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# What makes good source data

> Why enrichment output is capped by input quality, what a workable product record contains, and what to fix before you spend entitlements.

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:

| Input                                                             | What it contributes                                                                        |
| ----------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| **Top five images** (the first five in the product's image order) | Visual detail, such as color, shape, and styling, that the text fields may not mention     |
| **Name** (`name`)                                                 | The product's identity and the anchor for every generated field                            |
| **Description** (`description`)                                   | Most of the facts available to write from — materials, dimensions, features, and use cases |
| **SEO keywords** (`seoKeywords`)                                  | Terms the product is already associated with in search                                     |

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](/developer/docs/ai-tools/catalog-enrichment/inputs/how-inputs-are-used).

## What a workable record contains

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

| Present in the record                  | What it enables                                                            |
| -------------------------------------- | -------------------------------------------------------------------------- |
| A real product name, not a SKU code    | Everything. A name like `SKU-4471-BLK` gives the tool nothing to work with |
| Materials, dimensions, capacity        | Concrete description copy and factual Q\&A answers                         |
| Use cases or intended audience         | Intent Q\&A, and copy that speaks to a buyer                               |
| Distinguishing features                | Content that separates this product from the next one                      |
| Existing description, even a rough one | A starting point and a signal of what matters                              |

## 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.

> **What consumes an entitlement**
>
> Entitlements are consumed when products are **sent** for enrichment, not when you apply results. A product counts once whether or not it has variants. Retrying errored products is free; re-running a product that generated successfully consumes another entitlement.

## 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.