ProMapRanker
Review Schema Generator
Generate compliant Review and aggregateRating JSON-LD for your products or local business to display star-rich snippets.
What is the Review Schema Generator?
The Review Schema Generator is a free tool that builds valid Review and aggregateRating JSON-LD structured data so your product or local business pages can qualify for star rating rich snippets in Google search. You paste in your rating value, review count, item name, and author details, and the review schema generator returns clean, copy-ready markup you can drop into the head of your page. No coding knowledge is required, and you never have to memorize the exact schema.org syntax.
The input is a handful of plain fields (the thing being reviewed, the score, the number of reviews, and who wrote the review). The output is a block of JSON-LD that search engines can read. This tool is built for local business owners, ecommerce store managers, marketing agencies, and anyone who wants those yellow stars to appear under their listing without hand-writing structured data from scratch.
Structured data is the invisible layer of your website that talks directly to search engines. Humans see your reviews as text and stars on the page, but a crawler needs that same information in a format it can parse without guessing. Review schema is the specific vocabulary that describes ratings, and the tool above assembles it for you in the JSON-LD format Google recommends. You stay focused on the business, and the markup stays correct, which matters because a single misplaced bracket or wrong property name can quietly stop your stars from ever showing.
How to use the Review Schema Generator
Using the tool takes under a minute. Fill in the fields in the widget above, generate the code, and paste it into your page. Here is the exact sequence to follow.
- Choose whether you are marking up a single review or an aggregate rating (a summary of many reviews). Most local business and product pages use the aggregate option because it reflects an overall star average.
- Enter the name of the item being reviewed. For a local business this is your business name, and for a store this is the product title exactly as it appears on the page.
- Type the rating value. This is the average score, for example 4.7, and it must fall inside the scale you set (most sites use a 1 to 5 scale).
- Add the review count, which is the total number of reviews that number is based on. Only count reviews your own site actually collects and displays.
- Fill in the author or reviewer name when you are marking up an individual review, plus the review body text if you want the quote included.
- Click generate. The tool outputs a finished JSON-LD block. Copy it and paste it into the <head> of the matching page, then validate it before you publish.
Why review schema matters for local SEO
Review schema is one of the highest-leverage pieces of structured data a local business can add. When Google reads valid Review schema markup on your page, it can show a star rating rich snippet directly in the search results. Those stars make your listing stand out, and a more eye-catching result tends to earn more clicks than the plain blue links around it. For a local business fighting for attention in a crowded map pack and organic area, that visual edge is worth having.
Think about how a searcher scans a results page. Their eye moves fast, and it stops on anything that breaks the pattern of plain text. A row of gold stars and a rating like 4.8 does exactly that. Two competing plumbers may both rank on page one, but the one showing a star rating rich snippet looks more established and more trustworthy before the searcher has read a single word of copy. That perception gap is the practical payoff of clean structured data, and it costs you nothing beyond the few minutes it takes to add the markup correctly.
Structured data also helps search engines understand your content with less guesswork. A page that says "4.8 stars from 212 reviews" in plain text is ambiguous to a crawler, but the same information wrapped in aggregateRating JSON-LD is explicit and machine readable. That clarity supports how your business is represented across Google Search and, in combination with your Google Business Profile, how customers perceive your reputation when they are deciding who to call. In local search especially, where trust and proximity decide who gets the phone call, being the listing that looks credible at a glance is a real advantage.
None of this replaces genuine reputation work. Review schema does not invent ratings or inflate them, and it will not rank a weak page on its own. What it does is make the real reviews you already earned eligible for a richer, more clickable presentation. Pair strong local rankings with clean structured data and you get both the position and the presentation working in your favor. The businesses that win in local search treat both as part of the same job rather than hoping rankings alone will carry them.
Understanding the JSON-LD this tool builds
The markup this review schema generator produces follows the schema.org vocabulary that Google reads. Below is a breakdown of each part so you know exactly what you are pasting into your page and why each field is there.
The Review object
The Review object is the core wrapper. It uses the schema.org Review type and holds the details of a single opinion about something. Inside it you name what was reviewed, who wrote it, the score they gave, and optionally the text of the review. This is the building block Google looks for when deciding whether a page is eligible for a review rich result.
aggregateRating
When you want to summarize many reviews into one overall score, you use aggregateRating instead of a single Review. This object represents the combined average, so it is what most local business and product pages rely on. The aggregateRating in your JSON-LD tells search engines the overall star level for the item and how many opinions that average is built from.
ratingValue and reviewCount
These two properties do the heavy lifting. The ratingValue is the numeric score, such as 4.7, and it must sit within the bestRating and worstRating range you declare (commonly 5 and 1). The reviewCount states how many reviews produced that average. Both need to match the real, visible numbers on your page, because mismatched or invented values violate Google's structured data policy and can trigger a manual action.
author and itemReviewed
The author property names the person or organization that wrote a single review, and itemReviewed identifies exactly what the review is about, whether that is a Product, a LocalBusiness, or another supported type. Naming the itemReviewed correctly matters because Google only shows review snippets for specific content types, and a mislabeled item can quietly disqualify your markup. When you use aggregateRating, this is usually attached directly to the item type rather than nested inside a separate Review, which keeps the structure clean and easy for crawlers to follow.
bestRating, worstRating, and the rating scale
Every rating needs a scale so search engines know what the number means. The bestRating and worstRating properties declare the top and bottom of that scale, and if you leave them out Google assumes a 1 to 5 range. Setting them explicitly prevents confusion when your site uses a different scale, such as 1 to 10, and it guarantees your ratingValue is interpreted the way you intended rather than being silently rescaled.
