Waitlist + live packet preview

Recover suspended Google Merchant Center accounts faster

Q: Is this just a ChatGPT wrapper?

No. The output is built from deterministic parsing, policy mapping, and mismatch checks.

Q: Can I use this before requesting re-review?

Yes. Fix findings first, collect evidence, then request re-review.

Q: What inputs produce the best packet?

Diagnostics export, feed sample, and URL-level crawl findings.

Paste diagnostics JSON, feed rows, and crawl findings. AppealForge builds a deterministic evidence bundle with policy crosswalk, URL-level fixes, and a re-review draft.

Appeal Packet Generator

Primary suspension reason

GMC diagnostics export (JSON array or JSON lines)

Feed sample CSV (id,title,price,availability,link,image_link,crawl_price)

Crawler findings (one per line: url | finding | evidence)

Sample packet excerpt

Policy: Price and availability mismatch
Evidence count: 12
High-risk URLs: /products/a, /products/b, /products/c
Required fixes:
- Sync feed price + landing page price
- Remove stale out-of-stock SKUs
- Re-crawl and attach corrected screenshot evidence

Appeal line:
"We corrected all feed/landing inconsistencies and attached URL-level proof for re-review."

Join early access waitlist

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Policy crosswalk

Maps each finding to a concrete Merchant Center policy area with required fixes.

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Evidence bundle structure

Outputs the exact files you need for a defensible re-review submission.

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Deterministic checks

Not a prompt wrapper, rules engine validates feed and landing consistency URL by URL.

FAQ

Is this just a ChatGPT wrapper?

No. The core output comes from deterministic parsing, policy mapping, and mismatch checks across diagnostics, feed rows, and crawl evidence.

Can I use this before requesting re-review?

Yes, that is the best use case. Fix findings first, collect evidence, then submit your appeal packet.

What inputs produce the best packet?

Merchant diagnostics export, current feed sample, and crawl findings with URL-level notes.