Often marketers face the challenge of how to communicate best with the customers who have the right responsibilities, influence or purchasing power, especially in business-to-business (B2B) settings. For example, B2B marketers selling software and IT need to identify IT decision-makers (ITDMs) within organizations. The modern digital environment in theory allows marketers to target individuals in organizations through specifically designed third-party audience segments based on deterministic prospect lists or probabilistic inference. However, in this paper we show that in our context, such ‘off-the-shelf’ segments perform no better at reaching the right person than random prospecting. We present evidence that even deterministic attribute information is flawed for ITDM identification, and that the poor campaign results can be partly linked to incorrect assignment of established prospect profiles to online identifiers. We then use access to our publisher network data to investigate what would happen if the advertiser had used first-party data that are less susceptible to the identified issues. We demonstrate that first-party demographics or contextual information allows advertisers and publishers to outperform both third-party ITDM audience segments and random prospecting. Our findings have implications for understanding the shift in digital advertising away from third-party cookie tracking, and how to execute digital marketing in the context of broad privacy regulation.

营销人员经常面临如何与具有适当责任、影响力或购买力的客户进行最佳沟通的挑战，尤其是在企业对企业 (B2B) 环境中。例如，销售软件和 IT 的 B2B 营销人员需要识别组织内的 IT 决策者 (ITDM)。理论上，现代数字环境允许营销人员根据确定性前景列表或概率推理，通过专门设计的第三方受众群体来定位组织中的个人。然而，在本文中，我们表明，在我们的背景下，这种“现成的”细分在找到合适的人方面并不比随机勘探更好。我们提供的证据表明，即使是确定性的属性信息对于 ITDM 识别来说也是有缺陷的，并且糟糕的活动结果可能部分与将已建立的潜在客户概况错误地分配给在线标识符有关。然后，我们使用对发布商网络数据的访问权限来调查如果广告商使用不易受已识别问题影响的第一方数据会发生什么情况。我们证明，第一方人口统计数据或上下文信息使广告商和发布商能够超越第三方 ITDM 受众群体和随机勘探。我们的研究结果对于理解数字广告远离第三方 cookie 跟踪的转变，以及如何在广泛的隐私监管背景下执行数字营销具有重要意义。