Aligned or Apart? Multi-Agent Insights into Consumer and Brand Messaging Discrepancies

In the digital age, brand meaning is increasingly shaped through user participation and content sharing on social media platforms. However, significant perceptual gaps often exist between official brand narratives and consumer interpretations. These multimodal and cognitively nuanced gaps are challenging to detect and model using traditional analytical methods. To address this, we propose a multi-agent framework that metaphorically models perception as an optical process-propagation, interference, and measurement - -termed OPIM. We construct a novel dual-perspective dataset from representative social media platforms, integrating text and image content from both user-generated and official brand communications. We evaluate brand perception along six psychological dimensions. Experiments across 15 brands demonstrate that our framework effectively captures key perception gaps, particularly in sincerity, professionalism, and attractiveness. In contrast, materialism and sophistication exhibit higher alignment between brand messaging and consumer perception. Our framework enhances the cognitive alignment and multimodal interpretability of large language models, offering actionable insights for brand strategy and bridging computational modeling with human-centric understanding. The dataset will be available at https://github.com/htgan-ai/OPIM.