Generative AI catalog management software in practice

How generative AI catalog management software works

Generative AI catalog management software reads a store's products, identifies empty or contradictory fields, and suggests copy and attributes based on facts already present in the product page, images and merchant files. It does not replace the store management system: it works with real data, assigns a score to each product reference and, after approval, writes to WooCommerce by SKU. The goal is to make every product understandable to Google and assistants without inventing specifications.

In a WooCommerce catalog, a crawler reads the title, long description, images, price, availability and attributes displayed on the page. What is usually missing is a verified brand, material, manufacturer-declared measurements, an original image that is not shared, and copy that matches the fields. Assistants read the same page text: structured data confirms price and availability when they match what is written. WooCommerce already produces basic Product markup; what holds a product reference back are missing or vague facts, in the text and in the data.

Why a catalog remains difficult to find

A catalog remains difficult to find when product pages do not consistently say what is being sold, at what price and whether it is available.

People who manage WooCommerce alongside Amazon, eBay, Etsy or Vinted often end up copying short titles from one channel to another. A marketplace title does not explain the material, size or condition. The description repeats slogans. The color attribute exists in the Products menu under Attributes, but does not appear in the text. The crawler sees a product; the assistant sees a generic sentence.

An illustrative example: a store with forty ceramic product references publishes “Blue plate 28” without clay, glaze, a manufacturer-declared diameter or a unique image across three SKUs. Google Shopping and the ChatGPT feed receive an incomplete object. This is not a problem of “more words”; it is a problem of missing facts.

Page text and structured data work together: markup confirms price and availability when it matches the page.

For people with little time for daily routines

Someone who opens the management system after working at the counter does not have a session available to rewrite three hundred product pages. They need a clickable list of problems, bulk actions with the credit cost visible before confirmation, and free corrections that remain reversible. Without this operational queue, the catalog stays stuck: the price is updated and everything else is left as it is.

An artisan selling ceramics and managing around forty product references

With a few dozen items, the risk is not volume but an all-caps product page, a studio photo used for several variants and a missing GTIN. Independent producers should state that a manufacturer GTIN is unavailable rather than inventing a code. Glaze and diameter variants should be grouped only after confirmation, with a group identifier in the feed.

For people publishing the same product references across channels

Anyone also selling on Vinted or Etsy needs a product page ready to copy, not automatic publication on those channels. On WooCommerce, writing can be bidirectional by SKU. On other channels, the product page is prepared and the merchant publishes it manually. No price is suggested from a marketplace's historical data.

What this type of software actually does

The software imports the catalog, measures the gaps, suggests corrections based on existing facts and, only after confirmation, writes them to the channel that accepts synchronization.

AI product cataloging is not free-form text created from nothing. It starts with a deterministic audit engine, without generation: key areas covering identity and fields, images, copy, duplicates and consistency, freshness and synchronization, and channel readiness. Each issue has a public source for the rule, such as Google, Meta or OpenAI documentation, and a correction path.

Then, if a rewrite is requested, AI works on the text behind a safeguard: brands, certifications and brand history are not invented; a measurement found online that contradicts the merchant's title is not included. Store data takes precedence over the web. If the text does not pass, the rewrite credit is not charged.

1. Import from a public WooCommerce store, images (one image, one product page), a price-list PDF or CSV.
2. Read visible fields and attributes already in the store without changing anything in read-only mode.
3. Assign scores and create the “fix now” list.
4. Confirm free corrections, such as capitalization, HTML, condition and Google category, or paid actions.
5. Synchronize by SKU to WooCommerce, or copy the product page for marketplaces managed manually.

How a catalog is read and how scores are created

The read-only scan, with up to one hundred products and no account, returns two scores for each product reference, plus Relevance and Completeness.

The first score concerns traditional search: title, attributes, images, and consistency between copy and fields. The second concerns readiness for assistants: explicit facts, a description a model can cite, and consistency between the page and its data. Relevance checks whether the brand and category fit the store's theme. Completeness lists missing or incorrect fields rather than judging style.

From an image, the tool reads only what is visible: brand, category, color, size, material and printed codes. It does not estimate prices or price ranges, measure dimensions, or infer season, use occasion, style or audience. Filling empty fields with facts from the web is a separate, explicitly requested action with a source; the second credit for that action is charged only if at least one field is written.

