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Summary of Optimizing Item-based Marketing Promotion Efficiency in C2c Marketplace with Dynamic Sequential Coupon Allocation Framework, by Jie Yang et al.


Optimizing Item-based Marketing Promotion Efficiency in C2C Marketplace with Dynamic Sequential Coupon Allocation Framework

by Jie Yang, Padunna Valappil Krishnaraj Sekhar, Sho Sekine, Yilin Li

First submitted to arxiv on: 13 Sep 2024

Categories

  • Main: Machine Learning (cs.LG)
  • Secondary: None

     Abstract of paper      PDF of paper


GrooveSquid.com Paper Summaries

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Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
This paper explores ways to improve e-commerce transactions by optimizing coupon strategies for customer-to-customer marketplaces. The researchers highlight the importance of balancing buyer and seller satisfaction, as current marketing approaches tend to focus on buyers alone. They also point out that existing strategies prioritize short-term gains over long-term benefits, leading to inefficiencies. To address this issue, the authors develop a novel approach that considers multiple promotions simultaneously, aiming to reduce unnecessary costs and enhance overall market performance.
Low GrooveSquid.com (original content) Low Difficulty Summary
The paper is about how coupons work in online marketplaces. It’s important for both people who buy things (buyers) and people who sell things (sellers) to be happy. Right now, most marketing strategies only focus on making buyers happy, but this isn’t good enough. The current way of doing things means we waste money trying to make a quick impact with each promotion, rather than thinking about what’s best for the whole market.

Keywords

* Artificial intelligence