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TwitterFirst of all, Amazon product datasets are indispensable for reverse engineering your rivals. For example, you can collect a list of keywords you already rank for or want to, and go through DataForSEO Amazon Products Database to find other sellers appearing as the top results for these terms.
Next, you can narrow down the scope of your contenders to those performing the best. To do so, you can filter out sellers who won the “Amazon’s Choice” and those whose products got listed multiple times on the first page.
Once you’ve compiled the final list of your challengers, Amazon Products Database will help you to quickly examine product titles, descriptions, prices, images, and other details that will let you grasp the main contributors to your competitors’ success. Once you’ve figured that out, you can start optimizing your product listings and pricing strategies to increase conversions.
However, the number of use cases for Amazon product data isn’t limited to competitor analysis. It can be applied to monitoring product rankings, running price comparisons, and more.
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TwitterAttribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
Dataset Card for "amazon-product-data-filter"
Dataset Summary
The Amazon Product Dataset contains product listing data from the Amazon US website. It can be used for various NLP and classification tasks, such as text generation, product type classification, attribute extraction, image recognition and more.
Languages
The text in the dataset is in English.
Dataset Structure
Data Instances
Each data point provides product information, such… See the full description on the dataset page: https://huggingface.co/datasets/iarbel/amazon-product-data-filter.
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TwitterOpenWeb Ninja's Amazon Data API provides fast and reliable access to real-time Amazon data across all 22 Amazon domains. With over 600 million product listings and more than 40 data points per product, the API makes it simple to search products, query by category, and extract structured ecommerce product data at scale.
Key capabilities: - Product Search & Categories: search Amazon by keyword or retrieve products directly from categories. - Product Data: titles, descriptions, images, pricing, availability, attributes. - Amazon Reviews Data: full review content, ratings, timestamps, helpful counts. - Offers & Sellers Data: all current offers, with sellers data, and more. - Amazon Sellers Data: Amazon sellers profile, sold products, and seller reviews. - Best Sellers & Deals: Amazon Best Sellers by category, Today’s Deals, and promotions. - ASIN to GTIN: convert ASIN to GTIN/EAN/ISBN for external integrations.
Coverage & Scale: - 600M+ products across all major categories and industries. - 22 Amazon countries/domains supported. - 40+ structured data points per product. - Real-time updates, delivered via a fast and reliable REST API.
Use cases: - Pricing and product comparison tools. - Ecommerce and market research. - Seller and competitor monitoring. - Product discovery and trend analysis. - Sentiment analysis with customer product reviews data.
With OpenWeb Ninja's Amazon Data API, you get the most complete Amazon data - from product details and reviews to best sellers and deals - always delivered in real time through a fast and reliable REST API.
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TwitterReal-time Amazon Data API with 600M+ products across 22 countries - get products by keyword or category, including product details, Amazon product reviews data, offers, best sellers, deals, Amazon sellers data, Amazon influencers data, and more.
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TwitterThese datasets contain 1.48 million question and answer pairs about products from Amazon.
Metadata includes
question and answer text
is the question binary (yes/no), and if so does it have a yes/no answer?
timestamps
product ID (to reference the review dataset)
Basic Statistics:
Questions: 1.48 million
Answers: 4,019,744
Labeled yes/no questions: 309,419
Number of unique products with questions: 191,185
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Twitterhttps://brightdata.com/licensehttps://brightdata.com/license
Gain extensive insights with our Amazon datasets, encompassing detailed product information including pricing, reviews, ratings, brand names, product categories, sellers, ASINs, images, and much more. Ideal for market researchers, data analysts, and eCommerce professionals looking to excel in the competitive online marketplace. Over 425M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:
Title Asin Main Image Brand Name Description Availability Subcategory Categories Parent Asin Type Product Type Name Model Number Manufacturer Color Size Date First Available Released Model Year Item Model Number Part Number Price Total Reviews Total Ratings Average Rating Features Best Sellers Rank Subcategory Buybox Buybox Seller Id Buybox Is Amazon Images Product URL And more
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TwitterThink about extracting 25 million product information from Amazon everyday?
Data extraction from Amazon on a large scale is a pain. However - our data as a service platform is capable of performing data extraction at scale without getting blocked by Amazon's anti-scraping technology.
We are giving our customers access to ready-to-use product data feeds from Amazon on a huge scale. A scale that most web scraping service providers can't even dream about.
