Schema Entity Audit Template

Auditing existing schema.org structured data implementations across multiple entity types without standardized evaluation criteria leads to inconsistent quality assessments—this Google Sheets audit template provides a systematic framework for evaluating structured data quality across 7 entity categories (Organization, Leadership/Person, Product/Service, Content/Article, Location, Event, Concept) using a 5-point scoring system that grades implementations from Excellent (complete properties, entity relationships, zero validation errors) to Poor/Broken (missing required properties, critical errors, non-functional markup). Created by Beatrice Gamba for MLforSEO, this audit tool enables technical SEO teams to assess current schema deployment quality, identify gaps requiring immediate attention versus incremental improvements, and prioritize remediation efforts based on severity—providing consistent evaluation criteria through detailed scoring rubrics with concrete examples showing what differentiates a score-5 Organization schema (founder relationships, multiple locations, awards) from score-3 adequate implementation (required properties only, no relationships) or score-1 broken markup (missing required name property, validation errors).
The template implements a three-column assessment structure: Entity Type lists the categories to audit, Present (Y/N) indicates whether markup exists, and Quality Score (1-5) rates implementation completeness using the defined framework. The scoring system progresses from 5-Excellent (all required AND recommended properties, proper @id references, entity relationships, rich details, zero validation errors) through 4-Good (required properties plus most recommended, minor warnings, basic connections), 3-Adequate (required only, missing recommended, validation warnings, minimal relationships), 2-Minimal (bare properties, multiple errors, placeholder values, no relationships), to 1-Poor (critical errors, missing required fields, incorrect types) and 0/N/A-Not Present. Each score level includes entity-specific examples demonstrating the criteria.
Use this for:
‧ Structured data quality audits documenting current implementation status across entity types with consistent scoring criteria for remediation prioritization
‧ Migration validation comparing pre/post schema quality scores to demonstrate improvement from implementation projects
‧ Competitive benchmarking by auditing competitor schema implementations to identify quality gaps or opportunities
‧ Client reporting providing stakeholder-friendly quality scores rather than technical validation errors
This is perfect for technical SEO teams conducting schema audits, agencies evaluating client implementations, or enterprise SEO departments establishing structured data quality baselines—particularly valuable when prioritizing remediation efforts by severity, demonstrating schema implementation ROI through before/after quality scores, or establishing organization-wide structured data quality standards.