ReducE-Comm: Effective inventory reduction system for e-commerce

Shay Gershtein, Tova Milo, Slava Novgorodov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many e-commerce platforms serve as an intermediary between companies/manufacturers and consumers, receiving a commission per purchase. To increase revenue, such sites tend to offer a wide variety of items. However, in many situations a smaller subset of the items should be selected and offered for sale, e.g., when opening an express branch or expanding to a new region, or when maintenance costs become prohibitive and redundant items should be disposed of. In all these cases selecting a reduced inventory which covers most consumer needs is an important goal. In this demo we introduce ReducE-Comm - a highly parallelizable and scalable system that given a large set of items, a bound on the number of items that can be supported and information about consumer preferences/items relationships, allows to select a subset of the items which maximizes the likelihood of a purchase. Our system is interactive and facilitates real-time analysis, by providing detailed per-item impact statistics. We demonstrate the effectiveness of ReducE-Comm on real-world data and scenarios taken from a large e-commerce system, by interacting with the CIKM'19 audience who act as analysts aiming to intelligently reduce the inventory.

Original languageEnglish
Title of host publicationCIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages2957-2960
Number of pages4
ISBN (Electronic)9781450369763
DOIs
StatePublished - 3 Nov 2019
Event28th ACM International Conference on Information and Knowledge Management, CIKM 2019 - Beijing, China
Duration: 3 Nov 20197 Nov 2019

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference28th ACM International Conference on Information and Knowledge Management, CIKM 2019
Country/TerritoryChina
CityBeijing
Period3/11/197/11/19

All Science Journal Classification (ASJC) codes

  • General Decision Sciences
  • General Business,Management and Accounting

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