Product preflight for regulated commerce

Find the product issues that can cost visibility.

FeedZip checks claims, product data, and channel risks before they become disapprovals, suppressions, wasted spend, or rework.

No credit card. Clear findings—not promises of platform approval.

Good products deserve a fair path to market.

AI Shopping Readiness

See how AI reads your product

Preflight

Review claims before you commit

Suppression Recovery

Find out why it got blocked

Compliance Review

Catch ad disapprovals before you spend

Built-in · AI Shopping Readiness

Turn product copy into structured data machines can read.

FeedZip separates facts, claims, attributes, and sources — then returns machine-readable structured output shopping, search, marketplace, feed, and AI assistants can parse reliably, while your brand story still comes through.

Paste any product copy. No setup, no code.

Readiness Generator

Structured product data · Google Shopping

Step 1 of 2 — Product source

Product name (optional)

e.g., Omega-3 Fish Oil Softgels

Product copy *

Paste the product title, bullets, description, or claims…

What the structured output contains

Normalized attributes

Cleaner, reusable product fields.

Claims vs. facts

What it is — and what the brand says.

Source status

Supplied, extracted, inferred, or missing.

Conflict resolution

Surface inconsistencies, don't merge them.

Structured output

Reusable fields and schema.

Channel expressions

Tuned for Google, ChatGPT, Amazon.

Continue

Built-in · Suppression Recovery

Turn a suppression into a policy-cited appeal kit.

When a listing gets flagged, FeedZip maps each phrase to the exact platform policy it triggered, drafts before/after corrections, and writes a six-section formal appeal letter — packaged as a downloadable PDF you can submit.

Already dealing with enforcement? This is where to start.

Appeal Kit Generator

Policy-cited PDF appeal document · Google Ads

Step 1 of 2 — Your details

Brand / Business name *

e.g. Vitality Labs

Your name (optional)

e.g. Jane Smith

What this appeal kit contains

Violation breakdown

Each issue tied to its policy rule.

Before / after table

Every change and why it's needed.

Policy references

Links to official policy pages.

Formal appeal letter

Six-section letter, ready to submit.

Evidence checklist

What to attach as proof.

Revised listing copy

Compliant copy to resubmit.

Continue

FeedZip.ai Real analysis

Check a product before the platforms do.

Paste the product information you have. FeedZip will identify potential claim risks, missing or inconsistent data, and channel concerns—then show you what to review next.

1What are you reviewing?

Product name (optional)

2Paste your product copyRequired

Your copy isn’t stored

3Where will this run?

Category selectedChannels selectedAdd product copy

Paste product copy and pick a channel to continue.

See what FeedZip finds

See what FeedZip finds.

FeedZip shows the finding, the reason it matters, the information it relied on, and a lower-risk alternative when one is appropriate.

Example review

Original language

“Clinically proven to eliminate joint pain.”

Potential issue

Therapeutic / outcome claim

Why it matters

“Eliminate joint pain” can be interpreted as a treatment claim. “Clinically proven” also requires substantiation appropriate to the exact product and claim.

Lower-risk alternative

“Supports joint comfort and everyday mobility.”

Also found

Ingredient naming conflict · Identifier not supplied · Structured data incomplete

Source status

Claim: supplied · Ingredient conflict: extracted · Identifier: missing · Alternative copy: recommended

This example illustrates a FeedZip review. Recommended wording can reduce an identified content risk but does not guarantee platform approval or regulatory compliance.

What you get

A useful review—not a mystery score.

Findings organized by what needs attention, why it matters, and what to do next—across Google, Meta, Amazon, TikTok, Walmart, Shopify, and AI shopping.

Claim review

Disease, therapeutic, guarantee, and substantiation concerns in your language.

Product-data review

Missing or inconsistent attributes that affect feeds and machine interpretation.

Channel guidance

Findings organized for the platforms you selected.

Lower-risk copy

Alternatives that preserve the benefit while addressing the concern.

Prioritized next steps

What to change now, what to verify, what to flag.

Structured output

Reusable product fields and schema where sources support them.

Built for the places commerce happens

FeedZip helps ecommerce teams find risks before they become disapprovals, suppressions, or wasted spend.

Preflight Checks

Check product listings before advertising or distribution. Identify risky claims, missing data, and channel conflicts before they become larger problems.

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Product Compliance

Evaluate product content against the requirements and restrictions that affect how products can be represented across commerce and advertising platforms.

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Claims Risk

Identify language that may create advertising, marketplace, regulatory, or substantiation risk—especially for sensitive categories.

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Product Data Validation

Find missing, inconsistent, or poorly structured information that can interfere with feeds, listings, ad eligibility, and machine understanding.

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Channel Risk

Understand how product content may be interpreted differently across Google, Meta, Amazon, TikTok Shop, Walmart, Microsoft, Shopify, and AI surfaces.

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Suppression

Identify issues that can cause products to be rejected, restricted, quietly limited, or removed from important commerce surfaces.

Explore

Recovery & Appeals

When a product is already affected, identify likely violations, organize corrective actions, and build a structured response for appeal.

Explore

AI Shopping Readiness

Evaluate whether product information is structured, consistent, and complete enough to be interpreted by AI shopping systems and commerce agents.

Explore

Read the Knowledge Base Explore Channel Guides

Built from enforcement experience

Built from real-world enforcement.

FeedZip grew from years of listing suppressions, feed problems, claim reviews, and appeals across large catalogs—now distilled into a faster first review.

20+ years

Commerce and catalog operations

Thousands of SKUs

Across complex commerce environments

Real catalog ops

Founder-led marketplace appeal and suppression workflows

Built for the team accountable when a product gets stuck.

Brands and product teams

Catch claim and content risks before PDPs and launches get expensive to change.

Agencies and growth teams

Spot product, landing-page, feed, and claim issues before campaigns spend.

Catalog and commerce teams

Review data consistency and channel readiness across a catalog.

Under every review

One product. Many channels. One source of truth.

Behind every review is Product Truth—a structured, sourced representation separating what a product is, what’s claimed, where each fact came from, and how to express it across channels.

Sources

Label · PDP · Feed · COA · Product data

Product Truth

Identity · Attributes · Claims · Evidence · Conflicts · Confidence

Expressions

Preflight · Ads · Marketplaces · Schema · Appeals · AI

Product Truth is how FeedZip keeps a product consistent without forcing every channel to use identical language.

Find the issue. Understand the reason. Know what to fix.

FeedZip begins with a practical review—then expresses that product knowledge across every commerce surface.

FeedZip provides guidance—not a guarantee of platform approval or visibility.