Instant Answering in E-Commerce Buyer-Seller Messaging using Message-to-Question Reformulation
This addresses the cost and delay in buyer-seller messaging for e-commerce platforms, though it is an incremental improvement using a novel method for a known bottleneck.
The paper tackled the problem of automating responses to detailed buyer inquiries in e-commerce by reformulating messages into succinct questions, resulting in a 757% increase in question understanding and a 1,746% increase in answering rate.
E-commerce customers frequently seek detailed product information for purchase decisions, commonly contacting sellers directly with extended queries. This manual response requirement imposes additional costs and disrupts buyer's shopping experience with response time fluctuations ranging from hours to days. We seek to automate buyer inquiries to sellers in a leading e-commerce store using a domain-specific federated Question Answering (QA) system. The main challenge is adapting current QA systems, designed for single questions, to address detailed customer queries. We address this with a low-latency, sequence-to-sequence approach, MESSAGE-TO-QUESTION ( M2Q ). It reformulates buyer messages into succinct questions by identifying and extracting the most salient information from a message. Evaluation against baselines shows that M2Q yields relative increases of 757% in question understanding, and 1,746% in answering rate from the federated QA system. Live deployment shows that automatic answering saves sellers from manually responding to millions of messages per year, and also accelerates customer purchase decisions by eliminating the need for buyers to wait for a reply