Over 1.6M WooCommerce stores from around the world: United States (308k stores) Canada (68k stores) Europe (818k stores) Asia (279k stores) Oceania (94k stores) South America (100k stores)

Sample data: https://docs.google.com/spreadsheets/d/1CpJSjaVOUQGw2qwahGeQkgnNN2Lt6BGbY0wiqjHVlHU

We can create a custom list based on your criteria e.g. stores from specific countries and categories, using specific technologies and apps, with certain keywords on the homepage, with over 10k Instagram followers etc.

Pricing: $0.05 per lead

We also offer volume discounts on orders above 10,000 sellers.

Austin Water’s Standard Products List specifies acceptable manufacturer products for use in the construction of water and wastewater facilities. These products have undergone stringent testing to ensure the safety, reliability and consistency within the Austin Water system

This Appendix to the 2021 Virginia Coastal Resilience Master Plan Technical Study provides a simple consolidated list of study analytical and geospatial products. High-level descriptions of the approaches and products are available in the Coastal Resilience Master Plan document and the Coastal Resilience Web Explorer. The Web Explorer allows users to interact with many of the data products. Details on the data sources and methodologies for the products listed herein are located in the Coastal Resilience Master Plan Technical Appendices.

These datasets contain peer-to-peer trades from various recommendation platforms.

Metadata includes

• peer-to-peer trades

• have and want lists

• image data (tradesy)

Active list of products sold by the associated solicitor to the wholesaler.

The list includes only farm product liens that have not lapsed - ORS 80.118. To access liens up to one year past the lapse date, use the UCC Seach

Find any Shopify store in the world's detailed info. The data includes: - Store Name - Store URL - Product Distribution and Categories - Alexa Ranks - Number Of Products - Country (Please look into other products for the global lists) - Email and Contact Info - Social Media Outlets With URLs

Additional fields can be added via requirements as well.

This dataset contains a list of products that carry the Design for the Environment (DfE) label. This mark enables consumers to quickly identify and choose products that can help protect the environment and are safer for families. When you see the DfE logo on a product it means that the DfE scientific review team has screened each ingredient for potential human health and environmental effects and that-based on currently available information, EPA predictive models, and expert judgment-the product contains only those ingredients that pose the least concern among chemicals in their class. Product manufacturers who become DfE partners, and earn the right to display the DfE logo on recognized products, have invested heavily in research, development and reformulation to ensure that their ingredients and finished product line up on the green end of the health and environmental spectrum while maintaining or improving product performance. EPA's Design for the Environment Program (DfE) has allowed use of their logo on over 2500 products. These products are formulated from the safest possible ingredients and have reduced the use of "chemicals of concern" by hundreds of millions of pounds. A Spanish version of this dataset is available for download at https://www.epa.gov/dfe/pubs/products/list_of_labeled_products.html

Gain insight into product margins through web-sourced product availability and discounting data for beauty, fashion, and household brands. Retail pricing data is sourced from dozens of US online retailers.

United States Consumer List Database with full contact information, including; Addresses, Telephone Numbers, Email Address and Location as well as hundreds of available consumer behavior/buying activity/lifestyle/interest attributes. Attribute categories include; Income, Net Worth, Home Ownership, Vehicle Ownership, Loan and Mortgage, Credit Usage, Buying Activities, Donor History and Lifestyle Interests/Hobbies. Please contact us for a full list of available attributes, list counts, and pricing.

This blog post was posted by Wes Barker on July 27, 2018. It was written by Steven Posnack, M.S., M.H.S., Dustin Charles and Wes Barker.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The Product Catalog Data provides a comprehensive overview of products across various categories. This dataset includes detailed product titles, descriptions, barcodes, category-specific attributes, weight, measurements, and imagery. It's tailored for marketplaces, eCommerce sites, and data analysts who require in-depth product information to enhance user experience, SEO, and product categorization.

