Challenges and Prospects of Using Synthetic Control Groups in Measuring Digital Advertising Effectiveness: A Data Quality Perspective

Citation: Dash Shruti, "Challenges and Prospects of Using Synthetic Control Groups in Measuring Digital Advertising Effectiveness: A Data Quality Perspective", Universal Library of Innovative Research and Studies, Volume 02, Issue 04.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The article examines the potential of using the synthetic control group method to measure the incremental effect of digital advertising in fragmented ecosystems and under conditions of limited feasibility for classical experiments. The relevance of the work is driven by the rapid growth of the share of digital media in global advertising budgets and, consequently, the high cost of systematic errors in assessing the contribution of campaigns to business outcomes. The study aims to provide a critical analysis of the methodological and operational challenges in applying synthetic control, clarify its scope of applicability, and formulate requirements for data, campaign design, and procedures for diagnosing the robustness of estimates. The novelty of the article lies in shifting the focus from the abstract properties of the method to the concrete conditions of digital advertising practice: it is demonstrated how panel structure, tracking quality, the extent of spillover effects, and the choice of data aggregation level may reinforce or, conversely, undermine the identification assumptions of synthetic control. Particular attention is devoted to comparing synthetic control with alternative causal methods, discussing typical scenarios of estimation bias, and proposing practical heuristics for donor pool selection and for configuring diagnostic placebo procedures in real-world projects. This approach should be regarded as a complementary instrument to randomized geo-experiments and media mix models, and its use requires a prespecified research protocol, unified modeling standards, and transparent communication of estimation uncertainty to stakeholders. The article is intended for researchers in marketing analytics, media measurement specialists, and digital communications managers responsible for building and developing advertising effectiveness measurement systems across industries.

Keywords: Digital Advertising, Panel Data Quality, Incremental Effect, Synthetic Control Method, Counterfactual Analysis.

https://doi.org/10.70315/uloap.ulirs.2025.0204016