• Identity: stable SKU, brand, condition, new, refurbished or used, and category.
• Images: format, minimum side, an image not shared between different SKUs, and alt text by language.
• Copy: a title that is not all caps, a description aligned with the attributes, and no messy HTML.
• Duplicates: the same title with size or color to be grouped only after confirmation.
• Freshness: price and availability matching on the page and in the feed.
• Channels: a product page ready for Google Shopping, the ChatGPT feed, Meta, a PDF or the store.

How AI rewrites product pages without inventing data

The rewrite starts with the merchant's facts and discards every claim that does not pass the verifier for brands, certifications and measurements.

An illustrative before-and-after example, without traffic results. Before: title “BLUE VASE 20CM”, empty description, missing material attribute, the same image across three SKUs and no GTIN. After, if the facts are already present on a label or in a PDF: correctly formatted title, material and diameter only if they appeared in the store's materials, a description repeating the stated color and use, and alt text written by looking at the image. If the diameter is not among the facts, it stays out. If the manufacturer's GTIN is missing, its absence is stated; the code is not searched for online and, if read from packaging, a PDF or CSV column, it must pass the GS1 check digit.

Anyone with a price-list PDF can extract text blocks and embedded images, then match them to products. Anyone with only an image receives a draft product page to review. Images generated for products without photos should be labeled as illustrative, according to the marking required for generated content. A photo studio created from an existing image produces a scene or background; the result must be checked, the scanner does not remove the background automatically and does not state resolutions.

The merchant-declared data takes precedence over any measurement found elsewhere: if the two values conflict, the external measurement is not added to the product page.

WooCommerce synchronization and channel readiness

On WooCommerce, writing is bidirectional by SKU and does not create duplicates; on other channels, only ready content is exported, with different fields for Google and ChatGPT.

The official plugin on WordPress.org aligns the catalog by item code. Bulk actions clearly distinguish free corrections from paid ones and show credits before confirmation. A Google taxonomy category is suggested for each store category; the identifier enters feeds only after the merchant confirms it.

An ACP feed is the product file ChatGPT uses to list items for sale, according to the OpenAI specification. The required fields are nine: item_id, title, description, url, brand, seller_name, image_url, availability and price with currency. GTIN and MPN are optional, and a GTIN is never invented. The link and image_link names belong to Google Merchant Center, not the ChatGPT feed: they should not be mapped as required fields for OpenAI. Only in a Google-compatible profile, when OpenAI confirms it, is a GTIN or MPN required, unless that profile states that the identifier does not exist.

1. Check that every row has the nine OpenAI fields completed and matching the product page.
2. Leave GTIN empty if it is not in the store's materials; do not copy a code from another item.
3. Export a separate CSV for Google Shopping with Merchant Center field names and only ready product pages.
4. Group variants with item_group_id only after confirmation.
5. Check that the feed price and availability match what is visible in WooCommerce.

Images are measured by side and format. According to Google's documentation, there is a recommended minimum side for images; Meta already requires it. The check can write alt text by looking at the image, by language, at no cost. Shared images across several products are flagged because an assistant and a feed treat them as the same visual object.

Common errors

The most frequent errors mix up feed fields, invent identifiers or make the image say something it does not show.

The first error appears when a ChatGPT file contains columns intended for Merchant Center, or when url or image_url is missing while people focus on an unavailable barcode. This happens because a Google export is reused. The solution is to keep two files: the nine OpenAI fields in one, and Google's field names in the other.

The second error appears when a GTIN is added even though it is not on the label, PDF or CSV. This happens because the code is searched for online or copied from a variant. The solution is to read only the store's materials and, if the manufacturer does not provide one, state that it is unavailable.

The third error appears when a season, audience or “inferred” price range is added to the product page based on the image. This happens because the model is asked to complete information beyond what is visible. The solution is to limit image reading to brand, category, color, size, material and printed codes.

The fourth error appears as all-caps titles, leftover HTML and the same image on different SKUs. This happens when content is copied from marketplaces. The solution is to use confirmed, never silent, reversible corrections for thirty days: Title Case, HTML cleanup, condition and variant grouping.

The fifth error appears when people expect Vinted or Shopify to update automatically. The Shopify connection is not available. On Vinted, the product page is prepared and published manually. The solution is to use WooCommerce as the writable channel and the others as controlled copy channels.

