What it is
A lightweight catalog diagnostic for AI-facing product data, with an optional paid findings report when you need a saved issue register and cleanup order.
Catalog Scanner
Is your product data ready for AI-facing commerce?
Check whether missing fields, weak identifiers, variants, prices, availability, or feed structure are holding back AI-facing commerce surfaces.
Entry point
Free scanner + paid report
Best for
Merchants with a product export, feed sample, API payload, or catalog file.
What it solves
Missing fields, messy product details, weak identifiers, stale price or availability values, and target-format issues that make product facts harder for AI search tools and shopping agents to trust.
Who it is for
Merchants who already have a feed export, product file, API payload, or catalog sample they want checked.
Deliverables
- Catalog Scanner result
- Issue mix and severity
- Optional paid PDF findings report
- Recommended AI-facing product-data cleanup path
What is not included
- Silent unsupported value filling
- Claims that one converted feed equals full readiness
- Storefront theme fixes or custom protocol implementation by default
Launch version
The sequence is simple: run the free Catalog Scanner first, turn the saved result into the paid Catalog Scanner PDF report when the catalog clearly needs AI-facing product-data cleanup, then move into Catalog Remediation only if the report has already narrowed the scope.
Scope guardrail
Improve readiness before heavier work.
This service improves readiness, fit, and the quality of the next decision for AI search and agentic commerce. It does not promise platform activation, approval, rankings, or guaranteed results.
How the steps fit
Use the Catalog Scanner before the paid report.
Catalog Scanner is the smaller free step. The paid Catalog Scanner report is the findings layer. Catalog Remediation and Recurring Monitoring come after that.
Free preview
Use the free site preview when the AI-commerce next step is still unclear.
Site Scanner checks a sample of pages, policy coverage, behind-the-scenes product data, and one recommended next move for AI search and shopping-agent readiness.
- Best when the team is still unsure whether the issue is the site, trust, structured data, or platform path.
- Scores what the bounded scan can actually verify on the storefront.
- Recommends the safest next service without asking you to choose a technical path first.
Catalog Scanner
Use the smaller feed check when catalog cleanup might be the real issue.
Upload or paste a representative feed sample to see whether missing fields, inferred values, or weak catalog structure are slowing AI-facing product data down.
- Best when a feed export, Merchant Center sample, or catalog file is already in hand.
- Checks product records, fit for the selected path, and common feed issue categories.
- Keeps feed questions separate from storefront, policy, and pathway claims.
Paid path
Start paid work only after the issue is clear.
Move into the paid full report when the site needs a deeper review. Move into Catalog Remediation when catalog data is clearly the issue, or AI Search Remediation when site clarity is the issue.
- Site Scanner for broader storefront coverage and paid report delivery.
- Catalog Scanner for a saved PDF findings layer before AI-facing cleanup work.
- AI Search Remediation, Catalog Remediation, and Recurring Monitoring come after confirmed findings.
Proof point
A sample result from a realistic messy export.
Representative sample result
Messy merchant export routed into AI-facing feed cleanup first.
This proof card is based on the repo's realistic `messy-merchant-export.csv` fixture against the Google-side feed path. It shows the kind of rules-based output Catalog Scanner surfaces before any paid Catalog Scanner report scope is proposed.
Rules-based result
The sample is workable, but not ready to push forward cleanly.
- 4 source records parsed from the repo's messy sample export
- 3 records cleaned into a shared product shape
- 1 record structurally usable for the Google-side target check
- 7 feed issues total: 6 major and 1 moderate
What it proves
Catalog Scanner separates feed cleanup from broader AI search readiness claims.
- Top recurring issues: image links weak or broken, inferred values required, and price cleanup.
- Recommended next service: Catalog Scanner.
- Guardrail: this sample does not claim Merchant Center approval or broader AI search readiness.