polygons display when zoomed out beyond 1:37,050-scale. Tax parcel polygons display when zoomed in below 1:37,051-scale. The NYS Tax Parcels Public layer contains 2024 parcel data only for NY State counties which gave NYS ITS Geospatial Services permission to share this data with the public. Work to obtain parcel data from additional counties, as well as permission to share the data, is ongoing. To date, 36 counties have provided Geospatial Services permission to share their parcel data with the public. Parcel data for counties which do not allow Geospatial Services to redistribute their data must be obtained directly from those counties. Geospatial Services' goal is to eventually include parcel data for all counties in New York State. Parcel geometry was incorporated as received from County Real Property Departments. No attempt was made to edge-match parcels along adjacent counties. County attribute values were populated using 2024 Assessment Roll tabular data the NYS ITS Geospatial Services obtained from the NYS Department of Tax and Finance’s Office of Real Property Tax Services (ORPTS). Tabular assessment data was joined to the county provided parcel geometry using the SWIS & SBL or SWIS & PRINT KEY unique identifier for each parcel. Detailed information about assessment attributes can be found in the ORPTS Assessor’s Manuals available here: https://www.tax.ny.gov/research/property/assess/manuals/assersmanual.htm. New York City data comes from NYC MapPluto which can be found here: https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-pluto-mappluto.page. Thanks to the following counties that specifically authorized Geospatial Services to share their GIS tax parcel data with the public: Albany, Cayuga, Chautauqua, Cortland, Erie, Genesee, Greene, Hamilton, Lewis, Livingston, Montgomery, NYC- Bronx, NYC- Kings (Brooklyn), NYC- New York (Manhattan), NYC- Queens, NYC- Richmond (Staten Island), Oneida, Onondaga, Ontario, Orange, Oswego, Otsego, Putnam, Rensselaer, Rockland, Schuyler, St Lawrence, Steuben, Suffolk, Sullivan, Tioga, Tompkins, Ulster, Warren, Wayne, and Westchester. Geometry accuracy varies by contributing county. This map service is available to the public. The State of New York, acting through the New York State Office of Information Technology Services, makes no representations or warranties, express or implied, with respect to the use of or reliance on the Data provided. The User accepts the Data provided “as is” with no guarantees that it is error free, complete, accurate, current or fit for any particular purpose and assumes all risks associated with its use. The State disclaims any responsibility or legal liability to Users for damages of any kind, relating to the providing of the Data or the use of it. Users should be aware that temporal changes may have occurred since this Data was created.

A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.

Collection of digitised maps over Queensland at various scales 1841–2005, including cadastral maps which show property boundaries, property descriptions and land tenure, and some other related miscellaneous maps. Some are annotated and quality of scans varies. The majority of map series include key maps.

Please note: Detailed instructions on how to access each of the scanned maps can be found on the following page http://www.qld.gov.au/recreation/arts/heritage/museum-of-lands/maps-plans/cadastral/

At Echo, our dedication to data curation is unmatched; we focus on providing our clients with an in-depth picture of a physical location based on activity in and around a point of interest over time. Our dataset empowers you to explore the “what” by allowing you to dig deeper into customer movement behaviors, eliminate gaps in your trade area and discover untapped potential. Leverage Echo's Activity datasets to identify new growth opportunities and gain a competitive advantage.

This sample of our Area Activity data provides you insights into the estimated total unique visitors and visits in an area. This helps you understand frequentation dynamics over time, identify emerging trends in people movements and measure the impact of external factors on how people move across a city.

Additional Information: - Understand the actual movement patterns of consumers without using PII data, gaining a 360-degree consumer view. Complement your online behavior knowledge with actual offline actions, and better attribute intent based on real-world behaviors. - Echo collects, cleans and updates its footfall on a daily basis. Normalization of the data occurs on a monthly basis. - We provide data aggregation on a weekly, monthly and quarterly basis. - Information about our country offering and data schema can be found here:

1) Data Schema: https://docs.echo-analytics.com/activity/data-schema
2) Country Availability: https://docs.echo-analytics.com/activity/country-coverage
3) Methodology: https://docs.echo-analytics.com/activity/methodology

Echo's commitment to customer service is evident in our exceptional data quality and dedicated team, providing 360° support throughout your location intelligence journey. We handle the complex tasks to deliver analysis-ready datasets to you.

Business Needs: 1. Site Selection: Leverage footfall data to identify the best location to open a new store. By analyzing areas with high footfall you can select sites that are likely to attract more customers. 2. Urban Planning Development: City planners can use footfall data to optimize the layout and infrastructure of urban areas, guide the development of commercial areas by indicating where pedestrian traffic is heaviest, and aid in traffic management and safety measures. 3. Real Estate Investment: Leverage footfall data to identify lucrative investment opportunities and optimize property management by analyzing pedestrian traffic patterns.