Convert B2B Customer Ratings to AggregateRating Schema
✓ TestedWorks with CSV, Excel, Google Sheets → JSON-LD Schema
By dataclean.to team · 2026-02-05
B2B customer satisfaction data converts to AggregateRating schema for product visibility. Review platforms and internal feedback systems contain rating information that maps to AggregateRating properties. This conversion displays star ratings in business product search results.
The Problem
B2B companies collect customer ratings across G2, Capterra, TrustRadius, and internal systems without unified schema. Product pages lack AggregateRating markup preventing star rating display in search. Combining ratings from multiple sources requires calculation and schema generation. Automated conversion handles data aggregation and markup creation. Schema.org AggregateRating specification
How to Fix It
1
Upload Rating Data
Import customer reviews and ratings from review platforms or internal databases with scores and review counts.
2
Aggregate Rating Statistics
Calculate average ratings, total review counts, and distribution across the rating scale for each product or service.
3
Map to Schema Properties
Assign aggregated data to AggregateRating fields including ratingValue, reviewCount, bestRating, and worstRating.
4
Link to Products
Connect ratings to their respective products using itemReviewed with Product or Service schema references.
5
Export Rating Schema
Generate AggregateRating JSON-LD for integration into product pages and service listings.
Frequently Asked Questions
Can I combine ratings from multiple platforms?
Import reviews from all platforms into one dataset, calculate combined statistics, and generate a single AggregateRating representing total customer feedback.
How often should I update AggregateRating schema?
Update schema whenever new reviews arrive or at regular intervals. Fresh rating data maintains search result accuracy as customer feedback evolves.
What if different platforms use different scales?
Normalize all ratings to a common scale (typically 1-5) before aggregation. Convert 10-point or 100-point scales proportionally to the standard range.
Example: Input → Output
name
email
phone
city
status
Alice Johnson
alice@example.com
+1-555-0101
New York
active
alice johnson
ALICE@EXAMPLE.COM
5550101
new york
Active
Red rows show common data quality issues. dataclean.to normalizes and generates JSON-LD automatically.