Context

This is a pre-crawled dataset, taken as subset of a bigger dataset (more than 115k products) that was created by extracting data from Amazon.com.

Content

This dataset has following fields:

• product_name
• manufacturer - The item manufacturer, as reported on Amazon. Some common "manufacturers", like Disney, actually outsource their assembly line.
• price
• number_available_in_stock
• number_of_reviews
• number_of_answered_questions - Amazon includes a Question and Answer service on all or most of its products. This field is a count of how many questions that were asked actually got answered.
• average_review_rating
• amazon_category_and_sub_category - A tree-based, >>-delimited categorization for the item in question.
• customers_who_bought_this_item_also_bought - References to other items that similar users bought. This is a recommendation engine component that played a big role in making Amazon popular initially.
• description
• product_information
• product_description
• items_customers_buy_after_viewing_this_item
• customer_questions_and_answers - A string entry with all of the product's JSON question and answer pairs.
• customer_reviews - A string entry with all of the product's JSON reviews.
• sellers - A string entry with all of the product's JSON seller information (many products on Amazon are sold by third parties).

Acknowledgements

This dataset was created by PromptCloud's in-house web-crawling service.

Inspiration

This detailed dataset can be used to answer questions like:

• What types of toys are most popular on Amazon?

• How dominant are brands in the Amazon toy market?

• Can you break down reviews to analyze their sentiment and contents?