MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation
Aleksandr Farseev, Marlo Ongpin, Qi Yang, Ilia Gossoudarev, Yu-Yi Chu-Farseeva, Sergey Nikolenko

TL;DR
MindFuse introduces an explainable generative AI framework that enhances marketing strategy co-creation by integrating real advertising data, real-time optimization, and interpretability, significantly improving efficiency and strategic alignment.
Contribution
The paper presents MindFuse, a novel explainable AI system that combines content generation, interpretability, and real-time campaign adaptation for marketing, advancing beyond traditional LLM applications.
Findings
Up to 12 times efficiency gains in marketing workflows
Effective diagnosis of ad effectiveness through attention-based explainability
Successful deployment in agency settings with real-world validation
Abstract
The future of digital marketing lies in the convergence of human creativity and generative AI, where insight, strategy, and storytelling are co-authored by intelligent systems. We present MindFuse, a brave new explainable generative AI framework designed to act as a strategic partner in the marketing process. Unlike conventional LLM applications that stop at content generation, MindFuse fuses CTR-based content AI-guided co-creation with large language models to extract, interpret, and iterate on communication narratives grounded in real advertising data. MindFuse operates across the full marketing lifecycle: from distilling content pillars and customer personas from competitor campaigns to recommending in-flight optimizations based on live performance telemetry. It uses attention-based explainability to diagnose ad effectiveness and guide content iteration, while aligning messaging with…
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Taxonomy
TopicsAI in Service Interactions · Persona Design and Applications · Digital Marketing and Social Media
