We help product-led organisations structure, connect and improve the catalogue data required for AI-assisted discovery and supported shopping channels.
The underlying catalogue must be accurate. Products, formats and variants must be distinguishable. Prices, availability, delivery and returns must remain current. Identifiers and merchant systems must agree. Without that foundation, new discovery channels reproduce the same gaps already present in the commerce system.
Review titles, descriptions, variants, formats, ISBNs, GTINs, SKUs and the data relationships between them.
Assess catalogue structure, product taxonomy, feeds, merchant settings and supported channel configuration.
Improve the information AI systems and shopping interfaces can use to understand what the product is, who it is for and whether it is available.
Map books, editions, bundles, territories, special products and author or franchise relationships without flattening the commercial model.
Set up practical reporting for AI referrals, assisted discovery and commerce performance where platform data permits.
[ We improve readiness, eligibility, data quality, representation and measurement. We do not promise guaranteed listing, ranking, recommendation or placement inside any AI platform. ]
A title may exist as hardback, paperback, ebook, audiobook, signed edition, bundle, regional edition or pre-order. Agentic commerce work for publishers must preserve those distinctions while keeping product data consistent across the store, merchant feeds, marketplaces and fulfilment systems.
→ Discuss a publishing or IP catalogueA structured assessment of catalogue quality, identifiers, Shopify or commerce configuration, supported AI channels and current measurement. You receive a ranked readiness plan, including what can be corrected now and what should be monitored as platforms mature.
A Fit Call establishes the objective and whether the AI Commerce Readiness Assessment is the right first step.