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NEW GOES-19 Data!! On April 4, 2025 at 1500 UTC, the GOES-19 satellite will be declared the Operational GOES-East satellite. All products and services, including NODD, for GOES-East will transition to GOES-19 data at that time. GOES-19 will operate out of the GOES-East location of 75.2°W starting on April 1, 2025 and through the operational transition. Until the transition time and during the final stretch of Post Launch Product Testing (PLPT), GOES-19 products are considered non-operational regardless of their validation maturity level. Shortly following the transition of GOES-19 to GOES-East, all data distribution from GOES-16 will be turned off. GOES-16 will drift to the storage location at 104.7°W. GOES-19 data should begin flowing again on April 4th once this maneuver is complete.
NEW GOES 16 Reprocess Data!! The reprocessed GOES-16 ABI L1b data mitigates systematic data issues (including data gaps and image artifacts) seen in the Operational products, and improves the stability of both the radiometric and geometric calibration over the course of the entire mission life. These data were produced by recomputing the L1b radiance products from input raw L0 data using improved calibration algorithms and look-up tables, derived from data analysis of the NIST-traceable, on-board sources. In addition, the reprocessed data products contain enhancements to the L1b file format, including limb pixels and pixel timestamps, while maintaining compatibility with the operational products. The datasets currently available span the operational life of GOES-16 ABI, from early 2018 through the end of 2024. The Reprocessed L1b dataset shows improvement over the Operational L1b products but may still contain data gaps or discrepancies. Please provide feedback to Dan Lindsey (dan.lindsey@noaa.gov) and Gary Lin (guoqing.lin-1@nasa.gov). More information can be found in the GOES-R ABI Reprocess User Guide.
NOTICE: As of January 10th 2023, GOES-18 assumed the GOES-West position and all data files are deemed both operational and provisional, so no ‘preliminary, non-operational’ caveat is needed. GOES-17 is now offline, shifted approximately 105 degree West, where it will be in on-orbit storage. GOES-17 data will no longer flow into the GOES-17 bucket. Operational GOES-West products can be found in the GOES-18 bucket.
GOES satellites (GOES-16, GOES-17, GOES-18 & GOES-19) provide continuous weather imagery and
monitoring of meteorological and space environment data across North America.
GOES satellites provide the kind of continuous monitoring necessary for
intensive data analysis. They hover continuously over one position on the surface.
The satellites orbit high enough to allow for a full-disc view of the Earth. Because
they stay above a fixed spot on the surface, they provide a constant vigil for the
atmospheric "triggers" for severe weather conditions such as tornadoes, flash floods,
hailstorms, and hurricanes. When these conditions develop, the GOES satellites are able
to monitor storm development and track their movements. SUVI products available in both NetCDF and FITS.
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TwitterGet the needed Amazon product data right from the data extractor! Collect Amazon data product information from 19 Amazon countries from the following domains: - amazon.com - amazon.com.au - amazon.com.br - amazon.ca - amazon.cn - amazon.fr - amazon.de - amazon.in - amazon.it - amazon.com.mx - amazon.nl - amazon.sg - amazon.es - amazon.com.tr
Request Ecommerce Product Data dataset by: - keyword - category - seller
Amazon E-commerce Data datasets gathered by keyword and category contain: - product page position in search - product position on the page - product global position
Data attributes contain: - ASIN - URL - Price (current price and discount information) - Reviews (total reviews and total rating). - Reviews information: each product can be enriched with the sub-dataset with reviews - Title - Description - Audio and Video And dozens of additional information.
Amazon extraction results can be delivered by schedule or API request, so the data can be extracted in real-time.
DATAANT uses the in-house web scraping service with no concurrency limitations, so unlimited data extractions can be performed simultaneously.
Output can and attributes can be customized to fit your particular needs.
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TwitterThis dataset provides comprehensive real-time data from Amazon's global marketplaces. It includes detailed product information, reviews, seller profiles, best sellers, deals, influencers, and more across all Amazon domains worldwide. The data covers product attributes like pricing, availability, specifications, reviews and ratings, as well as seller information including profiles, contact details, and performance metrics. Users can leverage this dataset for price monitoring, competitive analysis, market research, and building e-commerce applications. The API enables real-time access to Amazon's vast product catalog and marketplace data, helping businesses make data-driven decisions about pricing, inventory, and market positioning. Whether you're conducting market analysis, tracking competitors, or building e-commerce tools, this dataset provides current and reliable Amazon marketplace data. The dataset is delivered in a JSON format via REST API.
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TwitterAPISCRAPY's Amazon Data extraction is a sophisticated solution that leverages AI & web scraping skills to supply organizations with critical data from the Amazon platform. By scraping Amazon you get a product-related Amazon database, including product names, descriptions, pricing, ratings & reviews
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Access a comprehensive dataset of over 240,000 shoe product listings directly from Amazon UK. This dataset is ideal for researchers, e-commerce analysts, and AI developers looking to explore pricing trends, brand performance, product features, or build training data for retail-focused models.
