This April 2025 paper introduces SODA, a novel framework designed to enhance digital advertising strategies by making opaque AI systems more understandable for marketers. The authors highlight the current challenges faced by advertisers due to the lack of transparency in major ad platforms like Meta, which often results in wasted ad spend and reliance on intuition. To address this, SODA integrates Large Language Models (LLMs) with explainable AI techniques to provide clear, actionable insights into ad performance. The framework initially employs an improved Click-Through Rate (CTR) prediction model, SoWide-v2, which also offers visual explanations through attention maps. Furthermore, SODA leverages LLMs to automate comprehensive ad analysis, including identifying target audiences, brand personas, and key messaging, providing marketers with summarized and comparative data that was previously difficult to obtain without extensive manual effort. A case study with marketing professionals validated the framework's practical value and potential to streamline decision-making in fast-paced advertising environments.
Source:
https://arxiv.org/pdf/2504.20064
