Review Schema

Review Schema helps search engines and AI systems understand real customer reviews and ratings when those reviews are properly shown and documented on a page.

Reviews are evidence.

Review Schema labels that evidence for machines.

That sounds simple because it is.

Where businesses get into trouble is when they try to turn Review Schema into a magic star machine.

There is no magic star machine.

Disappointing, I know.

What Is Review Schema?

Review Schema is structured data used to describe a review.

It can identify:

The goal is to help machines understand review information accurately.

Why Review Schema Matters

Customer reviews help establish trust.

They give search engines and AI systems another source of evidence about a business, product, service, or organization.

When reviews are clearly documented, they can support:

Reviews tell machines what customers have experienced.

That matters.

Review Schema Must Be Honest

Let’s be honest.

This is not the place to get creative.

If the review is not visible on the page, do not mark it up.

If the review is fake, do not mark it up.

If the rating is cherry-picked, misleading, or disconnected from the actual review, do not mark it up.

Structured Data should describe reality.

Not your dream version of reality.

Common Review Schema Properties

Property Purpose
Review Identifies the structured data as a review.
author The person or organization that wrote the review.
reviewBody The text of the review.
reviewRating The rating connected to the review.
itemReviewed The business, product, service, or item being reviewed.
datePublished When the review was published.

Where Review Schema Makes Sense

Review Schema can make sense on pages where real reviews are visible and relevant.

Examples include:

The key word is visible.

If users cannot see the review, machines should not be told it is there.

A Simple Example

This is a simplified Review Schema example.

{ "@context":"https://schema.org", "@type":"Review", "author":{ "@type":"Person", "name":"Jane Smith" }, "reviewBody":"Firm IQ helped us understand why our business was not showing up clearly in AI search.", "reviewRating":{ "@type":"Rating", "ratingValue":"5", "bestRating":"5" }, "itemReviewed":{ "@type":"Organization", "name":"Firm IQ" } }

Your actual implementation should match the visible review content and the real entity being reviewed.

Review Schema Is Not Review Strategy

This is important.

Review Schema does not help you earn reviews.

It does not respond to reviews.

It does not fix a bad customer experience.

It only labels review information that already exists.

If the business has a review problem, solve the business problem first.

The schema can come after.

Common Review Schema Mistakes

Most Review Schema mistakes come from chasing rich results instead of documenting trust.

That is backwards.

Review Schema and AI Visibility

AI systems increasingly summarize reputation.

They look for patterns in customer feedback.

They evaluate trust signals.

They compare claims against evidence.

Review Schema can help structure that evidence when the underlying reviews are real and useful.

But the schema is only as trustworthy as the reviews themselves.

Firm IQ Definition

At Firm IQ, Review Schema is machine-readable reputation documentation.

It helps search engines and AI systems understand real customer feedback when that feedback is visible, accurate, and connected to the correct entity.

It does not create trust.

It labels trust that has already been earned.

Here’s what we’ve learned: Review Schema works best when the reviews are real, specific, and earned. Fake trust signals are like fake plants. They may look fine from far away, but nobody should be impressed.

Related Concepts