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 create dynamic maps that capture 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).

We introduce information exigencies as a novel solution to a major challenge in digital marketing: targeting a specific audience with desired characteristics during their online searches. Search advertising campaigns target consumers through the queries they submit. Yet, marketers typically lack insights into the characteristics of consumers submitting these queries. Information exigencies, consumers’ imminent demand for information that manifests in their queries, bridge this gap. They contain signals of otherwise unobservable characteristics of the searching consumers, including sociodemographics, experience, or brand attitudes. To harness this potential, we develop TAVIX (Targeting via Information Exigencies), a comprehensive targeting approach incorporating a novel research-app. Our approach identifies information exigencies from search queries recorded from a consumer panel and links them to panelists’ characteristics. Subsequently, the TAVIX app lets marketers interactively build search campaigns aligned with their desired target audiences. We demonstrate the value of TAVIX for search advertising in a field study in collaboration with a major European retail bank. A campaign built with the TAVIX app substantially outperforms a campaign built by SEA domain experts in attracting a desired target audience—yielding both higher rates of new customer acquisition (share of new customers: +21.37%) and customer revenue (average trading volume per customer: +97.90%).