消费品的受众创造--面向不断增长的市场的简单且可扩展的精确营销
Audience Creation for Consumables -- Simple and Scalable Precision Merchandising for a Growing Marketplace
摘要：
杂货和快速消费品等消费品类别是发展中国家电子商务市场增长的关键。在这项工作中，我们提出了一个精确的销售系统的设计和实施，该系统创建了来自1000多万消费者的受众集，并部署在印度最大的在线杂货店之一Flipkart Supermart。我们采用时间点过程来模拟消费品购买动态的潜在周期性和相互激励。此外，我们开发了一个无似然估计程序，对数据稀疏性，谴责和噪声典型的不断增长的市场是强大的。最后，我们通过量化触发内核和利用商业分布式线性代数后端上可用的稀疏矩阵向量乘法原语来扩展推理。在一年多的运营中，我们见证了店面中基于横幅的商品销售的点击率在25-70%之间的持续增长，以及基于推送通知的活动的点击率在12-26%之间的增长。
英文摘要：
Consumable categories, such as grocery and fast-moving consumer goods, are quintessential to the growth of e-commerce marketplaces in developing countries. In this work, we present the design and implementation of a precision merchandising system, which creates audience sets from over 10 million consumers and is deployed at Flipkart Supermart, one of the largest online grocery stores in India. We employ temporal point process to model the latent periodicity and mutual-excitation in the purchase dynamics of consumables. Further, we develop a likelihood-free estimation procedure that is robust against data sparsity, censure and noise typical of a growing marketplace. Lastly, we scale the inference by quantizing the triggering kernels and exploiting sparse matrix-vector multiplication primitive available on a commercial distributed linear algebra backend. In operation spanning more than a year, we have witnessed a consistent increase in click-through rate in the range of 25-70% for banner-based merchandising in the storefront, and in the range of 12-26% for push notification-based campaigns.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
