dataclean.to

Clean Product Data for Google Merchant Center

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-13

Google Merchant Center is the gateway to Google Shopping, free product listings, and Performance Max campaigns. But Merchant Center is notoriously strict about data quality — even small formatting inconsistencies can cause product disapprovals, account warnings, or feed-level suspensions. dataclean.to helps you identify and fix data quality issues in your product feed before upload, reducing disapproval rates and getting your products listed faster.

The Problem

Merchant Center disapproves products for dozens of reasons, many of them data formatting issues that are hard to catch manually. GTINs fail checksum validation because of transcription errors. Prices don't match what's on your landing page because the feed has stale data. Shipping weights use inconsistent units. Product titles exceed character limits or contain promotional text that violates Google's policies. Color and size values don't match Google's standardized attribute values. When you're managing hundreds or thousands of SKUs, these issues compound into a significant percentage of your catalog being disapproved at any given time. Google Merchant Center product data specification

How to Fix It

1
Import your product feed data
Upload your product data CSV or spreadsheet to dataclean.to. The platform accepts feeds in any format — you don't need to pre-format columns to match Google's naming conventions before importing.
2
Auto-detect product data fields
dataclean.to identifies product-specific field types: GTINs/EANs/UPCs (with checksum validation), prices with currency detection, weight and dimension values, URL fields for product pages and images, and categorical fields like brand, color, and condition.
3
Fix common Merchant Center rejection issues
Apply cleaning rules that address the most frequent Merchant Center disapprovals. GTINs are validated against check digit algorithms. Prices are normalized to decimal format with correct currency codes. Availability maps to Google's four accepted values. Product titles are checked against character limits.
4
Validate required and recommended attributes
Ensure every product has the required attributes (id, title, description, link, image_link, price, availability, brand or GTIN) and review recommended attributes (color, size, material, product_type, google_product_category) that improve listing quality and reduce disapprovals.
5
Export Merchant Center-ready feed
Download the cleaned data as a CSV using Google's expected column headers and value formats. The export is formatted for direct upload to Merchant Center via file upload, scheduled fetch, or Content API integration.

Frequently Asked Questions

What GTIN validation does dataclean.to perform?
dataclean.to validates GTIN-8, GTIN-12 (UPC), GTIN-13 (EAN), and GTIN-14 formats. It checks that the number has the correct length, contains only digits, and passes the check digit algorithm. Invalid GTINs are flagged so you can correct them before Merchant Center rejects the product.
Can dataclean.to help with Merchant Center's price mismatch errors?
dataclean.to normalizes price formatting in your feed data — removing currency symbols, fixing decimal separators, and standardizing to the format Merchant Center expects. However, price mismatch errors (where feed price differs from landing page price) require updating either your feed or your website to make them consistent.
How does this differ from cleaning data for Google Shopping specifically?
Google Merchant Center is the platform where you manage your product data; Google Shopping is one of the surfaces where products appear. Cleaning for Merchant Center covers all feed requirements including free listings, Shopping ads, and Buy on Google. The data requirements are the same regardless of which Google surface you're targeting.

Example: Input → Output

nameskupricebrandrating
Wireless Headphones ProWHP-001$89.99SoundTech4.5
wireless headphones proWHP00189.99soundtech4.5/5

Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Wireless Headphones Pro",
  "sku": "WHP-001",
  "offers": {"@type": "Offer", "price": "89.99", "priceCurrency": "USD"},
  "brand": {"@type": "Brand", "name": "SoundTech"},
  "aggregateRating": {"@type": "AggregateRating", "ratingValue": "4.5"}
}
💡 How it works: Product schema enables rich results with price, availability, and star ratings in Google Shopping.

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