Popular Attributes:

✔ Detailed product information

✔ High-quality imagery

✔ Extensive attribute coverage

✔ Ideal for UX and SEO optimization

✔ Comprehensive product categorization

Key Information:

Rich dataset with 30+ attributes per product

Pricing: Flexible subscription models

Update Frequency: Daily updates

Coverage: Global and specific markets

Historical Data: 12 Months +

Our extensive database contains approximately 800,000 active rental property listings from across the United States. Updated daily, this comprehensive collection provides real estate professionals, investors, and property managers with valuable market intelligence and business opportunities. Database Contents

Property Addresses: Complete location data including street address, city, state, ZIP code Listing Dates: Original listing date and most recent update date Availability Status: Currently available, pending, or recently rented properties Geographic Coverage: Properties spanning all 50 states and major metropolitan areas

Applications & Uses

Market Analysis: Track rental pricing trends across different regions and property types Investment Research: Identify high-opportunity markets with favorable rental conditions Lead Generation: Connect with property owners potentially needing management services Competitive Intelligence: Monitor listing volumes, vacancy rates, and market saturation Business Development: Target specific neighborhoods or property categories for expansion

File Format & Delivery

Organized in easy-to-use CSV format for seamless integration with data analysis tools Accessible through secure download portal or API connection Daily updates ensure you're working with the most current market information Custom filtering options available to narrow results by location, date range, or other criteria

Data Quality

Rigorous validation processes to ensure address accuracy Duplicate listing detection and removal Regular verification of active status Standardized format for consistent analysis

Subscription Benefits

Access to historical listing archives for trend analysis Advanced search capabilities to target specific property characteristics Regular market reports summarizing key trends and opportunities Custom data exports tailored to your specific business needs

AK ~ 1,342 listings AL ~ 6,636 listings AR ~ 4,024 listings AZ ~ 25,782 listings CA ~ 102,833 listings CO ~ 14,333 listings CT ~ 10,515 listings DC ~ 1,988 listings DE ~ 1,528 listings FL ~ 152,258 listings GA ~ 28,248 listings HI ~ 3,447 listings IA ~ 4,557 listings ID ~ 3,426 listings IL ~ 42,642 listings IN ~ 8,634 listings KS ~ 3,263 listings KY ~ 5,166 listings LA ~ 11,522 listings MA ~ 53,624 listings MD ~ 12,124 listings ME ~ 1,754 listings MI ~ 12,040 listings MN ~ 7,242 listings MO ~ 10,766 listings MS ~ 2,633 listings MT ~ 1,953 listings NC ~ 22,708 listings ND ~ 1,268 listings NE ~ 1,847 listings NH ~ 2,672 listings NJ ~ 31,286 listings NM ~ 2,084 listings NV ~ 13,111 listings NY ~ 94,790 listings OH ~ 15,843 listings OK ~ 5,676 listings OR ~ 8,086 listings PA ~ 37,701 listings RI ~ 4,345 listings SC ~ 8,018 listings SD ~ 1,018 listings TN ~ 15,983 listings TX ~ 132,620 listings UT ~ 3,798 listings VA ~ 14,087 listings VT ~ 946 listings WA ~ 15,039 listings WI ~ 7,393 listings WV ~ 1,681 listings WY ~ 730 listings

Grand Total ~ 977,010 listings

This dataset was created to simulate a market basket dataset, providing insights into customer purchasing behavior and store operations. The dataset facilitates market basket analysis, customer segmentation, and other retail analytics tasks. Here's more information about the context and inspiration behind this dataset:

Context:

Retail businesses, from supermarkets to convenience stores, are constantly seeking ways to better understand their customers and improve their operations. Market basket analysis, a technique used in retail analytics, explores customer purchase patterns to uncover associations between products, identify trends, and optimize pricing and promotions. Customer segmentation allows businesses to tailor their offerings to specific groups, enhancing the customer experience.

Inspiration:

The inspiration for this dataset comes from the need for accessible and customizable market basket datasets. While real-world retail data is sensitive and often restricted, synthetic datasets offer a safe and versatile alternative. Researchers, data scientists, and analysts can use this dataset to develop and test algorithms, models, and analytical tools.

