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.

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.

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.

1) Data Introduction • The Amazon Products Sales Dataset 2023 is a large e-commerce dataset that summarizes various product information in a tabular format, including product name, price, rating, discount information, images, and links by 142 major categories collected from Amazon's website.

2) Data Utilization (1) Amazon Products Sales Dataset 2023 has characteristics that: • Each row contains 10 key attributes, including product name, main/subcategory, image, Amazon link, rating, number of ratings, discount price, and actual price. • The data encompasses a wide range of products and is structured to enable multi-faceted analysis such as price policy, customer evaluation, and trend by category. (2) Amazon Products Sales Dataset 2023 can be used to: • Product Recommendation and Marketing Strategy: Use rating, price, and category data to develop a customized recommendation system, analyze popular products, and establish a category-specific marketing strategy. • Price and Discount Policy Analysis—Based on discounted prices and actual prices, ratings, reviews, etc., it can be applied to effective pricing policies, promotion strategies, market competitiveness analyses, 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.

Explore our extensive Amazon Product Dataset, featuring detailed information on prices, ratings, sales volume, and more.

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

Between 2023 and 2024, it is forecast that Amazon's share of total e-commerce sales in the United States will increase across all five featured product categories. Health and personal care will see the greatest growth, rising from **** percent to **** percent. The other categories include electronics, office items, clothing and home furnishings. With a market share projected to hit almost ** percent in 2024, Amazon dominates the electronics online retail space in the United States.

E-Commerce Sales Dataset

Analyzing and Maximizing Online Business Performance

By ANil [source]

About this dataset

This dataset provides an in-depth look at the profitability of e-commerce sales. It contains data on a variety of sales channels, including Shiprocket and INCREFF, as well as financial information on related expenses and profits. The columns contain data such as SKU codes, design numbers, stock levels, product categories, sizes and colors. In addition to this we have included the MRPs across multiple stores like Ajio MRP , Amazon MRP , Amazon FBA MRP , Flipkart MRP , Limeroad MRP Myntra MRP and PaytmMRP along with other key parameters like amount paid by customer for the purchase , rate per piece for every individual transaction Also we have added transactional parameters like Date of sale months category fulfilledby B2b Status Qty Currency Gross amt . This is a must-have dataset for anyone trying to uncover the profitability of e-commerce sales in today's marketplace

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How to use the dataset

This dataset provides a comprehensive overview of e-commerce sales data from different channels covering a variety of products. Using this dataset, retailers and digital marketers can measure the performance of their campaigns more accurately and efficiently.

The following steps help users make the most out of this dataset: - Analyze the general sales trends by examining info such as month, category, currency, stock level, and customer for each sale. This will give you an idea about how your e-commerce business is performing in each channel.
- Review the Shiprocket and INCREF data to compare and analyze profitability via different fulfilment methods. This comparison would enable you to make better decisions towards maximizing profit while minimizing costs associated with each method’s referral fees and fulfillment rates.
- Compare prices between various channels such as Amazon FBA MRP, Myntra MRP, Ajio MRP etc using the corresponding columns for each store (Amazon MRP etc). You can judge which stores are offering more profitable margins without compromising on quality by analyzing these pricing points in combination with other information related to product sales (TP1/TP2 - cost per piece).
- Look at customer specific data such as TP 1/TP 2 combination wise Gross Amount or Rate info in terms price per piece or total gross amount generated by any SKU dispersed over multiple customers with relevant dates associated to track individual item performance relative to others within its category over time periods shortlisted/filtered appropriately.. Have an eye on items commonly utilized against offers or promotional discounts offered hence crafting strategies towards inventory optimization leading up-selling operations.?
- Finally Use Overall ‘Stock’ details along all the P & L Data including Yearly Expenses_IIGF information record for takeaways which might be aimed towards essential cost cutting measures like switching amongst delivery options carefully chosen out of Shiprocket & INCREFF leadings away from manual inspections catering savings under support personnel outsourcing structures.?

By employing a comprehensive understanding on how our internal subsidiaries perform globally unless attached respective audits may provide us remarkably lower operational costs servicing confidence; costing far lesser than being incurred taking into account entire pallet shipments tracking sheets representing current level supply chains efficiencies achieved internally., then one may finally scale profits exponentially increases cut down unseen losses followed up introducing newer marketing campaigns necessarily tailored according playing around multiple goods based spectrums due powerful backing suitable transportation boundaries set carefully

Research Ideas

• Analysing the difference in profitability between sales made through Shiprocket and INCREFF. This data can be used to see where the biggest profit margins lie, and strategize accordingly.
• Examining the Complete Cost structure of a product with all its components and their contribution towards revenue or profitability, i.e., TP 1 & 2, MRP Old & Final MRP Old together with Platform based MRP - Amazon, Myntra and Paytm etc., Currency based Profit Margin etc.
• Building a predictive model using Machine Learning by leveraging historical data to predict future sales volume and profits for e-commerce products across multiple categories/devices/platforms such as Amazon, Flipkart, Myntra etc as well providing m...

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,...

OpenWeb 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.

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.

• 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

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.

Real-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.

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.

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.

Over the course of 2024, in the United States, the retailer market share of home improvement sales on Amazon varied. The retailer market share started at just over 14 percent at the beginning of the year. Throughout the year, the market share fell, before rising to around 18 percent in the last month of the year.

APISCRAPY'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