How to Fix “Unparsable Structured Data” Error in GSC

Unparsable structured data is a Google Search Console error indicating schema markup on your pages contains syntax errors, invalid JSON-LD format, or incorrect implementation preventing Google from reading and using the structured data.

At HiAgency, we resolve structured data errors for Australian businesses through comprehensive Technical SEO audits, fixing syntax errors, validating schema implementation, and ensuring proper rich results eligibility.

This guide explains what unparsable structured data means, common causes, and step-by-step solutions to fix schema markup errors.

What Does “Unparsable Structured Data” Mean?

“Unparsable structured data” is a Google Search Console error appearing in the Enhancements report indicating Google encountered schema markup on your pages but couldn’t parse (read and interpret) it due to syntax errors or formatting problems.

Structured data uses standardized formats (JSON-LD, Microdata, RDFa) to describe page content to search engines. When implemented correctly, structured data enables rich results – enhanced search listings displaying additional information like star ratings, prices, event dates, or recipe details.

Unparsable errors prevent Google from understanding your structured data, eliminating eligibility for rich results despite having schema markup present.

Why Does This Error Occur?

Unparsable structured data errors typically result from JSON-LD syntax mistakes or implementation problems.

Missing or Extra Commas

JSON-LD requires commas between properties but not after the last property in an object. Missing commas or trailing commas cause parsing failures.

Incorrect examples:

• Missing comma: “name”: “Product” “price”: “99” (missing comma between properties)
• Trailing comma: “name”: “Product”, “price”: “99”, } (comma after last property)

Missing or Mismatched Brackets

Every opening bracket { or [ requires corresponding closing bracket } or ]. Mismatched brackets break JSON structure.

Example: { “name”: “Product”, “offers”: { “price”: “99” } (missing closing } for main object)

Unescaped or Missing Quotes

Property names and string values require double quotes. Missing quotes or quotes within strings without escaping cause errors.

Incorrect examples:

• Missing quotes: {name: “Product”} (property name needs quotes)
• Unescaped quotes: “description”: “This is a 10″ tablet” (quote inside string breaks syntax)

Invalid Characters or Encoding Issues

Special characters, line breaks, or encoding problems in property values can break JSON parsing.

Common issues include:

• Unescaped line breaks in descriptions
• Special characters not properly encoded
• Smart quotes (” “) instead of straight quotes (” “)
• HTML tags within JSON-LD values

Incorrect Data Types

Schema.org properties expect specific data types (text, number, date, URL). Providing wrong types causes validation errors.

Examples:

• Price as text with currency symbol: “price”: “$99” (should be number: “price”: 99)
• Date in wrong format: “startDate”: “12/25/2024” (should be ISO format: “2024-12-25”)

Invalid or Missing Required Properties

Each schema type requires specific properties. Missing required properties or using invalid property names causes errors.

How to Identify Unparsable Errors?

Google Search Console and Rich Results Test tool help identify specific parsing problems.

Step 1: Open Google Search Console, navigate to Enhancements section

Step 2: Look for “Unparsable structured data” error in enhancement reports (Product, Recipe, Event, etc.)

Step 3: Click error to view affected URLs

Step 4: Use Rich Results Test tool (search.google.com/test/rich-results) entering affected URL

Step 5: Review error messages showing specific problems:

• Syntax errors with line numbers
• Missing required properties
• Invalid property values
• Parsing failures with descriptions

Rich Results Test provides exact error locations and descriptions making identification straightforward.

How to Fix Unparsable Structured Data?

Fixes depend on specific syntax errors or validation problems identified.

Solution 1: Fix JSON-LD Syntax Errors

Correct syntax mistakes preventing JSON parsing.

Common fixes:

• Add missing commas: Place commas between all properties except the last one
• Remove trailing commas: Delete commas after last property in objects
• Match brackets: Ensure every { has closing } and every [ has closing ]
• Add missing quotes: Property names and string values need double quotes
• Escape internal quotes: Use ” for quotes within strings: “description”: “This is a 10″ tablet”
• Remove line breaks: Replace line breaks in strings with n or remove entirely

Validation: Use online JSON validator (jsonlint.com) pasting your JSON-LD code to identify syntax errors before testing in Rich Results Test.

Solution 2: Fix Data Type Errors

Ensure property values match expected data types.

Correct formats:

• Numbers: No quotes, no currency symbols: “price”: 99.99
• URLs: Full absolute URLs: “url”: “https://example.com/product”
• Dates: ISO 8601 format: “startDate”: “2024-12-25” or “2024-12-25T19:00:00”
• Currency: Three-letter code: “priceCurrency”: “AUD”
• Boolean: true or false (no quotes): “inStock”: true

Solution 3: Add Missing Required Properties

Include all required properties for your schema type.

