Quick answer: An entity consistency audit compares the facts your WordPress site publishes about an organization, person, or product across visible pages, author profiles, structured data, and trusted external profiles. The goal is to choose a truthful source of record, correct contradictions, and make the same entity easy to identify everywhere. Consistency can reduce ambiguity, but it does not guarantee rankings, AI citations, or inclusion in an answer.
Key takeaways
- Audit one entity at a time: your organization first, then authors, products, or services.
- Compare visible copy with JSON-LD; schema should describe the page, not contradict or embellish it.
- Prioritize wrong names, URLs, authors, locations, and contact details before cosmetic wording differences.
- Keep evidence for each correction and measure crawl, indexing, search, and referred visits separately.
Prerequisites for an entity consistency audit
You need WordPress access, a list of important public pages, the organization’s approved facts, and permission to confirm author or business details. You should also be able to view page source or use a structured-data testing tool. Start with facts you can verify; do not infer credentials, founding dates, addresses, or ownership.
Google’s people-first guidance recommends clear sourcing and background about the author or site. Its Article documentation also recommends an author name plus a URL or sameAs value that identifies the author. Review the helpful-content guidance and Article structured-data guidance before changing author markup.
What should you compare?
| Entity | Facts to check | Common surfaces | High-risk conflict |
|---|---|---|---|
| Organization | Name, URL, logo, contact details, address | Home, About, Contact, footer, Organization JSON-LD | Different brand names or obsolete address |
| Author | Public name, bio URL, role, credentials | Byline, profile, Article JSON-LD, editorial page | Schema names a person not shown on the article |
| Product or service | Name, provider, availability, key terms | Landing page, pricing, policies, Product or Service markup | Visible terms disagree with structured data |
Google recommends useful Organization properties such as a name, real-world presence, URL, and logo. It says the Organization name and alternateName should match the names used for the site name. That makes an Organization markup review a practical comparison point, not a license to add unsupported facts.
How to run the audit step by step
1. Choose one entity and define the scope
Begin with the organization because its facts often appear sitewide. List the homepage, About page, Contact page, footer, author profiles, important commercial pages, and policy pages. Include only public canonical URLs. A focused scope prevents an audit from becoming an endless crawl.
2. Create a source-of-truth record
Make a sheet with columns for fact, approved value, evidence, owner, and last verified date. Evidence might be an official registration, an owner-approved brand guide, or the current contact system. Use your actual public brand name separately from a legal name when both are needed. Never convert a service area into a physical address.
3. Inventory visible facts
Record the exact wording on every scoped page. Check mobile menus and footers as well as main content. For authors, compare the visible byline with the profile name and biography. The E-E-A-T guide explains why transparent authorship helps users evaluate content, while a separate source audit covers evidence inside the article itself.
4. Extract the structured data
Inspect the rendered JSON-LD, not only a plugin’s settings screen. Record each Organization, Person, Article, Product, or Service node and note which plugin or theme generates it. Google advises including every visible article author in markup, using the appropriate Person or Organization type, and providing a valid author URL or sameAs identifier. The broader schema markup guide can help you inspect syntax without treating markup as a ranking switch.
5. Classify each mismatch
- Critical: the wrong entity, domain, author, or canonical organization name.
- Material: an obsolete address, phone number, role, logo, or service term.
- Contextual: a historical fact presented without its original date or context.
- Cosmetic: capitalization or punctuation that does not change identity.
Fix critical and material conflicts first. Do not standardize harmless wording at the expense of clarity.
6. Correct the authoritative source first
Update the page or profile that owns the fact, then the template, plugin, or schema generator that repeats it. Keep visible text and structured data aligned. If two plugins emit duplicate Organization nodes, find the controlling source instead of stacking a third node. Preserve truthful historical statements and add dates where context matters.
7. Validate and record the change
Recheck the live HTML, canonical URL, robots directives, and rendered JSON-LD. Confirm that names and URLs resolve, images are crawlable, and author links lead to real profiles. Record the affected URLs, before and after values, date, and evidence. Google’s AI search guidance says ordinary SEO foundations still apply and no special AI schema or llms.txt file is required.
Illustrative worked example
Imagine a fictional consultancy called Northstar SEO Lab. Its About page uses that name and says it began in 2021. The footer says “Northstar Digital,” Organization JSON-LD uses the old name and an obsolete office, and articles show “Benjamin Lee” while Article markup lists “Admin.” This is an example, not a test result.
| Finding | Priority | Repair |
|---|---|---|
| Organization name differs in visible copy and JSON-LD | Critical | Confirm the approved public name; update the generating source and site-name settings |
| Visible author and schema author differ | Critical | Use the truthful visible author in Article markup and link to the real profile |
| Obsolete office appears in schema | Material | Remove or replace it only after verifying the current address |
| Founding year differs in an old announcement | Contextual | Preserve the archive; clarify whether it refers to the company or rebrand |
The team would correct the two identity conflicts first, verify the address next, and document the historical wording rather than rewriting it blindly. Its next AI search content brief would reuse the approved entity record.
Troubleshooting common entity conflicts
- Two legitimate brand names: choose the primary public name and use
alternateNameonly for a genuine alternate name. - Pseudonym or brand byline: use the truthful public identity and a profile explaining it; never invent credentials.
- Duplicate schema: identify which theme or plugin owns each node before disabling or editing anything.
- Crawler access but no citation: access is only eligibility. OpenAI documents OAI-SearchBot for search and GPTBot for potential training as independent controls; neither guarantees selection. See the OpenAI crawler documentation.
Limitations and measurement
An entity consistency audit cannot prove that an AI system recognized, mentioned, or cited your brand. Measure technical eligibility, indexed pages, search performance, and business outcomes separately. In GA4, the AI Assistant channel covers identifiable visits from services such as ChatGPT, Gemini, Deepseek, Copilot, and Grok; Google AI Overviews and AI Mode are excluded. Those referred sessions are not a count of all mentions or citations. Use the current GA4 channel definitions and, where available, Google Search Console’s generative-AI reporting rather than guessing from query shapes.
Frequently Asked Questions
What is an entity consistency audit?
It is a comparison of verified facts about an organization, person, product, or service across visible pages, profiles, structured data, and relevant external profiles. The output is a prioritized list of contradictions to correct.
Which website entities should I audit first?
Start with the organization, then authors, important products, and core services. Prioritize entities that appear across many pages or influence trust, contact, or purchasing decisions.
Does Organization schema improve AI citations?
Organization schema can help machines understand declared facts, but Google does not promise rankings or AI citations because it is present. Use supported properties that match visible, verified content.
Should every author use Person schema?
Use Person for a real individual and Organization for an organizational author. The markup should match the visible byline, include all shown authors, and link to a page that identifies each author when practical.
How often should I repeat the audit?
Repeat it after a rebrand, migration, author change, address change, plugin replacement, or major template update. Otherwise, a focused quarterly review of high-value entities is a reasonable maintenance cadence.
Conclusion
A useful entity consistency audit is a fact-checking workflow, not an AI citation trick. Choose one entity, establish verified facts, compare visible pages with rendered markup, repair meaningful contradictions at their source, and document what changed. That gives users and search systems a clearer, more trustworthy account of who created the content and which organization, product, or service it represents.