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
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
SpaceX Said to Pursue 2026 IPO
10 Dec 2025
Bloomberg Tech
Don’t Call It a Comeback
10 Dec 2025
Motley Fool Money
Japan Claims AGI, Pentagon Adopts Gemini, and MIT Designs New Medicines
10 Dec 2025
The Daily AI Show
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
What it will take for AI to scale (energy, compute, talent)
10 Dec 2025
Azeem Azhar's Exponential View
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast