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.

Buy Amazon datasets and get access to over 300 million records from any Amazon domain. Get insights on Amazon products, sellers, and reviews.

According to a 2023 survey conducted among small and medium-sized businesses selling on Amazon, Home and kitchen was the most popular category among small sellers on Amazon's online marketplace, with over ******* (** percent) of respondents saying they had such products listed there for sale. In addition, ** percent of the sellers surveyed reported selling products in the beauty and personal care category.

Amazon Product Description Dataset

This dataset is a cleaned version of Amazon Product Data. Cleaned by team at https://exnrt.com

421K Unique Examples Empty description rows are being removed. Description Smaller then 200 characters are removed Convert to Proper Format Remove non-ASCII characters from both column And few more techniques

  Original Dataset

This original dataset has 10 Million Examples. Original, Un-cleaned DataSet:… See the full description on the dataset page: https://huggingface.co/datasets/Ateeqq/Amazon-Product-Description.

Dataset Card for Amazon Products 2023

  Dataset Summary

This dataset contains product metadata from Amazon, filtered to include only products that became available in 2023. The dataset is intended for use in semantic search applications and includes a variety of product categories.

Number of Rows: 117,243 Number of Columns: 15

  Data Source

The data is sourced from Amazon Reviews 2023. It includes product information across multiple categories, with additional… See the full description on the dataset page: https://huggingface.co/datasets/milistu/AMAZON-Products-2023.

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

According to forecasts as of March 2022, the sales share of electrical products on Amazon was expected at **** percent that year. By 2027, electrical products will make up **** percent of Amazon sales. Additionally, fashion and apparel was forecast to make up **** percent of Amazon sales by 2027, *** percentage point higher than in 2022.

First 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.

Context

This 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:

  • The total number of reviews is 233.1 million (142.8 million in 2014).

• New reviews:

  • Current data includes reviews in the range May 1996 - Oct 2018.

• Metadata: - We have added transaction metadata for each review shown on the review page.

  • Added more detailed metadata of the product landing page.

Acknowledgements

If you publish articles based on this dataset, please cite the following paper:

• Jianmo Ni, Jiacheng Li, Julian McAuley. Justifying recommendations using distantly-labeled reviews and fined-grained aspects. EMNLP, 2019.

Amazon's monthly revenue in the United States for beauty and personal care sales is estimated to range from 2.4 to 3.8 billion U.S. dollars in 2024. The sales revenue is estimated to experience two significant peaks, one in July 2024 at 3.6 billion U.S. dollars and the other in December 2024 at 3.8 billion U.S. dollars. In the same year, beauty and personal care products were one of Amazon's most profitable product categories.

Amazon is known as an e-commerce company, but in recent years, the retailer has invested in opening physical stores across the United States with more international expansion in mind. Amazon’s physical retail stores come in different formats, including Amazon Fresh grocery stores, Amazon Go, Amazon Books, Amazon 4 Star, and Amazon Pop-up. Typically, Amazon’s branded devices, books and other merchandise are available in these stores. In the fourth quarter of 2024, net sales from Amazon’s physical retailing amounted to nearly 5.8 billion U.S. dollars. Whole Foods acquisition and Amazon Fresh Amazon’s venture into brick-and-mortar grocery store retailing started with the acquisition of the Whole Foods Market in 2018. By 2017, just before it was bought out by Amazon, the supermarket Whole Foods had registered a net sales revenue of over 16 billion U.S. dollars. In addition to some 500 Whole Foods locations, Amazon’s grocery retail business is supported by Amazon Fresh with stores predominantly in the United States. Outside of the United States, Amazon opened its first Amazon Fresh stores in the United Kingdom in March 2021. Amazon’s retail portfolio Amazon has a diverse retail portfolio, both in terms of merchandise and the business models it offers across its platforms. While it started its e-commerce business as an online retailer acting as the first-party owner of the products on offer, third-party selling on the Amazon marketplace increasingly became the norm among online sellers, who often employ both models when working with Amazon. Since 2017, more than half of paid units of Amazon is attributed to third-party sellers using the Amazon marketplace to sell their products.

Comprehensive dataset analyzing Amazon product review counts across categories, including 40 reviews average, category-specific benchmarks, and reviews-to-sales ratios based on analysis of 31,900 brands and 12 million product reviews.

This 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.

Amazon is one of the most recognisable brands in the world, and the third largest by revenue. It was the fourth tech company to reach a $1 trillion market cap, and a market leader in e-commerce,...

1) Data Introduction • The Amazon Sales Dataset includes e-commerce product and consumer feedback data, including details on more than 1,000 products collected from Amazon's official website, discount prices, ratings, reviews, and categories.

2) Data Utilization (1) Amazon Sales Dataset has characteristics that: • The dataset includes a variety of product and review-related attributes, including product ID, product name, category, real and discounted prices, discount rates, ratings, rating numbers, product descriptions, user reviews, images, and product links. (2) Amazon Sales Dataset can be used to: • Product Rating and Review Analysis: Use rating and review data to analyze consumer satisfaction, popular products, review trends, and develop marketing strategies for each product. • Development of Price Policy and Recommendation System: Based on price information such as actual price, discount price, and discount rate, it can be used for price policy analysis, product recommendation system, consumer purchasing behavior prediction, etc.

These 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

• 200K+ Seller Leads • Seller Type: Brand/PL Seller, 1P/Amazon Vendor Central and 3P Sellers • Selling Platforms: Amazon USA, UK, EU, CA, AU • C-Suite/Marketing/Sales Contacts • FBA/FBM Sellers • Filter your leads by revenue, categories, location, SKU's and more • 100% manually researched and verified.

For over a decade, we have been manually collecting Amazon seller data from various data sources such as Amazon, LinkedIn, Google, and others. We specialize in getting valid data so you may conduct ads and begin selling without hesitation.

We designed our data packages for all types of organizations, thus they are reasonably priced. We are always trying to reduce our prices to better suit all of your requirements.

So, if you’re looking to reach out to your targeted Amazon sellers, now is the greatest time to do so and offer your goods, services, and promotions. You can get your targeted Amazon Sellers List with seller contact information.

Alternatively, if you provide Amazon Seller Names or IDs, we will conduct Custom Research and deliver the customized list to you.

Data Points Available:

Full Name Linkedin URL Direct Email Generic Phone Number Business Name and Address Company Website Seller IDs and URLs Revenue Seller Review Count Niche FBA/Non-FBA Country and More

Comprehensive dataset covering Amazon's 1.9 million active third-party sellers worldwide, including regional distribution, growth trends, and marketplace dynamics from 2000-2025.

Download seller's data & convert sellers into leads into potential clients for your business. Amazon sellers' data including their addresses, brands, ASINs, phone, and more. Amazon US, UK, India, Canada, Mexico, and Italy country data available All data went through QA process We are updating data every 6 months

Each product image downloaded and stored in locally and attached local image path to each record.

Total records: 99K+

Images count: 493K+