dataclean.to

Generate Review Schema from Customer Feedback Data

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

Review databases contain customer feedback with ratings, text reviews, reviewer information, and timestamps. Review schema enables rich search results with star ratings and review snippets. Structured review data improves trust signals and enables review filtering in search features.

The Problem

Review databases store ratings on inconsistent scales and lack standardized aggregation across products or businesses. Reviewer attribution may be incomplete and review dates ambiguous. Without Review schema markup, search engines cannot display star ratings, review counts, or reviewer credibility indicators, reducing social proof impact on search visibility and conversion. Schema.org Review

How to Fix It

1
Extract Review Core Data
Parse review text content, headline, and publication date. Identify review language and sentiment. Extract review ID or URL for reference and duplicate detection.
2
Parse Rating Information
Extract rating value and identify rating scale (5-star, 10-point, etc.). Map to reviewRating property with Rating schema including ratingValue, bestRating, and worstRating to normalize scales.
3
Structure Reviewer Information
Extract reviewer name, username, or identifier. Include reviewer reputation indicators like verified purchase status or review count. Map to author property using Person schema.
4
Link to Reviewed Entity
Identify the product, business, or service being reviewed. Map to itemReviewed property using appropriate schema type (Product, LocalBusiness, Service, etc.) with at minimum a name field.
5
Generate Review Schema JSON-LD
Output Review schema with required reviewRating and itemReviewed fields. Include reviewBody for text content, author for reviewer, datePublished, and optional reviewAspect for specific features reviewed.

Frequently Asked Questions

How should I normalize ratings from different rating scales?
Always include bestRating and worstRating in the Rating object to indicate scale. For a 5-star system use bestRating of 5, for 10-point use 10. This allows search engines to normalize comparisons across different rating systems.
Can I include review responses from business owners in Review schema?
Yes, nest a Review object within the original review using the reviewRating property is not required for responses. Alternatively, use Comment schema for simpler response structures or include in the review's text with clear attribution.
Should individual reviews include AggregateRating information?
No, AggregateRating goes on the entity being reviewed (Product, Organization, etc.), not on individual Review objects. Each Review has its own reviewRating with an individual rating value, while the reviewed item has aggregateRating summarizing all reviews.

Example: Input → Output

nameemailphonecitystatus
Alice Johnsonalice@example.com+1-555-0101New Yorkactive
alice johnsonALICE@EXAMPLE.COM5550101new yorkActive

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

{
  "@context": "https://schema.org",
  "@type": "Dataset",
  "name": "Cleaned Customer Data",
  "description": "Normalized customer records with standardized fields",
  "keywords": ["customer data", "CRM", "contact list"]
}
💡 How it works: Consistent data formatting reduces import errors and makes your dataset compatible with downstream tools.

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