It reads the plugin's per-product sync status from _wc_gla_sync_status, error messages from _wc_gla_errors, and the Merchant Center ID. Standard WooCommerce attributes like SKU, GTIN, brand, and category are pulled from regular postmeta and taxonomies. Setup takes a few minutes per data source.

Yes. The plugin stores the raw Merchant Center error code and message in postmeta. The bot reads both, translates the error into plain language, and points at the exact field or image to fix. Common ones like missing GTIN, image-link issues, and promotional overlay text are explained with a concrete next step.

Yes. SleekAI reads product and order data through the WooCommerce data layer, so legacy post-based orders and High-Performance Order Storage both work. The GLA plugin writes its sync metadata against product posts regardless of the order storage mode, so the bot's view is unchanged.

No, as long as you scope the bot correctly. Display conditions restrict the feed-status bot to logged-in admins or shop managers on wp-admin URLs. A separate sales chatbot for the storefront has no access to GLA variables in its system message, so customers never see internal sync errors.

Yes. Because it reads the WooCommerce title, description, and gallery alongside the GLA error, it can suggest a rewritten title that includes the brand or a description that adds the missing attribute. Pair that with SleekAI's content generator and the fix can be one click instead of a manual edit.

Each variation is a child post with its own sync status. SleekAI's data sources can read the parent and the variations together, so the bot can confirm whether the medium-blue variant synced cleanly while the small-red one failed on a missing image, without you exposing the entire SKU list to the prompt.

Yes, with a bit of wiring. SleekAI exposes a function-call layer where the bot can trigger the GLA plugin's existing sync action for a single product or a batch. Most teams keep this manual at first and add the action once the read-only flow is stable.

Every conversation is stored inside WordPress with messages, model name, token usage, and originating page URL. You can spot patterns like repeat questions about a specific category failing, then fix the underlying attribute mapping once instead of answering the same question every week.