Browser / Operating System-Linked audiences

What are browser/operating system-linked audiences? 

这些受众是通过解决方案交付的，这些解决方案允许广告商在一个封闭环境的范围内以1:1的水平定位和衡量受众. Rather than identifying users 1:1, 它们提供了访问一组通过隐私增强技术(pet)分组和匿名的人的权限。. A key example in this space is Privacy Sandbox's Topics, while on mobile Apple’s iOS SKAdNetwork is an aggregate linked solution. 

Apple’s App Transparency Framework 

In April 2021, Apple launched the App Tracking Transparency (ATT) framework in its iOS 14.5 update as a proprietary requirement. 它要求那些在App Store上提供应用程序的公司在跟踪其他公司的应用程序和网站的用户活动之前，必须征得同意.

这种变化给广告商在移动生态系统中与消费者互动带来了巨大的挑战, without explicit opt-in user consent, advertisers no longer have access to device identifiers on iOS, including the commonly used Identifier for Advertisers (IDFA).

The impact of losing access to these identifiers has been significant across the ecosystem where advertising techniques rely on individual identifiers in order to function; causing challenges with attribution and measurement, as well as common budget management techniques such as frequency capping and ad sequencing.

To address some of these challenges, including attribution, Apple has created certain privacy-friendly approaches that operate within the constraints of ATT. Most notably, this includes SKAdNetwork (SKAN), 哪种框架能够报告广告和应用安装之间的归因关系，而不会泄露任何关于个人的潜在数据. Instead, it provides high-level, aggregated reporting only.

ATT的引入已经对广告商通过iOS接触消费者的能力产生了重大影响. Reports show that there is an average 60-65% opt-out rate among consumers via the ATT prompt, 哪些因素会影响应用程序和移动平台通过使用定向广告实现内容货币化的能力. While SKAN has evolved to improve reporting and attribution capabilities, there has been limited success in replicating the targeting capabilities available prior to ATT.

Google’s Privacy Sandbox

In 2019, Google announced its Privacy Sandbox initiative, 在Chrome浏览器弃用第三方cookie后，该公司寻求为广告商寻找替代解决方案，以定位和衡量广告活动. This was initially established to operate in Chrome, but Google announced in February 2022 that the scheme will be extended to also cover the Android operating system.

隐私沙箱旨在通过防止识别个人用户来减少或消除跨站点和跨应用程序的跟踪, whether based on cookies or other similar techniques (such as device fingerprinting).

To achieve this goal, Google已经提出了许多api来复制现有的基于cookie的定位和测量所提供的功能, but in a more privacy-conscious way.

Here we provide a summary of some of the key advertising API services being developed by Privacy Sandbox, namely: Topics (interest-based targeting), Protected Audiences (remarketing and custom audiences, formerly FLEDGE) and Attribution Reporting (measurement).
 

Topics

主题API旨在实现基于兴趣的广告，而不依赖于第三方cookie或个人标识符.

浏览器将被限制在一个预定义的人工策划的细分列表中，以避免敏感的数据类别. An overview of workflow is as follows:

1. Labelling of content within a website according to the pre-defined segments
2. The browser collects all of the topics associated with the user’s site browsing on their device; on Android the user’s app usage is used to identify the top topics
3. Providing this segment data to an advertiser for targeting purposes without identifying the user

虽然这种方法比使用第三方cookie更注重隐私，并将允许广告商接触到相关受众, 一个值得注意的挑战是，当前的分类法仅限于350个主题，因此与cookie相比，它没有那么具体的定位功能.
 

Protected Audiences

受保护受众API允许广告商根据自定义细分和兴趣向用户或目标用户进行再营销. 用户根据现场行为被分组成群组，所有后续目标定位都是在群组水平而不是个人用户水平上完成的. 受保护受众还包括确保用户隐私和防止跨站点跟踪的机制, 例如，只允许在有限的时间内使用队列，并限制可以共享或加入的数据量，以防止微目标.

At a high level, the process for targeting using the Protected Audiences API is described as:

1. 广告商或DSP(兴趣组所有者)根据用户的标准将用户添加到浏览器/设备中的兴趣组对象中
2. On-device bidding by buyers (DSPs or advertisers), based on interest-group metadata
3. On-device ad selection by the seller (SSP or publisher) to determine winning bid

Attribution Reporting

In contrast to the Topics and Protected Audience APIs, which focus on targeting mechanisms, 归因报告API专注于在后第三方cookie或标识符框架中重新创建广告性能报告. API被广泛地定义为两种互补的报告类型，它们的范围和粒度不同:事件级报告和摘要报告.

事件级报告允许通过简化的转换终点对广告点击和视图进行细粒度归因. In contrast to existing event level reporting, the Privacy Sandbox event-level reports will introduce ‘noisy’ datasets with a delay to preserve privacy.

Summary reporting provides aggregated user reporting with increased resolution on conversion datasets. While event-level reports at the user level are primarily used for optimisation, anomaly detection and coarse reporting, the summary reports are for more general campaign reporting tasks.

Considerations

业界支持聚合链接解决方案的理由是，它们更注重隐私，因为它们在1:1的水平上工作，而不是在1:1的水平上识别人. Data will be pseudonymised and grouped so that users can’t be individually identified by advertisers. 业内潜在的担忧是，与目前可实现的目标相比，这种方法可能导致以特定利益为中心的基本目标.

Summary

• 浏览器/操作系统链接的受众描述了浏览器或操作系统进行受众链接的环境, as noted above with regard to Privacy Sandbox and SKAN in particular

• 这种方法依赖于相关的浏览器或操作系统执行特定于用户的分析，并仅报告聚合的结果, non-identifiable result to the advertiser

• This takes various forms, 例如，通过隐私沙箱和主题API等框架进行设备上的机器学习，以分析应用和网络行为，并创建基于兴趣的细分，呈现给广告商, without any ability to access underlying individual-based identifiers

• As these technologies are on-device by definition, there can be challenges with measurement beyond these siloes. Further, these types of techniques include specific protections to prevent indirect identification of individuals, including preventing the tracking of movement between interest groups or segments, and time-delaying aggregated reporting

• Project Rearc’s support of solutions in this area is its SKAdNetworks List, which maintains a registrar of Advertisers, DSPs and networks that can be utilised by App Publishers for attribution support