Detailed Report:

Discoverability

❌ Image or video sitemap not found

What we saw

We found a standard XML sitemap, but we didn’t find a dedicated sitemap for images or videos. That means your visual assets aren’t being presented as clearly as they could be.

Why this matters for AI SEO

When AI systems look for supporting visuals, clear organization helps them discover and connect media to the right pages and topics. Without that extra layer of clarity, your visual content can be easier to overlook.

Next step

Add a dedicated image and/or video sitemap so your visual content is easier to discover and associate with the right pages.

Structured Data

❌ Markup not confirmed on a blog/resource page

What we saw

We weren’t able to review structured information for a blog or resource page because that page content wasn’t available in the audit inputs. As a result, we couldn’t confirm how well a typical article is described.

Why this matters for AI SEO

AI systems rely on consistent, page-level context to accurately interpret and summarize content across your site. If resource pages aren’t clearly described, it can reduce how confidently they’re understood and reused.

Next step

Make sure a representative blog/resource URL is available for review and includes clear structured information describing the page.

❌ Author not confirmed on a blog/resource page

What we saw

Because the blog/resource page content wasn’t available, we couldn’t confirm that an article includes a clear, non-generic author attribution. This left authorship signals on content pages unverified.

Why this matters for AI SEO

Clear authorship helps AI systems assess credibility and attribute information appropriately. When authorship is missing or unclear, content can feel less trustworthy or harder to cite.

Next step

Ensure blog/resource pages clearly name a real author (not a generic label) in a way AI systems can pick up reliably.

❌ Author profile links not confirmed

What we saw

We couldn’t confirm any author profile links tied to the author on a blog/resource page because that page content wasn’t available. This means we couldn’t verify if author identity is connected to credible external profiles.

Why this matters for AI SEO

When AI systems can connect an author to consistent external identity references, it strengthens trust and reduces ambiguity. Without that connection, it’s harder to validate who created the content.

Next step

Add clear author profile links on blog/resource pages so author identity is easier to verify across the web.

AI Readiness

❌ No Wikidata entity found for the brand

What we saw

We didn’t find a Wikidata entity associated with the brand. So there wasn’t a clear, canonical knowledge-base reference to tie the brand identity together.

Why this matters for AI SEO

AI systems often look for consistent, authoritative identity references when forming an understanding of a brand. When that reference isn’t available, brand interpretation can be less stable across different contexts.

Next step

Create or claim a Wikidata entity for the brand so AI systems have a stronger, consistent identity reference.

Reputation

❌ Negative client sentiment not confirmable

What we saw

We weren’t able to confirm clear signals about negative client assertions in the available reputation inputs. That means this aspect of brand sentiment couldn’t be validated either way.

Why this matters for AI SEO

When AI systems synthesize brand reputation, they depend on clear third-party sentiment signals. If those signals can’t be confirmed, the brand picture can be incomplete or inconsistent.

Next step

Gather and surface verifiable third-party sentiment signals so brand reputation is easier to evaluate.

❌ Negative employee sentiment not confirmable

What we saw

We weren’t able to confirm clear signals about negative employee assertions in the available reputation inputs. This left workforce sentiment signals unverified.

Why this matters for AI SEO

AI systems may reference employee sentiment as part of overall brand trust and legitimacy. Missing or unclear signals can make reputation summaries less grounded.

Next step

Make sure there are clear, verifiable sources that reflect employee sentiment in a way AI systems can reference.

❌ Broad brand recognition signals not confirmed

What we saw

We weren’t able to confirm signals indicating the brand is consistently recognized across multiple AI-facing sources. That left overall “known entity” strength unclear.

Why this matters for AI SEO

When a brand is consistently recognized, AI systems can summarize it with more confidence and fewer mismatches. If recognition signals are thin or unconfirmed, the brand may be treated as less established.

Next step

Strengthen and validate consistent third-party references to the brand across reputable sources.

❌ Brand identity consistency not confirmed

What we saw

We weren’t able to confirm consistent, reconciled identity details (like name, domain, and address) across the available reputation signals. This creates room for ambiguity in how the brand is understood.

