Stance partnered with Novi to improve how LLMs interpreted its Run Sock products, with a focused strategy spanning technical structure, PDP content, and category relevance. The impact showed up quickly and within weeks of deployment, priority products were being selected more often and moving significantly higher in AI rankings, while Stance also saw a sharp increase in traffic to its Run Sock collection.
Novi helped Stance build a stronger foundation for how its Run Sock products were understood by AI systems. The work combined back-end technical changes across the category with PDP structure and FAQ recommendations, plus deeper content optimization for the Run Light/UL line.
Novi also identified gaps in Stance’s schema and helped translate product differentiation, ratings, performance data, use cases, and key attributes into clearer, more structured information for AI systems. This gave Stance a stronger foundation for improving product eligibility, relevance, and ranking within the Run Sock category.
In the first weeks of working together, Stance began seeing measurable gains across AI performance and site traffic:
A priority Stance Run Sock product was selected significantly more often in relevant AI shopping results.
A priority Stance Run Sock product moved up 20 positions within the Running Socks category 2 weeks after deplyment.
Organic visitors to Stance’s Run Sock collection increased period over period.
That increase was accompanied by 102% growth in active users and 92% growth in events post-deployment.
