Context

Amazon.com is one of the largest electronic commerce and cloud computing companies.

Just a few Amazon related facts

• They lost $4.8 million in August 2013, when their website went down for 40 mins.
• They hold the patent on 1-Click buying, and licenses it to Apple.
• Their Phoenix fulfilment centre is a massive 1.2 million square feet.

Amazon relies heavily on a Recommendation engine that reviews customer ratings and purchase history to recommend items and improve sales.

Content

This is a dataset related to over 2 Million customer reviews and ratings of Beauty related products sold on their website.

It contains

• the unique UserId (Customer Identification),
• the product ASIN (Amazon's unique product identification code for each product),
• Ratings (ranging from 1-5 based on customer satisfaction) and
• the Timestamp of the rating (in UNIX time)

Acknowledgements

A description of the entire Amazon products dataset.

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).

For the complete dataset check out Amazon Product Data

Inspiration

Can a good Recommendation engine be created from this minimal dataset?

Give it a try!

If you have got any more cool Amazon facts, dataset or queries, just drop a comment.