• 500K+ Active Amazon Stores • 200K+ Seller Leads • Platforms USA, Germany, UK, Italy, France, Spain, CA • C-Suite/Marketing/Sales Contacts • FBA/Non-FBA Sellers • 15+ data points available for each prospect • Filter your leads by store size, niche, location, and many 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 are specialized to get valid, and potential 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

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

Capture all Amazon product listing details with confidence that you are getting complete and current data. Rainforest API offers comprehensive coverage of each of the product listings or search results in a cleanly structured output.

Rainforest API's advanced parsing means the results returned are exactly what a human user would see. You can request data from any Amazon domain and originate your request from any country in the world. The high-capacity, global infrastructure of the Rainforest API assures you the highest level of performance and reliability. For easy integration with your apps, data is delivered in JSON or CSV format. A convenient CSV Builder allows customization of data columns.

Data is retrieved in real time, by search term, or for single products, by global identifiers such as GTIN, ISBN, UPC and EAN rather than Amazon ASIN. The API automatically performs the ASIN conversion for each request. You can also submit a product page URL (product results), or a category ID (category search results) instead.

So what's in the data from Rainforest API?

Product: - Brand & manufacturer - Manufacturer & Amazon product descriptions - Specifications - Buy Box Winner: price, etc. - 1st party, 2nd party & 3rd party seller data - Additional product details (i.e. energy efficiency, add-ons) - A-Plus content - Imagery - Product videos - Category details (category, bestseller category) - Deals (types, states) - Bundles - Seller offers (including delivery options) - Frequently bought together / Also bought - Also viewed / Similar item to consider - Rating & reviews (incl. full review, top positive, top negative, manufacturer replies) - Stock estimation - Sales estimation (for select Amazon domains)

Search Results: - Product details per search result - Position - Related searches - Related brands

...and more, depending on your request parameters or the search result.

How can Traject Data: Amazon Product Results Data be used? - Product listing management - Price monitoring - Brand protection - Category & product trends monitoring - Market research & competitor intelligence - Location-specific & cross-border Amazon shipping data - Rank tracking on Amazon

Who uses Traject Data: Amazon Product Results Data? This data is leveraged by software developers, marketers, founders, sales & business development teams, researchers, and data analysts & engineers in ecommerce, other retail/wholesale business, agencies and SaaS platforms.

Anyone in your organization who works with your digital presence can develop business intelligence and strategy using this advanced product data.

✔️ Easy-to-handle Excel Sheet ✔️ Human Researched and Verified leads with Direct contacts ✔️ Up to 🇩🇪25K German Active Amazon third-party private Label Sellers lead direct contact and info ✔️ Up to 30+ data points for each prospect ✔️ Sort your list by store size, product category, company location, and much more! ✔️ Enjoy a list that has been hand-researched and verified. No scrapped contacts!

Data includes: Seller ID Seller Business Model: Private Label Seller/Wholesaler Estimated Annual Revenue in $ ( accurate +/-30%) Annual Revenue Bracket [$] % of goods shipped in FBA Amazon Seller Page Seller Website Decision Maker First Name Decision Maker Last Name Direct Email Generic Email Office Phone Number Decision Maker Linkedin URL Seller Name Seller Storefront Link Seller Business Name Seller Business Full Address City State Zip Seller Business Country Number of Reviews [30 days] Number of Reviews [90 days] Number of Reviews [12 months] Number of Reviews [lifetime] Seller Rating Lifetime Total number of products Total number of brands Brands Top Product URL Top Product Shipping From Top Product Category Top Product SubCategory

About SellerDirectories: SellerDirectories.com provides human-researched and verified data on Amazon sellers and eCommerce Brands.

Our human-researched and verified data is trusted by companies like Walmart, Microsoft, Tencent, Helium10, and 250 more! ⭐ Check our verified 5-star reviews on Trustpilot ⭐ https://www.trustpilot.com/review/sellerdirectories.com ⭐

✅ Data Sources: Aggregated from 50+ sources

✅ Data Collection: Human Researched and verified (we don't like scrapped contact data)

✅ 98%+ accurate and up-to-date data (verified)

✅ Brand /seller Targeting Options: Multiple filters available (including revenue, location, business model, and product category)

✅ Customer Service: Lifetime support and accuracy guarantee on your list. Our lists include resources on how best to run outreach campaigns to turn a prospect list into actual business opportunities. Buy B2B contact database with SellerDirectories.com, and get your B2B contacts database sorted!

