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Generate AggregateRating Schema for B2B Products

✓ Tested Works with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-05

B2B rating data converts to AggregateRating schema for business product visibility. Customer reviews of software, services, and business products contain ratings that map to AggregateRating properties. This conversion displays star ratings in search results.

The Problem

B2B companies collect customer ratings without structured schema markup. Product review data exists across platforms like G2, Capterra, and internal systems. Search engines cannot display rating summaries without AggregateRating schema. Manual schema creation for products with hundreds of reviews is impractical. Schema.org AggregateRating specification

How to Fix It

1
Upload Review Data
Import customer ratings with product identifiers, individual ratings, review counts, and rating scale information.
2
Calculate Aggregate Statistics
Compute average ratings, total review counts, and rating distributions from individual customer reviews.
3
Map to AggregateRating Fields
Assign calculated statistics to ratingValue, reviewCount, bestRating, and worstRating properties.
4
Link to Rated Items
Connect ratings to Product, Service, or Organization schema using the itemReviewed property.
5
Export Schema Markup
Generate AggregateRating JSON-LD for product pages, service listings, or company profiles.

Frequently Asked Questions

What B2B products benefit from AggregateRating schema?
Software products, SaaS platforms, professional services, business equipment, and enterprise solutions all use AggregateRating schema to display customer satisfaction in search results.
How do I combine ratings from multiple platforms?
Import reviews from all platforms into a unified dataset, calculate combined statistics, and generate a single AggregateRating reflecting total customer feedback across sources.
What rating scale should I use?
Most B2B review platforms use 1-5 stars. Specify the scale using bestRating and worstRating properties. Convert other scales to the standard 1-5 range for consistency.

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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