TL;DR
本文是LinkedIn广告团队关于出价策略总结，具体原理 和之前阿里妈妈的MCB、USCB以及Google广告的出价都是一致的，只是从另一种角度进行公式的推导。
摘要
We establish a general optimization framework for the design of automated bidding agent in dynamic online marketplaces. It optimizes solely for the buyer’s interest and is agnostic to the auction mechanism imposed by the seller. As a result, the framework allows, for instance, the joint optimization of a group of ads across multiple platforms each running its own auction format. Bidding strategy derived from this framework automatically guarantees the optimality of budget allocation across ad units and platforms. Common constraints such as budget delivery schedule, return on investments and guaranteed results, directly translates to additional parameters in the bidding formula. We share practical learnings of the deployed bidding system in the LinkedIn ad marketplace based on this framework.
我们建立了一个用于动态在线竞价市场中自动出价的通用最优化框架，它只面向广告主的利益进行优化，并不关注拍卖机制的具体形式。因此，该框架可以帮助在多个平台上进行投放的广告进行联合的优化，所推导出的最优出价策略，天然保证了广告预算能够以最优的方式分配在多个广告单元以及不同的投放平台，常见的约束，比如预算约束、ROI约束、结果约束，都可以转化成出价策略中的参数。同时，我们也分享了一些在LinkedIn平台上部署这套出价系统的实践经验。