ReFiBuy tells you what product data is missing or could be added.
Novi tells you why that data matters, whether it actually influences AI selection, and which signals are most important within the category.
Go beyond product data gaps. Novi shows you which signals actually influence AI selection and ranking, why they matter, and where to focus first.
ReFiBuy helps brands identify gaps in product information and improve catalog readiness for AI commerce. Novi goes deeper into the recommendation decision itself, helping brands understand which attributes and authority signals actually influence whether a product is selected, how it ranks, and what should be prioritized to improve performance.
Not every missing attribute has the same impact on an AI recommendation. Novi’s Category Intelligence identifies which signals matter within a specific category and connects those signals to actual selection and ranking behavior. This helps brands prioritize the changes most likely to influence recommendations rather than simply adding more product information.
AI systems evaluate products in the context of a category and a specific shopping need. Novi helps brands understand how attributes contribute to relevance, evidence, and competitive differentiation, so teams can focus resources on the signals that meaningfully affect recommendation outcomes.
Yes. Novi turns recommendation intelligence into prioritized updates across product attributes, PDPs, structured data, content, authority signals, and distribution. The difference is that those updates are informed by how AI is actually evaluating the category and the product.