Paid Digital Advertising Effectiveness: A Meta-Analysis

• Applicant: Dr. Farid Tarrahi
• Subject Area: Operations Management and Computer Science for Business Administration
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 524663513

Nowadays, advertisers spend roughly half of the global ad budget on digital advertising. Paid digital advertising (i.e., search and display advertising) compared to advertising in traditional, paid media provides several advantages to advertisers, such as better feedback, active consumers, narrow or even personalized targeting, or availability to consumers at any time and almost any place. However, digital advertising has some drawbacks, too, such as privacy intrusion or increasing annoyance about banner advertising. As a result, the research findings about digital advertising effectiveness are mixed and there are different views on effectiveness in practice. Other than research on advertising effectiveness in traditional media, the area of paid digital advertising still lacks empirical generalizations, information on input-output relationships, and benchmarks for its relative effectiveness as basis for comparisons with traditional advertising and other marketing instruments. Research further lacks any generalizable knowledge about when paid digital advertising is more or less effective. This meta-analytic research project intends to address these research gaps and aims to provide new empirical generalizations about paid digital advertising’s effectiveness and how the effectiveness depends on characteristics of the advertising, market, products, data and measures, model, any omitted marketing variables, and study factors. The project offers a scientific contribution by providing empirical generalizations about the effectiveness of paid digital advertising and its contexts. Empirical generalizations provide useful benchmarks for researchers who are investigating digital advertising response models. The results provide an integrative framework for the investigation of digital advertising effects and crossover effects of various advertising formats and marketing instruments. By identifying influential and non-influential factors, meta-analysis helps researchers focus on relevant research questions, making it easier to develop a research agenda. The project offers practical implications for advertising budgeting and helps managers to base their budget decisions on reliable benchmarks on the (forecast) returns on their investments and to defend their investments.

• DFG Programme: Research Grants
• Co-Investigators: Professorin Dr. Katja H. Brunk; Professor Dr. Martin Eisend