The next discovery advantage starts with product data.

Clarity is infrastructure

Product discovery depends on information a customer or system can interpret. A memorable campaign line is useful, but it cannot replace a consistent product name, an accurate description and meaningful attributes. Start with the catalogue rather than a promise about an emerging channel.

Make the important attributes explicit

Record dimensions, materials, compatibility, variants and intended use where they genuinely apply. Use a controlled vocabulary so similar products describe the same attribute in the same way. Avoid unsupported claims and distinguish a product fact from a brand promise.

Keep one accountable source

When different systems carry different versions of a product, accuracy becomes harder to maintain. Document where each field is owned, how it is updated and which storefronts or feeds consume it. A reliable process is more useful than a one-off clean-up.

Structure useful, visible information

Structured product information should agree with what a person can see on the page. Google’s product documentation describes supported product information for search features; eligibility does not guarantee presentation or ranking. Review the official requirements as part of implementation.

Evaluate assisted discovery deliberately

If an assistant is introduced, test its recommendations against the actual catalogue. Assess incorrect attributes, unavailable products, ambiguous questions and the route back to normal browsing. Better product data creates a stronger foundation, but it does not guarantee visibility in AI discovery systems.

Reference: Google Search Central — Product structured data. Consulted 18 September 2026.

A practical next step

Choose one part of your store and define the question you want to answer. The VIA77 Commerce Review provides a structured starting point for that conversation.