What Type of Digital Advertising is Most Effective for B2B Prospecting? The Case of IT Decision-Makers

Abstract

Business-to-business (B2B) marketers face the challenge of how to communicate best with decision-makers in a firm. For example, firms selling software and IT need to identify IT decision-makers (ITDM) within a firm. The modern digital environment in theory allows B2B marketers to target such individuals in organizations based on prospect lists or algorithmic inference. However, in this paper we present evidence that such specifically designed B2B segments are not performing better at reaching the right person in the firm than random prospecting. We then use access to our publisher network data to investigate what would happen if the advertiser had used demographics or context rather than third-party data to launch their campaigns. We show that this kind of first-party data allows publishers to outperform ITDM audience segments and random prospecting in our study. 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.

Keywords: Digital targeting, B2B marketing, online profiling