• 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

Tap into the power of verified Amazon sellers with our Amazon Sellers Email List, designed to help businesses connect with top eCommerce merchants. Access crucial details like Seller Name, Business Name, Contact Email, Phone Number, Revenue Size, Employee Size, and more. Enhance your marketing campaigns with highly targeted Amazon seller data, ensuring accurate outreach and increased conversions. Whether you're looking to partner with high-volume Amazon sellers or drive B2B sales, this list provides the right data to meet your goals. Key Highlights: ✅ 250K+ Amazon Sellers Worldwide ✅ Direct Contact Info for Amazon Store Owners ✅ 40+ Data Points ✅ Lifetime Access ✅ 10+ Data Segmentations ✅ FREE Sample Data

Over 2 million sellers of 10 European Amazon marketplaces: (Italy, France, Spain, Germany, Belgium, Greece, Czech, Poland, Croatia and the United Kingdom.

• The data can be customized to your filtering criteria and needs.

Fields available: • Seller URL • Seller ID • Store Name • Main Category • Brand owner • FBA Seller • Experience on Amazon • Orders • Business Name • Full Business Address • Country • State/Province • ZIP Code • City • Owner first name • Owner last name • Owner email • Email - company • Website • Star rating • Percentage of positive reviews • Lifetime number of seller ratings • Number of products listed • Brands listed • Number of brands listed

Pricing (no order minimums): • <500 leads: $0.59 per lead • 501-5000 leads: $0.39 per lead • 5000+ leads: $0.29 per lead

We update our seller database every month to keep the data current.

Unlock a wealth of business insights with our expansive dataset, meticulously tailored for both Amazon and non-Amazon sellers. Boasting over 1 million contacts, this comprehensive resource is characterized by unparalleled verification precision, ensuring the inclusion of verified emails and direct dials for decision-makers across the spectrum.

Unique Features: - Unrivaled Scale: 1M+ Contacts: A vast reservoir of contacts, offering a rich tapestry of data for comprehensive analysis. - Verification Precision: Rigorous validation processes guarantee accurate and up-to-date information, with a focus on verified emails and direct dials.

Data Sourcing: - Multi-Faceted Approach: We employ an advanced methodology, combining cutting-edge web scraping techniques, access to public records, and strategic partnerships with trusted data providers. This multi-faceted approach ensures a robust and diverse dataset. - Reliability Assurance: Regular updates and continuous monitoring practices are in place to maintain the highest standards of data quality, providing users with a dependable foundation for their strategic initiatives.

Primary Use-Cases: - Market Research: Gain deep insights into market trends, customer behavior, and competitive landscapes. - Lead Generation: Target decision-makers with precision, enhancing conversion rates. - Marketing Campaigns: Craft tailored strategies based on comprehensive data, ensuring maximum impact. - Competitive Analysis: Evaluate market positioning and identify strategic opportunities through detailed competitor insights.

Integration with Broader Offering: - Diverse Data Portfolio: Seamlessly integrates into our comprehensive data catalog, enhancing our commitment to providing a diverse, accurate, and scalable range of datasets. - Complementary Advantages: This dataset synergizes with our broader offering, providing users with a holistic solution for their data needs.

Coverage: - Global Reach: Encompassing multiple industries and countries, our dataset offers a global perspective for businesses seeking to expand their reach and explore new markets. - Strategic Expansion: Equip your business with the tools needed to navigate global markets confidently, with insights tailored to your expansion strategies.

Scale and Quality Indicators: - Superior Data Quality: Rigorous validation processes ensure the highest standards of precision and reliability. - Scalability: Adaptable to diverse business needs, accommodating various use cases and scenarios.

Target Audience: - E-commerce Players: Elevate your market presence and competitiveness in the dynamic e-commerce landscape. - Marketing Agencies: Craft targeted campaigns with confidence, backed by comprehensive and reliable data. - Business Intelligence Professionals: Gain deep market insights to inform strategic planning and decision-making.

Unveiling Opportunities: - Catalyst for Growth: Discover new markets and unearth business prospects. - Competitive Edge: Outpace competition by utilizing insights from our curated dataset.

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.

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.

Over 2 million sellers of 10 European Amazon marketplaces: (Italy, France, Spain, Germany, Belgium, Greece, Czech, Poland, Croatia and the United Kingdom.

• The data can be customized to your filtering criteria and needs.

