Improving sales forecasting models by integrating customers’ feedbacks: a case study of fashion products

Abstract

Potential consumers commonly examine online customers’ reviews before deciding buying the products. There are two types of reaction having in Shopee platform known as customer’ reviews and rating. While customer’ reviews are feedback of customers in text, icon which express their feelings after receiving package, rating of item is considered to make before purchasing goods, meaning there is a variety of ways depend of seller of each shop to hack this unreasonable reaction. Moreover, in case of fetching comments in my research, there are a large amount of comment crawled null and only has rating score since at time tool crawler processed, customers could remove that comment. Therefore, it is essential to remove rating feature in integrating with sentiment and daily quantity sold for sales forecasting in order to decrease noisy data.