Dataset

This dataset was created by DEBJYOTI SAHA

Contents

Dataset

This dataset was created by Yash Joshi

Released under Apache 2.0

Contents

Dataset

This dataset was created by sannihith banala

Released under Apache 2.0

Contents

Dataset

This dataset was created by Parmeet Singh

Contents

View Amazon Services Amazon Customer import export trade data, including shipment records, HS codes, top buyers, suppliers, trade values, and global market insights.

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 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,...

View Amazon Customer import export trade data, including shipment records, HS codes, top buyers, suppliers, trade values, and global market insights.

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Context: In the ever-evolving world of e-commerce, Amazon.com stands as a pioneering giant. Known for its innovative spirit and remarkable journey, Amazon has not only experienced glorious heights but also faced intriguing challenges along the way. Here are some fascinating insights:

Dataset Overview:

Now, let's delve into the dataset at hand. It comprises an extensive collection of over 2 million customer reviews and ratings of beauty-related products available on Amazon's platform. The dataset includes valuable information such as:

Unique User IDs for customer identification. Product ASIN (Amazon's distinctive product identifier). Ratings, which reflect customer satisfaction on a scale from 1 to 5. Timestamps, recorded in UNIX time, indicating when the ratings were submitted. Acknowledgments: This dataset is just a fragment of the extensive Amazon product dataset, encompassing a staggering 142.8 million reviews spanning the period from May 1996 to July 2014. The complete dataset provides a wealth of information, including detailed product reviews, metadata, category information, pricing data, brand details, and even image features.

A Costly Downtime:

In August 2013, Amazon encountered a 40-minute website downtime, causing a notable loss of $4.8 million. This incident highlights the critical importance of maintaining a seamless online presence. The 1-Click Innovation:

Amazon's inventive prowess is exemplified by its patent on the "1-Click" buying feature. This technology was not only a game-changer for Amazon but is also licensed to other tech giants, including Apple. Warehouses on Steroids:

Amazon's Phoenix fulfillment center is a colossal structure, spanning a jaw-dropping 1.2 million square feet. It serves as a testament to the logistics marvel that powers the company's global operations. The Power of Recommendations:

Amazon leverages a robust recommendation engine that relies on customer ratings and purchase history to provide personalized product suggestions. This engine is pivotal in enhancing customer satisfaction and driving sales.

Inspiration: Now, the challenge lies in leveraging this condensed dataset to build a powerful recommendation engine. Can we tap into this data to create a recommendation system that mirrors the capabilities of Amazon's own engine? It's an exciting endeavor, and your innovative ideas and solutions are the driving force behind this exploration.

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.

We present a collection of Amazon reviews specifically designed to aid research in multilingual text classification. The dataset contains reviews in English, Japanese, German, French, Chinese and Spanish, collected between November 1, 2015 and November 1, 2019. Each record in the dataset contains the review text, the review title, the star rating, an anonymized reviewer ID, an anonymized product ID and the coarse-grained product category (e.g. 'books', 'appliances', etc.)

Delve into Comprehensive WebAutomation Dataset: Amazon Best Seller Products with Global Coverage

Explore the depths of eCommerce with our expansive WebAutomation dataset, meticulously curated to provide a comprehensive overview of Amazon's best seller products. With global coverage and an extensive array of data points, including pricing data, eCommerce product details, and seller ratings, our dataset empowers businesses and researchers to extract actionable insights and drive informed decision-making.

What Sets Us Apart:

• Global Coverage: Our dataset spans across various regions and countries, offering insights into Amazon's best seller products on a global scale. Whether you're interested in market trends in North America, Europe, Asia, or beyond, our dataset has you covered.

• Rich Pricing Data: Dive into detailed pricing information for a wide range of products, enabling precise analysis of pricing strategies, competitive landscapes, and market trends. With historical pricing data, track changes over time and identify patterns to inform pricing decisions.

• Comprehensive Product Details: Gain access to a wealth of eCommerce product details, including product descriptions, specifications, images, and customer reviews. Whether you're conducting market research, competitor analysis, or product development, our dataset provides the depth of information needed to make informed decisions.

• Seller Ratings Data: Understand the reputation and performance of sellers on Amazon with our seller ratings data. Evaluate seller reliability, customer satisfaction levels, and overall trustworthiness to guide partnership decisions and enhance the customer experience.

  Use Cases:

• Market Analysis: Analyze market trends, consumer preferences, and competitive landscapes to identify growth opportunities and strategic advantages.

• Price Optimization: Utilize pricing data and historical trends to optimize pricing strategies, maximize profitability, and stay competitive in the market.