Best practices and common mistakes to avoid
Getting the syntax right is only half the job. The bigger risk is breaking Google's rules for review rich results, which are stricter than many people expect. Follow these tips to stay eligible and avoid a penalty.
- Do not mark up self-serving reviews. Google explicitly disallows review markup where the business writes or solicits a review about itself and hosts it as first-party structured data on its own page. Use aggregateRating for genuine customer ratings instead.
- Only mark up reviews your site actually hosts and displays to visitors. Pulling star ratings from a third-party platform and injecting them into your JSON-LD, when those reviews do not appear on the page, is against policy and is a common cause of failed rich results.
- Keep the ratingValue inside a valid range. If you use a 1 to 5 scale, a ratingValue of 4.7 is fine, but a value above your declared bestRating or below your worstRating is invalid and will be ignored.
- Make the visible content match the markup. The rating and review count in your structured data must be the same numbers a human sees on the page. If they differ, Google may treat the markup as spam.
- Pick the correct schema type for what you are reviewing. Review snippets are supported for a defined set of types such as Product and LocalBusiness, so do not attach them to unsupported content like a category page or your homepage in general.
- Validate every page before you publish. Run the generated JSON-LD through a testing tool to catch missing required fields, then recheck after any template change so a site update does not silently break your Review schema markup.
Common use cases
This tool fits several real situations. Here are the most common ones and how each plays out in practice.
- Local business pages. A dentist, plumber, or restaurant adds aggregateRating markup to a service or location page so their genuine customer star average can appear in search, reinforcing the trust signals customers already see on their Google Business Profile.
- Product pages. An online store marks up each product with the average rating and review count collected on that product page, giving individual listings a shot at star rating rich snippets that lift click-through from search.
- Agencies managing many clients. A marketing agency uses the generator to produce consistent, policy-safe JSON-LD across dozens of client sites without hand-coding each one, which saves time and reduces the chance of a costly markup error.
- Migrating away from a plugin. A site moving off a bloated reviews plugin or a page builder can generate clean standalone structured data here, drop it in directly, and remove the extra plugin weight while keeping the same star snippet eligibility.
- Fixing markup that stopped working. If a site once showed stars and then lost them after a redesign, the old plugin or theme may have output invalid or outdated JSON-LD. Regenerating fresh, policy-compliant markup and validating it is often the fastest way to recover the snippet without a full audit.
Across all of these, the common thread is the same. You have real reviews, you want them represented accurately in search, and you do not want to spend an afternoon debugging syntax. The tool handles the format so you can spend your time on the reputation itself, which is the part that actually earns the ratings.
Frequently asked questions about the review schema generator
What does a review schema generator actually do?
A review schema generator turns simple inputs like your rating, review count, and item name into valid Review or aggregateRating JSON-LD. You copy that output into your page head so search engines can read it and potentially show a star rating rich snippet. It removes the need to write structured data by hand.
Will this guarantee star ratings show in Google?
No tool can guarantee stars. Valid markup only makes your page eligible for a review rich result. Google decides whether to display it based on your content, the item type, and its policies. Accurate, honest structured data on a supported page type gives you the best chance, but display is always at Google's discretion.
Is the JSON-LD from this review schema generator free to use?
Yes. The review schema generator and the JSON-LD it produces are completely free, with no sign-up required to generate code. You own the output and can paste it into any page you control. There are no watermarks, no hidden branding, and no limit on how many code blocks you create.
What is the difference between Review and aggregateRating?
A Review represents one person's opinion, including their name, score, and comment. An aggregateRating represents the combined average of many reviews, using a ratingValue and a reviewCount. Most local business and product pages use aggregateRating because it shows an overall star average rather than a single individual review.
Where do I place the generated code on my page?
Paste the JSON-LD inside the <head> section of the specific page it describes, ideally near your other structured data. It can also sit in the body, but the head is cleanest. Make sure the same rating and review numbers are visible to users on that page, then validate the markup before publishing.
Do I need to add the code to every page or just once?
Add review markup to each individual page it describes, not once for the whole site. A product page carries that product's rating, and a location page carries that location's aggregate. The rating and count on each page must match what visitors see there, so a single sitewide block would be inaccurate and would not qualify for rich results.
Which sources define the rules for review structured data?
The authoritative references are Google's review snippet documentation and the schema.org Review type definition. Google's page covers eligibility and policy, while schema.org defines the exact properties. Reading both before you publish helps you avoid the mistakes that disqualify markup from showing.
If you run a local business and you care about star snippets, you also care about where you actually rank on Google Maps, and that is where ProMapRanker comes in. Clean review schema markup makes your listing more clickable, but you still need to know your true position across the grid of searches your customers run. You can start free with 150 credits and see exactly where you stand before you spend a dollar.
Related tools
- Product Schema Generator for building Product structured data with pricing and availability.
- Local Business Schema Generator for marking up your name, address, hours, and location.
- FAQ Schema Generator for turning your questions and answers into eligible FAQ markup.
- JSON-LD Validator for checking any structured data you generate before you publish it.
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