With yearly revenue exceeding one billion USD, Yahoo Gemini native advertising marketplace serves more than two billion impressions daily to hundreds of millions of unique users. One of the fastest growing segments of Gemini native is dynamic-product-ads (DPA), where major advertisers, such as Amazon and Walmart, provide catalogs with millions of products for the system to choose from and present to users. The subject of this work is finding and expanding the right audience for each DPA ad, which is one of the many challenges DPA presents. Approaches such as targeting various user groups, e.g., users who already visited the advertisers' websites (Retargeting), users that searched for certain products (Search-Prospecting), or users that reside in preferred locations (Location-Prospecting), have limited audience expansion capabilities. In this work we present two new approaches for audience expansion that also maintain predefined performance goals. The Conversion-Prospecting approach predicts DPA conversion rates based on Gemini native logged data, and calculates the expected cost-per-action (CPA) for determining users' eligibility to products and optimizing DPA bids in Gemini native auctions. To support new advertisers and products, the Trending-Prospecting approach matches trending products to users by learning their tendency towards products from advertisers' sites logged events. The tendency scores indicate the popularity of the product and the similarity of the user to those who have previously engaged with this product. The two new prospecting approaches were tested online, serving real Gemini native traffic, demonstrating impressive DPA delivery and DPA revenue lifts while maintaining most traffic within the acceptable CPA range (i.e., performance goal). After a successful testing phase, the proposed approaches are currently in production and serve all Gemini native traffic.

翻译：Yahoo Gemini原生广告市场年收入超过十亿美元，每日向数亿独立用户展示超过20亿次广告。Gemini原生广告中增长最快的板块之一是动态产品广告（DPA），Amazon、Walmart等大型广告主通过该功能提供数百万种产品的目录供系统选择并向用户展示。本文旨在为每个DPA广告寻找并扩展合适的受众，这是DPA面临的众多挑战之一。现有方法包括针对不同用户群体进行定向，例如曾访问广告主网站的用户（重定向）、搜索过特定产品的用户（搜索扩展）或位于偏好区域的用户（位置扩展），但这些方法的受众扩展能力有限。本文提出两种既能扩展受众又能维持预设性能指标的新方法。其中，转化扩展方法基于Gemini原生广告日志数据预测DPA转化率，并计算预期每次行动成本（CPA），以判定用户对产品的适配度，并在Gemini原生广告竞价中优化DPA出价。为支持新广告主和新产品，趋势扩展方法通过学习用户对广告主网站日志记录事件中产品的偏好倾向，将热门产品匹配给用户。该倾向得分反映了产品的流行度以及用户与历史互动用户的相似程度。这两种新扩展方法已通过在线测试，在真实Gemini原生广告流量中运行，在将大部分流量维持在可接受CPA范围（即性能目标）内的同时，显著提升了DPA投放量和DPA收入。经过成功的测试阶段后，所提方法已投入生产环境，服务于所有Gemini原生广告流量。