Ecommerce Product Review Dataset | Amazon reviews | Web Scraped Data

Ecommerce Product Review Dataset | Amazon reviews | Web Scraped Data

Our Ecommerce Product Review Dataset, scraped from platforms like Amazon Flipkart, JD and more, is a valuable resource for AI-powered analysis in the e-commerce domain. This comprehensive dataset encompasses a wide range of product reviews and associated data, enabling businesses to train AI models for sophisticated analysis and valuable insights. By leveraging this dataset, organizations can develop AI algorithms that perform sentiment analysis, feature identification, and pattern recognition to understand customer preferences and make data-driven decisions. With reviews from diverse sources and platforms, including Amazon, the dataset offers a comprehensive collection of customer opinions across various product categories. It empowers businesses to gain a deep understanding of customer sentiments, refine product offerings, optimize marketing strategies, and enhance the overall customer experience.

Volume: On-Demand

Available Formats: json, csv, xml

Coverage: More than 249 countries

Ecommerce Product Review Dataset | Amazon reviews | Web Scraped Data

Our dataset encompasses a range of valuable features that enhance its usability for AI-powered analysis. It includes essential components such as the review content, rating, customer name, and date for each review, if available. These attributes provide crucial information for conducting comprehensive analyses of customer feedback. The review content allows for sentiment analysis, feature identification, and other text-based analyses, while the rating offers a quantitative measure of customer satisfaction. The customer name and date provide additional context, enabling chronological analysis and identifying individual customer preferences and trends over time. Furthermore, the dataset accommodates any additional details associated with the reviews, which could include aspects such as product specifications, purchase details, or specific comments provided by customers

Use Cases
  • Review Analysis
  • Sentiment Analysis
  • Customer Feedback Analysis
  • Natural language processing
  • Data Extraction
  • Ecommerce Data
  • Product Review Data
  • Machine Learning (ML) Data

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