Dataset Information:

The columns provide information about the transactions, customers, products, and purchasing behavior, making the dataset suitable for various analyses, including market basket analysis and customer segmentation. Here's a brief explanation of each column in the Dataset:

• Transaction_ID: A unique identifier for each transaction, represented as a 10-digit number. This column is used to uniquely identify each purchase.
• Date: The date and time when the transaction occurred. It records the timestamp of each purchase.
• Customer_Name: The name of the customer who made the purchase. It provides information about the customer's identity.
• Product: A list of products purchased in the transaction. It includes the names of the products bought.
• Total_Items: The total number of items purchased in the transaction. It represents the quantity of products bought.
• Total_Cost: The total cost of the purchase, in currency. It represents the financial value of the transaction.
• Payment_Method: The method used for payment in the transaction, such as credit card, debit card, cash, or mobile payment.
• City: The city where the purchase took place. It indicates the location of the transaction.
• Store_Type: The type of store where the purchase was made, such as a supermarket, convenience store, department store, etc.
• Discount_Applied: A binary indicator (True/False) representing whether a discount was applied to the transaction.
• Customer_Category: A category representing the customer's background or age group.
• Season: The season in which the purchase occurred, such as spring, summer, fall, or winter.
• Promotion: The type of promotion applied to the transaction, such as "None," "BOGO (Buy One Get One)," or "Discount on Selected Items."

Use Cases:

• Market Basket Analysis: Discover associations between products and uncover buying patterns.
• Customer Segmentation: Group customers based on purchasing behavior.
• Pricing Optimization: Optimize pricing strategies and identify opportunities for discounts and promotions.
• Retail Analytics: Analyze store performance and customer trends.

Note: This dataset is entirely synthetic and was generated using the Python Faker library, which means it doesn't contain real customer data. It's designed for educational and research purposes.

The Medicare Electronic Health Record (EHR) Incentive Program provides incentives to eligible clinicians and hospitals to adopt electronic health records. This dataset combines meaningful use attestations from the Medicare EHR Incentive Program and certified health IT product data from the ONC Certified Health IT Product List (CHPL) to identify the unique vendors, products, and product types of each certified health IT product used to attest to meaningful use. The dataset also includes important provider-specific data, related to the provider's participation and status in the program, unique provider identifiers, and other characteristics unique to each provider, like geography and provider type.

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.

Drive sales and marketing strategies with insightful information from the B2B database, including company details, the contact information of sales leads, geographic location, and more from 15+ data fields. Access the fully verified B2B database and expand your business anywhere across the globe. Create a global presence by connecting to the top decision-makers, c-level executives, and business professionals using B2B data. Engage with relevant customers through multi-channel marketing campaigns such as email marketing, telemarketing, LinkedIn marketing, social media marketing, and direct mails. Reach out to decision-makers, influencers, and leaders of different industries and your target companies with high-quality verified databases. Infotanks Media helps companies get B2B data at 95% contact accuracy. Connect with a network of professionals with 20+ million companies and 82+ million contact data. The B2B mail list is a must-have tool to increase customer engagement and acquisition. Infotanks Media can provide you with a fully verified B2B contact database of different types, including B2B mailing lists. Speed up your business's growth pace by expanding the network of your B2B contact database from Infotanks Media to get started with data integration into all your CRMs and ESPs.

The three datasets were used in a model estimating the current and future persistence of 222 populations of southern hognose snakes, as estimated as part of the USFWS Species Status Assessment. Because these datasets contain information about sensitive species at risk of overcollection and harassment, they do not contain any spatial identifying information. The "HESIM_locs" dataset contains a list of southern hognose snake occurrence records with associated year of observation and population ID. The "SEsnakes_locs" dataset contains a list of non-target snake species occurrence records with associated year of observation and population ID. The "HESIM_pops_all" dataset contains a list of southern hognose snake populations with associated habitat metrics of current and future conditions derived from publically available spatial datasets, a habitat suitability model by Crawford et al. 2019, and estimated persistence probability from the analysis. A full description of the methodology and results of the southern hognose snake status assessment is available in the publication: Crawford, B.A., Olds, M.J., Maerz, J.C., and Moore, C.T., 2019. Estimating population persistence for at-risk species using citizen science data. Biological Conservation. In review. The full Species Status Assessment: U.S. Fish and Wildlife Service, 2019. Species status assessment for the southern hognose snake (Heterodon simus). Version 1.1, April 2019. Atlanta, GA. Available at https://ecos.fws.gov/ServCat/DownloadFile/168148.