All data is neatly packaged in a downloadable ZIP archive containing files in JSON format, making it easy to integrate with your preferred analytics or database tools.
Price and discount trend analysis
Competitor benchmarking
Product attribute extraction and modeling
AI/ML training datasets (e.g., shoe recommendation systems)
Retail assortment planning
This dataset is available as a static snapshot, but you can request weekly or monthly updates through the Crawl Feeds dashboard. Upon purchase, the data will be bundled and delivered via a direct download link.
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TwitterGlobal MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared reflectances, centered at 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used to determine the MODIS daily vegetation indices. The MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's Advanced Very High Resolution Radiometer (AVHRR) NDVI products and provides continuity for time series historical applications. MODIS also includes a new Enhanced Vegetation Index (EVI) that minimizes canopy background variations and maintains sensitivity over dense vegetation conditions. The EVI also uses the blue band to remove residual atmosphere contamination caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are computed from atmospherically corrected bi-directional surface reflectances that have been masked for water, clouds, heavy aerosols, and cloud shadows. Global MOD13Q1 data are provided every 16 days at 250-meter spatial resolution as a gridded level-3 product in the Sinusoidal projection. Lacking a 250m blue band, the EVI algorithm uses the 500m blue band to correct for residual atmospheric effects, with negligible spatial artifacts. Vegetation indices are used for global monitoring of vegetation conditions and are used in products displaying land cover and land cover changes. These data may be used as input for modeling global biogeochemical and hydrologic processes and global and regional climate. These data also may be used for characterizing land surface biophysical properties and processes, including primary production and land cover conversion.
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TwitterUnlock the potential of Ecommerce data scraping and extraction with APISCRAPY. Dive into Amazon data and tap into the vast Ecommerce market's secrets. Stay ahead of the competition by leveraging our powerful tool for comprehensive Ecommerce data insights.
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Twitterhttps://brightdata.com/licensehttps://brightdata.com/license
Buy Amazon datasets and get access to over 300 million records from any Amazon domain. Get insights on Amazon products, sellers, and reviews.
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TwitterDo you want to learn more about your brand's audience? Or perhaps you competitors?
With our Amazon User Profile API, you can get a list of verified past purchases of any user on Amazon with their profile URL. Our Online Reviews API can be used to extract customer reviews for any product on Amazon, including the author's profile URL. These URLs can in turn be used to retrieve some of the past purchases of these reviewers and can give you a clearer picture of the preferences of your target audience.
This data can be used to track customer loyalty and target audience for any brand that distributes using internet retail.
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Twitterhttps://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
Amazon marketplace is a refined dataset that provides key insights into product listings on Amazon. It focuses on essential product details such as pricing, discount rates, customer ratings, and descriptive information etc.
Researchers, data analysts, and other can use this dataset to:
Analyze price vs. rating relationships
analyze top rated or discounted products
Study category based product performaces
product_id: id of the product
product_name: name of the product
category: category of the product
actual_price:actual price of the product
discount_percentage:percentage of discount given
rating: rating given to product
rating_count:reviews the product received
about_product:specs
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Each product image downloaded and stored in locally and attached local image path to each record.
Total records: 99K+
Images count: 493K+
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TwitterThis Dataset is an updated version of the Amazon review dataset released in 2014. As in the previous version, this dataset includes reviews (ratings, text, helpfulness votes), product metadata (descriptions, category information, price, brand, and image features), and links (also viewed/also bought graphs). In addition, this version provides the following features:
More reviews:
New reviews:
Metadata: - We have added transaction metadata for each review shown on the review page.
If you publish articles based on this dataset, please cite the following paper:
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Twitterhttps://www.paradoxintelligence.com/termshttps://www.paradoxintelligence.com/terms
Real-time product search trends and consumer demand analytics across Amazon's marketplace with category and geographic granularity for institutional investment research.
Facebook
TwitterFirst of all, Amazon product datasets are indispensable for reverse engineering your rivals. For example, you can collect a list of keywords you already rank for or want to, and go through DataForSEO Amazon Products Database to find other sellers appearing as the top results for these terms.
Next, you can narrow down the scope of your contenders to those performing the best. To do so, you can filter out sellers who won the “Amazon’s Choice” and those whose products got listed multiple times on the first page.
Once you’ve compiled the final list of your challengers, Amazon Products Database will help you to quickly examine product titles, descriptions, prices, images, and other details that will let you grasp the main contributors to your competitors’ success. Once you’ve figured that out, you can start optimizing your product listings and pricing strategies to increase conversions.
However, the number of use cases for Amazon product data isn’t limited to competitor analysis. It can be applied to monitoring product rankings, running price comparisons, and more.