Fields available: • Seller URL • Seller ID • Store Name • Main Category • Brand owner • FBA Seller • Experience on Amazon • Orders • Business Name • Full Business Address • Country • State/Province • ZIP Code • City • Owner first name • Owner last name • Owner email • Email - company • Website • Star rating • Percentage of positive reviews • Lifetime number of seller ratings • Number of products listed • Brands listed • Number of brands listed

Pricing (no order minimums): • <500 leads: $0.59 per lead • 501-5000 leads: $0.39 per lead • 5000+ leads: $0.29 per lead

We update our seller database every month to keep the data current.

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 Products dataset to explore detailed product listings, pricing, reviews, and sales data. Popular use cases include competitive analysis, market trend forecasting, and e-commerce strategy optimization.

Use our Amazon Products dataset to explore detailed information on products across various categories, including pricing, reviews, ratings, and sales data. This dataset is ideal for e-commerce professionals, market analysts, and product managers looking to analyze market trends, optimize product listings, and refine competitive strategies.

Leverage this dataset to track pricing trends, assess customer feedback, and uncover popular product categories. Whether you're conducting competitive analysis, performing market research, or optimizing product strategies, the Amazon Products dataset provides key insights to stay ahead in the e-commerce landscape.

Dataset Features

• Title: The name or title of the product.
• seller_name: The name of the seller offering the product.
• Brand: The brand associated with the product.
• Description: A detailed description of the product, including key features.
• initial_price: The original price of the product before any discounts.
• final_price: The current price of the product after discounts.
• Currency: The currency in which the product is priced (e.g., GBP, USD).
• Availability: The stock status (e.g., in stock, out of stock).
• reviews_count: The total number of customer reviews.
• Categories: The specific category the product belongs to.
• asin: Amazon Standard Identification Number.
• buybox_seller: The seller currently winning the Amazon Buy Box.
• number_of_sellers: The number of sellers offering this product.
• root_bs_rank: The overall ranking of the product in the Amazon best-sellers list.
• answered_questions: The number of questions answered in the product Q&A section.
• domain: The website domain where the product is being sold.
• images_count: The number of images available for the product.
• URL: The link to the product page on Amazon.
• video_count: The number of videos available for the product.
• image_url: The URL of the primary image associated with the product.
• item_weight: The weight of the product.
• Rating: The average rating of the product based on customer reviews.
• product_dimensions: The dimensions of the product (e.g., length, width, height) and weight.
• seller_id: The unique identifier for the seller.
• date_first_available: The date when the product was first made available on Amazon.
• discount: Any discount applied to the product.
• model_number: The model number of the product.
• manufacturer: The company that manufactures the product.
• department: The department under which the product is categorized (e.g., Health & Household).
• plus_content: A flag indicating if the product has Amazon’s “Plus Content” (additional marketing content).
• upc: The Universal Product Code (UPC) associated with the product.
• video: URL(s) of any video content associated with the product.
• top_review: A summary or excerpt from the top customer review.
• variations: Different product variations (e.g., different sizes or flavors).
• delivery: Information on the delivery options (e.g., free delivery or Prime delivery).
• features: Key features or highlights of the product.
• format: The format of the product (e.g., powder, liquid).
• buybox_prices: Pricing details for the product, including the base and tiered prices.
• parent_asin: The ASIN of the parent product (if the product is part of a larger group of similar products).
• input_asin: The ASIN of the product as input for Amazon searches.
• ingredients: List of ingredients in the product (if applicable).
• origin_url: The source URL for product-related information or ingredients.
• bought_past_month: A flag indicating if the product was bought in the past month.
• is_available: Availability status of the product (True/False).
• root_bs_category: The broad product category (e.g., Health & Household).
• bs_category: The specific subcategory the product belongs to.
• bs_rank: The rank of the product in its specific subcategory.
• badge: Any badge or label the product has earned (e.g., Amazon's Choice).
• subcategory_rank: The rank of the product within its subcategory.
• amazon_choice: A flag indicating if the product has been selected as Amazon’s Choice.
• images: A list of URLs for additional product images.
• product_details: Detailed product specifications and features.
• prices_breakdown: A breakdown of the price, including any discounts or promotions.
• country_of_origin: The country where the product is made.
• from_the_brand: Information from the brand or manufact

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

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.

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.

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).

Amazon Sales Report

Overview:

This dataset provides detailed sales data from Amazon, offering a comprehensive look at various product categories and their performance over time. It includes information on sales figures, order details, product categories, and customer demographics.

Features:

1. Order ID

Description: A unique identifier for each order placed on Amazon. This field helps to track individual orders and link related records.

