One of the most important problems in e-commerce is the correct calculation of the points given to the products after sales. The solution to this problem means providing greater customer satisfaction for the e-commerce site, prominence of the product for the sellers and a seamless shopping experience for the buyers. Another problem is the correct ordering of the comments given to the products. Since misleading comments will directly affect the sale of the product, it will cause both financial loss and loss of customers. In the solution of these 2 basic problems, e-commerce site and sellers will increase their sales, while customers will complete their purchasing journey without any problems.

This dataset containing Amazon Product Data includes product categories and various metadata. The product with the most comments in the electronics category has user ratings and comments.

Business Problem: One of the most important problems in e-commerce is the correct calculation of the points given to the products after sales. The solution to this problem means providing greater customer satisfaction for the e-commerce site, prominence of the product for the sellers and a seamless shopping experience for the buyers. Another problem is the correct ordering of the comments given to the products. The prominence of misleading comments will cause both financial loss and loss of customers. In the solution of these 2 basic problems, while the e-commerce site and the sellers will increase their sales, the customers will complete the purchasing journey without any problems.

Dataset Story: This dataset containing Amazon Product Data includes product categories and various metadata. The product with the most comments in the electronics category has user ratings and comments.

reviewerID: User Id
asin: Product Id
reviewerName: User Name
helpful: Useful Evaluation Degree
reviewText: Evaluation
overall: Product Rating
summary: Evaluation Summary
unixReviewTime: Evaluation Time
reviewTime: Evaluation Time {RAW}
days - day_diff: Number of days since assessment
helpful_yes: The number of times the evaluation was found useful
total_vote: Number of votes given to the evaluation