What makes good source data

Enrichment writes from your existing product data and will not invent facts beyond it. Input quality sets a ceiling on output quality, so this is the first thing to check.

Enrichment amplifies, it does not fabricate

If a record says 100% cotton, enrichment can write about breathability and care. If the record never mentions material, the output won’t either — the gap stays a gap rather than being filled with a plausible guess.

That is the intended behaviour. Invented specifications are worse than missing ones.

What Catalog sends to the enrichment service

For each product in an enrichment, Catalog sends only the following fields to the enrichment service as inputs:

These product fields are combined with the purpose, brand voice, search keywords, and additional context you enter on the create screen. See How your inputs are used.

What a workable record contains

The more of these you have, the more there is to write from.

What to fix first

1. Products with no usable name. These fail or produce generic text. Fix them or exclude them.
2. Placeholder text. “Description coming soon” and lorem ipsum produce exactly what you would expect.
3. Your thinnest records. Sort by description length. The bottom of that list either needs a data pass first or should be left out of early batches.
4. Inconsistent units and terminology. Standardising these reduces contradictions between generated fields.

Errors are usually a data problem

Products that fail to generate appear on the Errors tab, and retrying them is free. But a retry on an unchanged record produces the same result. Read a few failures before retrying — the common cause is a record too sparse to work from.

A quick audit before your first batch

Pick 20 products at random. For each, ask whether a copywriter with no product knowledge could write a useful paragraph from the record alone. If the answer is no for most of them, fix data before spending entitlements.