✔️ Easy-to-handle Excel Sheet ✔️ Human Researched and Verified leads with Direct contacts ✔️ Up to 🇬🇧30K Active Amazon third-party private Label Sellers lead direct contact and info ✔️ Up to 30+ data points for each prospect ✔️ Sort your list by store size, product category, company location, and much more! ✔️ Enjoy a list that has been hand-researched and verified. No scrapped contacts! Buy B2B contact database with SellerDirectories.com, and get your B2B contacts database sorted!

Data includes: Seller ID Seller Business Model: Private Label Seller/Wholesaler Estimated Annual Revenue in $ ( accurate +/-30%) Annual Revenue Bracket [$] % of goods shipped in FBA Amazon Seller Page Seller Website Decision Maker First Name Decision Maker Last Name Direct Email Generic Email Office Phone Number Decision Maker Linkedin URL Seller Name Seller Storefront Link Seller Business Name Seller Business Full Address City State Zip Seller Business Country Number of Reviews [30 days] Number of Reviews [90 days] Number of Reviews [12 months] Number of Reviews [lifetime] Seller Rating Lifetime Total number of products Total number of brands Brands Top Product URL Top Product Shipping From Top Product Category Top Product SubCategory

About SellerDirectories: SellerDirectories.com provides human-researched and verified data on Amazon sellers and eCommerce Brands.

Our human-researched and verified data is trusted by companies like Walmart, Microsoft, Tencent, Helium10, and 250 more! ⭐ Check our verified 5-star reviews on Trustpilot ⭐ https://www.trustpilot.com/review/sellerdirectories.com ⭐

✅ Data Sources: Aggregated from 50+ sources

✅ Data Collection: Human Researched and verified (we don't like scrapped contact data)

✅ 98%+ accurate and up-to-date data (verified)

✅ Brand /seller Targeting Options: Multiple filters available (including revenue, location, business model, and product category)

✅ Customer Service: Lifetime support and accuracy guarantee on your list. Our lists include resources on how best to run outreach campaigns to turn a prospect list into actual business opportunities.

This dataset contains product reviews and metadata from Amazon, including 142.8 million reviews spanning May 1996 - July 2014.

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).

When sellers need help from Amazon, such as how to create a listing, they often reach out to Amazon seller support through email, chat or phone. For each contact, we assign an intent so that we can manage the request more easily. The data we present in this release includes 548k contacts with 118 intents from 70k sellers sampled from recent years. There are 3 columns. 1. De-identified seller id - seller_id_anon; 2. Noisy inter-arrival time in the unit of hour between contacts - interarrival_time_hr_noisy; 3. An integer that represents the contact intent - contact_intent. Note that, to balance the need between data anonymization and usefulness, we randomly perturbed the interarrival time in an intricate way such that the temporal pattern are preserved and seller identity are anonymized to the largest extent. We also note that for each seller_id_anon, the interarrival_time_hr_noisy are already arranged in chonological order, the first contact_intent_id_anon is always the origin when sellers begin to sell with us and the interarrival_time_hr_noisy for each seller_id_anon are all relative with respect to the previous contact. A straightforward use case of the data is to predict the next timestamp and intent of a user given the user's history.

Utilize our Amazon reviews dataset for diverse applications to enrich business strategies and market insights. Analyzing this dataset can aid in understanding customer behavior, product performance, and market trends, empowering organizations to refine their product and marketing strategies. Access the entire dataset or tailor a subset to fit your requirements. Popular use cases include: Product Performance Analysis: Analyze Amazon reviews to assess product performance, uncovering customer satisfaction levels, common issues, and highly praised features to inform product improvements and marketing messages. Customer Behavior Insights: Gain insights into customer behavior, purchasing patterns, and preferences, enabling more personalized marketing and product recommendations. Demand Forecasting: Leverage Amazon reviews to predict future product demand by analyzing historical review data and identifying trends, helping to optimize inventory management and sales strategies. Accessing and analyzing the Amazon reviews dataset supports market strategy optimization by leveraging insights to analyze key market trends and customer preferences, enhancing overall business decision-making.