Common required properties by type:

• Product: name, image, offers (with price, priceCurrency, availability)
• LocalBusiness: name, address, telephone
• Recipe: name, image, author, datePublished, description, prepTime, recipeIngredient
• Event: name, startDate, endDate, location, offers
• Article: headline, image, datePublished, author

Review schema.org documentation for complete required property lists for your schema types.

Solution 4: Remove Invalid Properties

Delete properties that don’t exist in schema.org specifications or are misspelled.

Use exact property names from schema.org documentation (case-sensitive). Common mistakes include:

• “telephone” not “phone”
• “priceRange” not “pricerange”
• “aggregateRating” not “rating”

Solution 5: Fix Template-Generated Errors

If errors affect many pages, the problem likely exists in schema templates or automatic generation code.

Template fix process:

Step 1: Identify template file or plugin generating schema (WordPress: theme functions, SEO plugins)

Step 2: Fix syntax errors in template code

Step 3: Test fixes on single page using Rich Results Test

Step 4: Deploy template changes affecting all pages

Step 5: Validate multiple affected pages confirming fixes work consistently

Solution 6: Handle Dynamic Content Properly

Dynamic values inserted into schema (prices, dates, availability) may introduce syntax errors if not properly escaped.

Safe dynamic insertion:

• Escape quotes in dynamic text values
• Validate dynamic values before inserting (ensure prices are numbers, dates are formatted correctly)
• Handle missing values gracefully (use conditional logic to omit properties rather than insert empty/null values)
• Test edge cases (products with special characters in names, very long descriptions)

How to Validate Fixes?

After fixing unparsable errors, verify corrections work properly.

Validation process:

Step 1: View page source confirming schema changes are live

Step 2: Use Rich Results Test tool entering page URL

Step 3: Verify “Valid” status with no parsing errors

Step 4: Check that all required properties show valid values

Step 5: Test multiple affected pages if template changes were made

Step 6: In Google Search Console, click “Validate Fix” for the unparsable structured data error

Step 7: Monitor validation status over 3-7 days as Google recrawls and verifies fixes

Successful validation shows “Passed” status in Search Console with affected page count decreasing to zero.

Common Mistakes When Fixing This Error

Only Testing One Page When Template Affects Many

Fixing one page without updating templates leaves errors on remaining pages. Always fix root cause templates affecting multiple pages.

Not Using Rich Results Test Before Requesting Validation

Requesting validation in Search Console before confirming fixes work wastes time. Always verify using Rich Results Test first.

Leaving HTML in JSON-LD Values

HTML tags like <br>, <p>, or <strong> break JSON syntax. Strip HTML from values or properly escape if necessary.

Using Relative URLs

Schema properties expecting URLs require absolute URLs (https://example.com/page) not relative URLs (/page).

Mixing Schema Formats

Using JSON-LD and Microdata for same schema type on one page can cause conflicts. Choose one format consistently.

How Long Does Fixing Take?

Timeline for resolving unparsable structured data errors:

• Identification: 15-30 minutes using Rich Results Test identifying specific errors
• Fixing: 1-4 hours depending on error complexity and number of affected pages
• Validation: 3-7 days for Google to recrawl pages and verify fixes
• Rich results appearance: 1-2 weeks after validation for rich results to appear in search (not guaranteed)

Template-level fixes affecting hundreds of pages resolve faster than fixing pages individually. Once template is corrected, all pages benefit from fix during next crawl.

Does Fixing Unparsable Errors Guarantee Rich Results?

No. Fixing unparsable errors makes pages eligible for rich results but doesn’t guarantee Google will display them.

Rich results eligibility requires:

• Valid, parsable structured data (no errors)
• Meeting all required properties
• Content matching schema markup claims
• Page quality meeting Google’s standards

Google decides whether to show rich results based on query relevance, content quality, and search context. Fixing parsing errors is necessary but not sufficient for guaranteed rich results.

Should You DIY or Hire Specialists?

Small sites with simple schema implementations can often fix unparsable errors following Rich Results Test error messages and schema.org documentation.

Hire specialists when facing:

• Complex schema implementations with multiple types
• Template-level errors requiring code changes
• Large-scale issues affecting hundreds or thousands of pages
• Persistent errors despite attempted fixes
• Custom schema implementations requiring structured data expertise
• E-commerce sites with complex product markup

At HiAgency, we resolve unparsable structured data errors for Australian businesses through comprehensive schema audits, syntax error correction, template fixes, and validation. Our approach ensures proper schema implementation supporting rich results eligibility and enhanced search visibility.

Consider that structured data errors prevent valuable search enhancements that improve click-through rates and visibility. Professional expertise ensures schema implementations follow best practices while avoiding common pitfalls causing parsing failures.

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HiAgency

HiAgency is a digital marketing and web development agency specializing in SEO optimization and content management solutions. We help businesses improve their online visibility through technical implementations, user experience enhancements, and strategic content organization.

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