We introduce a novel approach to analyze the positioning strategies of political actors based on their public communication. Leveraging recent advancements in natural language processing and market structure analysis, we measure the evolving positioning of political actors. By utilizing textual data from public records, embedding models, and dynamic mapping methods, our approach reveals how political actors position themselves in their communication and how their positioning changes over time. We illustrate our approach using data from Germany, including all public speeches in the German parliament between 2009 and 2022. Our application yields two major insights. First, our proposed approach provides an intuitive representation of the German political landscape and recovers pronounced shifts in the positioning of several German parties. Thereby, our estimates of party positioning exhibit high validity, aligning well with external measures of party ideology or parties’ actual voting behavior. Second, our proposed approach can help explain substantial variation in parties’ performance. Using our estimates, we quantify various aspects of German parties’ positioning, such as the degree of differentiation or stability over time. Panel regressions show that party positioning, as captured by these metrics, explains a substantial portion of within-party variation in regular election polls (+28% R2).

Effective online advertising depends on a marketer’s ability to reach a target audience—a specific group of consumers with desired characteristics. Traditionally, marketers have identified these consumers by tracking and analyzing their online behavior. However, growing privacy concerns and new regulations are restricting this practice. In response, this research investigates an alternative strategy for reaching target audiences online: inferring consumer characteristics solely from search queries consumers use when searching online. We empirically test the premise that search queries contain valuable signals about consumer characteristics that allow marketers to identify those queries most indicative of their target audience. Across three contexts—weight loss, online dating, and personal investing—we demonstrate that search queries strongly indicate consumer characteristics such as socio-demographics, category experience, or brand preferences. A subsequent field study further supports the external validity and practical implications of these findings. Using our results, a leading retail bank launched a search advertising campaign targeting a particular high-value audience. This audience-specific campaign converted a higher share of new customers (+21.37%) who generated substantially more revenue (average trading volume per customer: +97.90%), compared to a performance-driven campaign designed by SEA experts.