Amazon dataset was retrieved from data.world, an open-access repository. Created by @revanthkrishnaa.The DataSet contains historical sales data for 45 Amazon stores located in different regions.Dataset DescriptionThe DataSet contains historical sales data for 45 Amazon stores located in different regions. Each store contains a number of departments, and have to predict the department-wide sales for each store.In addition, Amazon runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of which are the Super Bowl, Labor Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the Dataset is modeling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data.This file contains anonymized information about the 45 stores, indicating the type and size of store.This is the historical training data, which covers to 2019-02-05 to 2021-11-01. Within this file you following are the different fields:Store - the store numberDept - the department numberDate - the weekWeekly_Sales - sales for the given department in the given store IsHoliday - whether the week is a special holiday week Temperature - average temperature in the region Fuel_Price - cost of fuel in the regionMarkDown1-5 - anonymized data related to promotional markdowns that Amazon is running. MarkDown data is only available after Nov 2020 and is not available for all stores all the time. Any missing value is marked with an NA.CPI - the consumer price indexUnemployment - the unemployment rateFor convenience, the four holidays fall within the following weeks in the dataset (not all holidays are in the data):Super Bowl: 12-Feb-19, 11-Feb-20, 10-Feb-21, 8-Feb-18Labor Day: 10-Sep-19, 9-Sep-20, 7-Sep-21, 6-Sep-18Thanksgiving: 26-Nov-19, 25-Nov-20, 23-Nov-21, 29-Nov-18Christmas: 31-Dec-19, 30-Dec-20, 28-Dec-21, 27-Dec-18Show less

Generative AI is already employed at Amazon. In 2024, a bit more than one-third of Amazon’s sellers and brands created and optimized product listings with AI tools. Another 14 percent of them shifted from manual to AI-based production of marketing and social media content.

A work-in-progress situation

AI use at Amazon aligns with the general trend observed in the United States. In 2023, only one-third of B2C e-commerce companies fully implemented AI in their operations, while nearly half of them are still in the experimental phase. In comparison, B2B organizations were lagging, as the full implementation rate stood at 25 percent.

What holds companies back?

Implementing AI-based solutions is easier said than done, as companies face numerous challenges ranging from data security to significant business costs – the main factors retail CEOs mentioned in a survey from 2023. In the same survey, over four in ten managers and employees believed AI innovations were hindered by a lack of understanding and expertise in AI use.

Buy Amazon Fashion datasets and get access to millions of records from any Amazon domain. Gain insights on fashion products, sellers, and customer reviews.

PromptCloud offers cutting-edge data extraction services that empower businesses with real-time, actionable intelligence from the vast expanses of the online marketplace. We are committed to putting data at the heart of your business. Reach out for a no-frills PromptCloud experience- professional, technologically ahead and reliable.

Our Amazon Best Seller Products Dataset is a key tool for businesses looking to understand and capitalize on market trends. It allows you to identify top-selling products and sellers, and track their performance across various categories and subcategories. This dataset is invaluable for competitive intelligence, monitoring trending products, and understanding customer sentiment. It also plays a crucial role in monitoring competitor prices and enhancing product inventory, ensuring that your business stays relevant and competitive.

Beyond Amazon, PromptCloud offers access to a diverse range of Ecommerce Product Data from various e-commerce websites. PromptCloud is a leading provider of advanced web scraping services, uniquely tailored to meet the dynamic needs of modern businesses. Our services are fully customizable, allowing clients to specify source websites, data collection frequencies, data points, and delivery mechanisms to fit their unique requirements​​. The data aggregation feature of our web crawler enables the extraction of data from multiple sources in a single stream, catering to a diverse range of ecommerce clients.

PromptCloud is a leading provider of advanced web scraping services, uniquely tailored to meet the dynamic needs of modern businesses. Our services are fully customizable, allowing clients to specify source websites, data collection frequencies, data points, and delivery mechanisms to fit their unique requirements​​. The data aggregation feature of our web crawler enables the extraction of data from multiple sources in a single stream, catering to a diverse range of clients, from news aggregators to job boards​​.

With over a decade of experience in extracting web data from any e-commerce website, PromptCloud stands as a seasoned veteran in the field. This extensive experience translates into high-quality, reliable data extraction, making PromptCloud your ideal product web data extraction partner. The reliability of our data is uncompromised, with a 100% verification process that ensures accuracy and trustworthiness.

According to forecasts as of March 2022, the sales share of electrical products on Amazon was expected at 28.3 percent that year. By 2027, electrical products will make up 28.6 percent of Amazon sales. Additionally, fashion and apparel was forecast to make up 25.7 percent of Amazon sales by 2027, one percentage point higher than in 2022.

