论文标题
通过生成优化的组合多个数字营销活动来增强零售商的收入
Boosting Retailer Revenue by Generated Optimized Combined Multiple Digital Marketing Campaigns
论文作者
论文摘要
广告系列是一种在传统营销中提升零售商的GMV（总商品）的经常使用的工具。作为在线环境中的同行，随着电子商务的迅速发展，数字营销挑战（DMC）近年来一直在趋势。但是，如何在在线零售平台上授权大量卖家能够应用多个数字营销活动来提高商店的收入的能力仍然是一个新的话题。在这项工作中，提出了一种全面的生成优化合并多个DMC的解决方案。首先，新提出的神经网络模型，即DMCNET（数字营销 - 吸引网络）为每个零售商生成了潜在的个性化DMC池。其次，基于DMCNET的下模量优化理论和DMC池，生成的组合多个DMC在其收入产生强度方面进行了排名，然后将前三名的广告系列返回到卖方的后端管理系统，以便零售商可以将多个DMC设置为在线商店，仅在一单程中进行多个DMC。 Real Online A/B检验表明，借助集成解决方案，在线零售平台的卖家将商店的GMVs增加了大约6 $ \％$。
Campaign is a frequently employed instrument in lifting up the GMV (Gross Merchandise Volume) of retailer in traditional marketing. As its counterpart in online context, digital-marketing-campaign (DMC) has being trending in recent years with the rapid development of the e-commerce. However, how to empower massive sellers on the online retailing platform the capacity of applying combined multiple digital marketing campaigns to boost their shops' revenue, is still a novel topic. In this work, a comprehensive solution of generating optimized combined multiple DMCs is presented. Firstly, a potential personalized DMC pool is generated for every retailer by a newly proposed neural network model, i.e. the DMCNet (Digital-Marketing-Campaign Net). Secondly, based on the sub-modular optimization theory and the DMC pool by DMCNet, the generated combined multiple DMCs are ranked with respect to their revenue generation strength then the top three ranked campaigns are returned to the sellers' back-end management system, so that retailers can set combined multiple DMCs for their online shops just in one-shot. Real online A/B-test shows that with the integrated solution, sellers of the online retailing platform increase their shops' GMVs with approximately 6$\%$.