How to get started without an SEO team

Start with a free read-only scan and pay only for catalog actions, with credits that do not expire and no subscription.

The one-time trial includes ten free credits, requires no card and does not renew. You can then purchase packages that do not expire. A rewritten product page costs one credit, and an image costs one credit. No per-page timing is promised: what counts is the action and the credit, not the clock.

1. Start a scan of the public WooCommerce catalog, with up to one hundred products.
2. Open the Problems column and the “fix now” dashboard.
3. Confirm free corrections that do not affect product facts.
4. Request rewriting or field completion only where Completeness identifies genuine gaps.
5. Synchronize by SKU and, if needed, export the Shopping CSV or ChatGPT feed containing only ready product pages.

How Katapic fixes the catalog without invisible work

Katapic is generative AI catalog management software designed for WooCommerce: it scans in read-only mode, assigns scores and writes only after confirmation, without inventing specifications.

The anonymous scan does not change the store. For every product, the traditional search score, assistant readiness, Relevance and Completeness remain visible. The audit engine lists findings in six areas with a correction path. Bulk actions show credits before confirmation. Rewriting uses a claims verifier and does not charge the credit if the text does not pass. The GTIN is not searched for online.

Anyone who already has WooCommerce can install the official plugin and synchronize by SKU. Anyone without a store can copy the product page in marketplace formats. You can import from images, PDFs and CSVs, suggest a Google category, group variants after confirmation, export the Shopping feed and ChatGPT feed, and format a catalog PDF. Image checks and alt text by language remain free.

Ten free credits once, then packages that do not expire, with no subscription. The principle is the same as throughout the article: merchant facts, explicit consent and no fabricated specifications. You can start from the Katapic page and launch a scan of the public catalog.

Frequently asked questions

What does generative AI catalog management software do?

It reads the catalog, finds empty or inconsistent fields and suggests copy and attributes based on facts already in the product page, images or files. It does not replace WooCommerce. After confirmation, it can write by SKU. AI must not invent brands, certifications, measurements or GTINs. Scores and the problem list come before generation, so you can decide where to spend credits.

How does AI product cataloging work?

First comes the deterministic audit, followed by generation if requested. The system imports from a store, image, PDF or CSV. Mechanical corrections, such as capitalization, HTML and condition, are confirmed. Rewriting or completion of empty fields with web facts and a source is requested only where needed. The consistency safeguard blocks anything that contradicts the merchant's title. The result is reviewed before synchronization.

How do you get an SEO and AEO score for WooCommerce products?

A read-only scan, even without an account and with up to one hundred products, assigns two separate scores: traditional search and assistant readiness, plus Relevance and Completeness. It is not a guarantee of ranking or citation. It shows which facts are missing. Page text and the markup already produced by WooCommerce remain aligned: the data is strengthened rather than adding an external schema.

Can product pages be rewritten without inventing data?

Yes, if the engine preserves store facts and verifies brands, certifications and measurements. A measurement found online that contradicts the product page is not included. GTIN is read only from packaging, a PDF or CSV and must pass the GS1 check. If the text does not pass the verifier, the rewrite credit is not charged. Human confirmation always remains necessary before writing to the catalog.

How does automatic WooCommerce catalog synchronization work?

With the official plugin, synchronization is bidirectional by SKU and does not create duplicates. Confirmed fields are updated, and products are not invented. Shopify is not connected. On Vinted, the prepared product page is published manually. Price and availability must match between the page and feed; otherwise Google Shopping and ChatGPT receive an object that differs from what the customer sees.

Which fields are required in a ChatGPT product feed?

According to the OpenAI specification, the required fields are nine: item_id, title, description, url, brand, seller_name, image_url, availability and price with currency. GTIN and MPN are optional; GTIN is never invented. Link and image_link are Google Merchant Center field names, not ChatGPT feed fields. In a Google-compatible profile, when OpenAI confirms it, a GTIN or MPN may be required, or the profile can state that the identifier does not exist.

Does the free scan change products in the store?

No. The initial scan of a public WooCommerce catalog is anonymous and read-only, with up to one hundred products and no account. It does not write titles, descriptions or prices. Corrections, including free ones, start only after explicit confirmation and remain reversible for thirty days. Without consent, the store stays as it is; only the visible report and scores change.

Further reading

• Product catalog SEO