Amazon Berkeley Objects (ABO) is a collection of 147,702 product listings with multilingual metadata and 398,212 unique catalog images. 8,222 listings come with turntable photography (also referred as "spin" or "360º-View" images), as sequences of 24 or 72 images, for a total of 586,584 images in 8,209 unique sequences. For 7,953 products, the collection also provides high-quality 3d models, as glTF 2.0 files.

✔️ Easy-to-handle Excel Sheet ✔️ Human Researched and Verified leads with Direct contacts ✔️ Up to 🇨🇳 10K Chinese Active Amazon third-party private Label Sellers lead direct contact and info ✔️ Up to 30+ data points for each prospect ✔️ Sort your list by store size, product category, company location, and much more! ✔️ Enjoy a list that has been hand-researched and verified. No scrapped contacts!

Data includes: Seller ID Seller Business Model: Private Label Seller/Wholesaler Estimated Annual Revenue in $ ( accurate +/-30%) Annual Revenue Bracket [$] % of goods shipped in FBA Amazon Seller Page Seller Website Decision Maker First Name Decision Maker Last Name Direct Email Generic Email Office Phone Number Decision Maker Linkedin URL Seller Name Seller Storefront Link Seller Business Name Seller Business Full Address City State Zip Seller Business Country Number of Reviews [30 days] Number of Reviews [90 days] Number of Reviews [12 months] Number of Reviews [lifetime] Seller Rating Lifetime Total number of products Total number of brands Brands Top Product URL Top Product Shipping From Top Product Category Top Product SubCategory

About SellerDirectories: SellerDirectories.com provides human-researched and verified data on Amazon sellers and eCommerce Brands.

Our human-researched and verified data is trusted by companies like Walmart, Microsoft, Tencent, Helium10, and 250 more! ⭐ Check our verified 5-star reviews on Trustpilot ⭐ https://www.trustpilot.com/review/sellerdirectories.com ⭐

✅ Data Sources: Aggregated from 50+ sources

✅ Data Collection: Human Researched and verified (we don't like scrapped contact data)

✅ 98%+ accurate and up-to-date data (verified)

✅ Brand /seller Targeting Options: Multiple filters available (including revenue, location, business model, and product category)

✅ Customer Service: Lifetime support and accuracy guarantee on your list. Our lists include resources on how best to run outreach campaigns to turn a prospect list into actual business opportunities. Buy B2B contact database with SellerDirectories.com, and get your B2B contacts database sorted!

In 2024, Amazon's total consolidated net sales revenue amounted to 638 billion U.S. dollars, 143 billion U.S. dollars of which were generated through international revenue channels. North America was the biggest operations segment, accumulating nearly 388 billion U.S. dollars in net sales during the year. Sales activities Amazon appeals because it sells a wide range of products. Its departments include beauty, clothing, electronics, games and even wine, along with digital products and subscription services. In 2022, Amazon's largest revenue segment was online retail product sales with roughly 220 billion U.S. dollars in global net sales. Retail third-party seller services ranked second with nearly 118 billion U.S. dollars in sales. A weak spot Faster and more efficient delivery services come with a price. Data from the company's financial reports showed that Amazon's worldwide shipping costs amounted to a staggering 83.5 billion U.S. dollars, up from 76.7 billion U.S. dollars in 2021. Amazon's annual fulfillment expenses have also risen steadily, from 75.1 billion U.S. dollars in 2021 to over 84 billion U.S. dollars in 2022.

Get the needed Amazon product review data right from the data extractor! Collect Amazon review 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 Review dataset by: - keyword - category - seller - product ID (ASIN)

Amazon E-commerce Reviews Data datasets gathered by keyword, seller, category, or ASIN contain: - Product ID (can be extended to the full product information) - Review content and rating - Review metadata

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.

Amazon Review 2023 is an updated version of the Amazon Review 2018 dataset. This dataset mainly includes reviews (ratings, text) and item metadata (desc- riptions, category information, price, brand, and images). Compared to the pre- vious versions, the 2023 version features larger size, newer reviews (up to Sep 2023), richer and cleaner meta data, and finer-grained timestamps (from day to milli-second).

Amazon Review is a dataset to tackle the task of identifying whether the sentiment of a product review is positive or negative. This dataset includes reviews from four different merchandise categories: Books (B) (2834 samples), DVDs (D) (1199 samples), Electronics (E) (1883 samples), and Kitchen and housewares (K) (1755 samples).

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.