Real-Time Bidding Optimization

https://www.databricks.com/solutions/accelerators/real-time-bidding-optimization

Real-time bidding (RTB): is a subcategory of programmatic media buying. RTB firms established the technology of buying and selling ads in real time (~ 10ms ) in an instant auction, on a per-impression basis. In this Databricks demo, we demonstrate a process to predict viewability using BidRequest Data. Keep in mind, the more likely users are to see an ad, the higher the price a DSPs will want to place on a bid for that ad, because it is ultimately more valueable to the advertiser.
By building a reliable, scalable, and efficient pipeline to predict viewability, advertisers can more accurately identify where to spend their marketing budgets to fine-tune media spend, improve ROI, and enhance campaign effectiveness.

Click on the "Get instant access" button in the top right corner to clone the solution accelerator repo into your workspace. Once the repo is cloned into your workspace, please execute the **RUNME** notebook in the repo in order to create the cluster and job you can use to run the notebooks.

https://www.databricks.com/solutions/accelerators/real-time-bidding-optimization

实时竞价（Real-time Bidding, RTB）是程序化媒体购买的一个子类别。实时竞价企业构建了基于单次曝光维度、在即时拍卖场景下以约10毫秒的速度实时买卖广告的技术。在本次Databricks演示中，我们将展示一套利用出价请求数据（BidRequest Data）预测广告可见性的流程。请注意，用户越有可能看到该广告，需求方平台（Demand-Side Platforms, DSPs）为该广告出价时所要求的价格就越高，因为这最终对广告主而言价值更高。

通过构建可靠、可扩展且高效的可见性预测流水线，广告主能够更精准地确定营销预算的投放方向，以此优化媒体投放、提升投资回报率（Return on Investment, ROI）并增强广告活动的效果。

点击右上角的「立即获取访问权限」按钮，将该解决方案加速器代码仓库克隆至你的工作区。将代码仓库克隆至工作区后，请执行该仓库中的**RUNME**笔记本，以创建可用于运行各笔记本的集群与作业（job）。

搜集汇总

背景与挑战

背景概述

该数据集演示了基于BidRequest数据预测广告可视性的流程，帮助广告主通过实时竞价技术优化媒体投放效果。用户可通过克隆解决方案库并运行指定笔记本来使用该数据集。