Learning Reasons for Product Returns on E-Commerce

Miriam Farber, Slava Novgorodov, Ido Guy


Abstract
In the rapidly evolving landscape of e-commerce, product returns have become a significant economic burden for businesses, where the reasons for returns may vary from wrong sizing and defective products to simply no longer needing the purchased product. This paper presents, to the best of our knowledge, the first comprehensive study of the complexities of product returns across a variety of e-commerce domains, focusing on the task of predicting the return reason. We propose a supervised approach for predicting return likelihood and the underlying return reason. We test our approach over a real-world dataset from a large e-commerce platform.
Anthology ID:
2024.ecnlp-1.1
Volume:
Proceedings of the Seventh Workshop on e-Commerce and NLP @ LREC-COLING 2024
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Shervin Malmasi, Besnik Fetahu, Nicola Ueffing, Oleg Rokhlenko, Eugene Agichtein, Ido Guy
Venues:
ECNLP | WS
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
1–7
Language:
URL:
https://aclanthology.org/2024.ecnlp-1.1
DOI:
Bibkey:
Cite (ACL):
Miriam Farber, Slava Novgorodov, and Ido Guy. 2024. Learning Reasons for Product Returns on E-Commerce. In Proceedings of the Seventh Workshop on e-Commerce and NLP @ LREC-COLING 2024, pages 1–7, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Learning Reasons for Product Returns on E-Commerce (Farber et al., ECNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.ecnlp-1.1.pdf