2. Dates

Description: The date when the order was placed. This field is crucial for analyzing sales trends over time and identifying seasonal patterns.

3. Status

Description: The current status of the order (e.g., Shipped, Delivered, Pending). This field provides insight into the order fulfillment process and helps monitor order processing efficiency.

4. Fulfillment

Description: Indicates the method used to fulfill the order (e.g., Fulfilled by Amazon, Fulfilled by Seller). This feature helps in analyzing the performance of different fulfillment methods and their impact on customer satisfaction.

5. Sales Channel

Description: The channel through which the sale was made (e.g., Amazon Website, Mobile App). This field is useful for evaluating the effectiveness of different sales channels and understanding customer preferences.

6. Category

Description: The product category to which the purchased item belongs (e.g., Electronics, Clothing, Home Goods). This feature aids in analyzing sales performance across various product categories.

7. Ship Service Level

Description: The shipping service level selected for the order (e.g., Standard Shipping, Two-Day Shipping). This field helps to assess the impact of shipping options on delivery times and customer satisfaction.

8. Size

Description: The size of the product ordered (e.g., Small, Medium, Large). This feature is relevant for analyzing sales performance based on product size and understanding inventory requirements.

9. Carrier Status

Description: The status of the shipment with the carrier (e.g., In Transit, Delivered, Returned). This field provides insights into the shipping process and helps in monitoring delivery performance and handling returns.

Use Cases:

Sales Analysis:

Examine trends in sales over time, identify peak periods, and analyze performance by product category.

Customer Insights:

Explore customer demographics to understand purchasing behavior and preferences.

Inventory Management:

Assess which products are performing well and which are not, aiding in inventory and supply chain management.

Marketing Strategies:

Develop targeted marketing campaigns based on sales trends and customer profiles.

Data Source:

This dataset is a simulated collection of Amazon sales data and is intended for educational and analytical purposes.

Acknowledgments:

This dataset was created to facilitate data analysis and machine learning projects. It is ideal for practicing data manipulation, statistical analysis, and predictive modeling.

What is this?

This is a cleaned version of Amazon Product Dataset 2020 from Kaggle.

  Why?

Using via Hugging Face API is easier; Kaggle API is annoying because their authentication is having credentials in a folder. Cleaned because 13/28 columns are empty.

Auto-generated structured data of Amazon Seller Central (Amazon SP) Field Reference from table Fields

**# 📌 Dataset Description for Kaggle: Amazon Best Sellers Data

**📖 Overview

This dataset contains real-time Amazon Best Sellers data across multiple countries and categories, specifically focusing on Software products. The data is collected via an API and includes details such as product titles, prices, star ratings, number of reviews, and rank changes.

With this dataset, you can analyze trending products, pricing strategies, and customer preferences across different regions. It is useful for market analysis, competitor research, and e-commerce insights.

📊 Dataset Contents

Each row in this dataset represents a top-selling software product on Amazon for a specific country. The dataset includes the following columns:

product_title 🏷️ – Name of the product product_price 💰 – Price of the product in the respective country’s currency product_star_rating ⭐ – Average star rating of the product product_num_ratings 📝 – Total number of customer reviews rank 🔢 – Current ranking of the product in the Best Sellers list country 🌍 – The country where the ranking is recorded

🎯 Potential Use Cases

✅ E-commerce Market Analysis – Identify top-selling software products in different regions. ✅ Pricing Strategy Optimization – Compare prices across markets and track fluctuations. ✅ Customer Sentiment Analysis – Analyze customer ratings and review trends. ✅ Competitor Research – Understand how products rank in different countries. ✅ Trend Forecasting – Observe rank changes and predict upcoming best-sellers.

Fast and Reliable real-time API access to Amazon Data with 300M+ Product Listings, including extensive Product Details, Product Reviews, All Product Offers, Amazon Best Sellers, Deals, ASIN to GTIN/EAN conversion, 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.

About this Dataset

You will get an active email list for real and active buyers who make regular purchases through Amazon and other e-commerce sites. This email list contains 100% original email address. You can also use these emails to increase visits to your website, blog, or YouTube channel. I offer you now, a great treasure to use whenever you want.

So don't waste your time and start boosting your ecommerce business online.

The buyers will be from:

United States of America Canada Europe Union

$ There are no duplicate emails $ No fake IDs $ Audiences ready to buy

Category

Markets

Keywords

market,emails,email ma,list,buyer

Row Count

70150

Price

$90.00