Best Seller Rank (BSR) to Sales: An empirical look at Amazon.com
Publication Date
12-1-2020
Document Type
Conference Proceeding
Publication Title
2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C)
DOI
10.1109/QRS-C51114.2020.00104
First Page
609
Last Page
615
Abstract
The market size of e-commerce continued to grow in recent years. Amazon, a leading technology company that provides reliable online marketplaces had attracted more than two million active sellers with over 600 million active products listed on it in a snapshot in 2019. The Amazon Best Sellers Rank (BSR) is an important indicator of how well the listed product is sold and it is a common interest to all sellers. This research investigates the algorithm for setting BSR on Amazon by developing a python-based web scrapper to collect hourly data on Amazon Web Services (AWS) server. A BSR to sales mapping study is performed using a machine learning regression algorithm. The study would help Amazon sellers to understand the mechanism of BSR and its impact on future sales.
Funding Number
61877044
Funding Sponsor
National Natural Science Foundation of China
Keywords
Amazon, Best Seller Rank, e-commerce, forecasting, online marketplace
Department
Industrial and Systems Engineering
Recommended Citation
Amit Sharma, Hongrui Liu, and Hongwei Liu. "Best Seller Rank (BSR) to Sales: An empirical look at Amazon.com" 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C) (2020): 609-615. https://doi.org/10.1109/QRS-C51114.2020.00104
