Catalog intelligence covers a lot: structure, quality, enrichment, governance, and how AI systems read product data. This guide is a route through it. Each step points to the pages that go deeper.
-
1. Understand the concept
Begin with the parent topic to see how the pieces connect. Read the Catalog Intelligence pillar and the answer What is catalog intelligence?
-
2. Diagnose your situation
Name the problem you actually have. The Answers library covers the common ones — why product data is messy, why products don't show up in search, and who owns product data.
-
3. Learn the fundamentals
Work through the four topic pillars, each with its own answer cluster: structured product data, product data quality, AI product discovery, and agentic commerce.
-
4. See who does what
Understand the platform landscape neutrally through the vendor directory and the plain-language vendor answers.
-
5. Compare approaches
Weigh options against each other and against building it yourself on the comparison pages.
-
6. Gauge your own catalog
Learn how quality is measured so you can assess where you stand: How do you measure catalog quality? and What is catalog quality scoring? When you're ready to act, the Catalog Quality Audit guide walks through the steps.