• Product Development: Inform product development efforts by leveraging comprehensive product details and customer feedback to identify gaps in the market and tailor offerings to meet customer needs.

• Partnership Evaluation: Evaluate seller ratings and performance metrics to make informed decisions when selecting partners and suppliers, ensuring a seamless and trustworthy customer experience.

  Unlock the Power of Data:

Empower your business with actionable insights derived from our WebAutomation dataset. Whether you're a market researcher, business analyst, or eCommerce professional, our dataset provides the tools and resources needed to stay ahead in today's dynamic marketplace.

The research explores artificial intelligence (AI) effects on Amazon's customer data analysis as the global e-commerce leader. The research used a mixed-methods approach to study how Amazon's 2023 AI-driven analytics platform affected customer experience and both operational efficiency and business performance. The research demonstrates how artificial intelligence (AI) improves personalization while optimizing supply chain logistics and elevating customer satisfaction through empirical data analysis combined with industry reports and theoretical models such as DIKW hierarchy and CRISP-DM framework. The research identifies important managerial consequences together with ethical issues and provides strategic guidance for the sustainable implementation of AI technology. The research findings advance the discussion about AI benefits within big data environments while offering a practical blueprint for customer-oriented businesses in the digital transformation process.

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns : marketplace - 2 letter country code of the marketplace where the review was written. customer_id - Random identifier that can be used to aggregate reviews written by a single author. review_id - The unique ID of the review. product_id - The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id. product_parent - Random identifier that can be used to aggregate reviews for the same product. product_title - Title of the product. product_category - Broad product category that can be used to group reviews (also used to group the dataset into coherent parts). star_rating - The 1-5 star rating of the review. helpful_votes - Number of helpful votes. total_votes - Number of total votes the review received. vine - Review was written as part of the Vine program. verified_purchase - The review is on a verified purchase. review_headline - The title of the review. review_body - The review text. review_date - The date the review was written.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('amazon_us_reviews', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

Dataset

This dataset was created by Yash Joshi

Released under CC0: Public Domain

Contents

Unlock powerful insights with the Amazon Prime dataset, offering access to millions of records from any Amazon domain. This dataset provides comprehensive data points such as product titles, descriptions, exclusive Prime discounts, brand details, pricing (initial and discounted), availability, customer ratings, reviews, and product categories. Additionally, it includes unique identifiers like ASINs, images, and seller information, allowing you to analyze Prime offerings, trends, and customer preferences with precision. Use this dataset to optimize your eCommerce strategies by analyzing Prime-exclusive pricing strategies, identifying top-performing brands and products, and tracking customer sentiment through reviews and ratings. Gain valuable insights into consumer demand, seasonal trends, and the impact of Prime discounts to make data-driven decisions that enhance your inventory management, marketing campaigns, and pricing strategies. Whether you’re a retailer, marketer, data analyst, or researcher, the Amazon Prime dataset empowers you with the data needed to stay competitive in the dynamic eCommerce landscape. Available in various formats such as JSON, CSV, and Parquet, and delivered via flexible options like API, S3, or email, this dataset ensures seamless integration into your workflows.

In 2024, when it came to usage of consumer electronics online shops in the United States, Amazon was leading the way with 61 percent of respondents stating that they used the brand in the past 12 months. Second was Walmart, with 45 percent of people reporting to use the online shop.

The Measurable AI Amazon Consumer Transaction Dataset is a leading source of email receipts and consumer transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan) - EMEA (Spain, United Arab Emirates)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

In late 2020, Hispanic and African American consumers each accounted for nearly a tenth all Amazon retail spending in the United States. Meanwhile, white consumers led the list, representing over ** percent of the e-commerce platform's consumer spending share.

Unlock powerful insights with the Amazon Electronics dataset, offering access to millions of records from any Amazon domain. This dataset provides comprehensive data points such as product titles, descriptions, brand details, pricing (initial and discounted), availability, customer ratings, reviews, and product categories. Additionally, it includes unique identifiers like ASINs, images, and seller information, allowing you to analyze product listings, trends, and customer preferences with precision. Use this dataset to optimize your eCommerce strategies by benchmarking competitor pricing, identifying top-performing brands, and tracking customer sentiment through reviews and ratings. Gain valuable insights into consumer demand, seasonal trends, and market gaps to make data-driven decisions that enhance your inventory management, marketing campaigns, and pricing strategies. Whether you’re a retailer, marketer, data analyst, or researcher, the Amazon Electronics dataset empowers you with the data needed to stay competitive in the dynamic eCommerce landscape. Available in various formats such as JSON, CSV, and Parquet, and delivered via flexible options like API, S3, or email, this dataset ensures seamless integration into your workflows.