According to a recent LinkedIn post from ReFiBuy, the company is emphasizing how rich product storytelling and store associate training content can be repurposed as valuable data for large language models. The post references a discussion on The Jason & Scot Show with Kendra Scott executives, focusing on using design histories and customer-interaction insights to improve AI-driven shopping experiences.
The company’s LinkedIn post highlights a concept it calls Agentic Commerce Optimization, which appears to center on feeding associate training material and product narratives into digital catalogs to enhance recommendation quality. For investors, this suggests ReFiBuy is positioning itself at the intersection of retail operations and AI, potentially increasing its relevance to brands seeking differentiated e-commerce tools.
The post suggests that leveraging in-store knowledge such as gift-guidance questions and style cues could make both on-site and off-site shopping agents, including voice-based platforms like Alexa for Shopping, more effective. If successfully productized and adopted at scale, this approach could deepen ReFiBuy’s integration with retail clients, support higher-value contracts, and strengthen its competitive standing in AI-enabled commerce solutions.