Why this matters for AI SEO

AI systems are sensitive to inconsistencies when they’re trying to match “who you are” across sources. If identity signals don’t line up clearly, it can reduce trust and increase confusion in summaries.

Next step

Ensure the brand’s core identity details are consistently represented across major third-party references.

❌ Wikidata match not confirmed

What we saw

We did not find a matching Wikidata entity for the brand in the reputation review. This limited our ability to confirm a canonical external identity.

Why this matters for AI SEO

Wikidata can serve as a strong anchor for disambiguation and brand verification. Without a match, AI systems have fewer dependable ways to connect the brand to a single, stable identity.

Next step

Create and validate a Wikidata entry that clearly matches the brand.

❌ Official identity anchors not confirmed

What we saw

We weren’t able to confirm official identity anchors tied to a Wikidata presence (like an official website reference). That means a key verification bridge wasn’t present.

Why this matters for AI SEO

Official anchors help AI systems trust that the identity reference truly represents your brand. Without them, it’s harder to separate your brand from similarly named entities.

Next step

Make sure any canonical brand identity references include official anchors that clearly point back to the brand.

❌ Third-party reviews not confirmed

What we saw

We weren’t able to confirm the presence of third-party reviews or customer feedback signals in the reputation results. This leaves customer validation unclear.

Why this matters for AI SEO

Reviews and feedback give AI systems concrete, quote-able evidence of real-world experience with your brand. When these signals are missing or unconfirmed, reputation summaries can end up thin.

Next step

Establish and surface third-party customer feedback signals that can be consistently referenced.

❌ Review sources not confirmed

What we saw

We weren’t able to confirm concrete, consistent sources for reviews in the available reputation signals. That made it difficult to validate where customer feedback lives.

Why this matters for AI SEO

AI systems tend to trust reputation signals more when they come from clear, reputable sources. If the sources aren’t clear, the credibility impact is limited.

Next step

Make sure customer feedback is associated with recognizable, consistent review sources.

❌ Consensus on major social profiles not confirmed

What we saw

While we did see a major social profile linked from the homepage, we couldn’t confirm broader consensus signals that validate the brand’s primary social profiles across sources. This can leave room for mismatches or incomplete identity linking.

Why this matters for AI SEO

When AI systems can confidently connect your brand to its official profiles, it reduces ambiguity and improves trust. If that consensus isn’t present, AI may be less certain about which profiles are official.

Next step

Strengthen consistent third-party references that clearly point to the brand’s official social profiles.

❌ Independent press or coverage not confirmed

What we saw

We weren’t able to confirm independent, offsite press or coverage signals for the brand in the reputation results. This left third-party validation through editorial mentions unclear.

Why this matters for AI SEO

Independent coverage can help AI systems corroborate that a brand is established and noteworthy beyond its own website. Without those signals, the brand story can be harder to substantiate.

Next step

Build and document independent third-party coverage references that AI systems can point to.

❌ Owned press or press releases not confirmed

What we saw

We weren’t able to confirm onsite press or press-release style content in the reputation results. That means there wasn’t a clear owned-media footprint to support brand claims.

Why this matters for AI SEO

Owned press can act as a consistent reference point for announcements, milestones, and credibility details. When it’s missing or unclear, AI systems have fewer stable sources to cite.

Next step

Create a clear owned press area that AI systems can reference for brand announcements and milestones.

LLM-Ready Content (Blog Analysis)

Heads up: this section looks at one article as a snapshot, so it’s a little more interpretive than the rest of the report and may shift slightly from run to run. Have questions? Just shoot us an email at hello@v9digital.com

❌ No table-based formatting found

What we saw

We didn’t find any table-based formatting on the page. That means key information isn’t presented in a compact, scan-friendly structure.

Why this matters for AI SEO

AI systems often extract and reuse structured information more cleanly when it’s presented in clearly organized blocks. Without that structure, important details can be harder to pull out consistently.

Next step

Add at least one simple table where it naturally fits to present key information in a clear, structured way.

❌ Subheadings are often too generic

What we saw

Many subheadings are short, generic labels that don’t stand well on their own. This makes sections feel less self-explanatory when skimmed out of context.

Why this matters for AI SEO

AI systems frequently use headings to understand what each section is “about” before they interpret the paragraphs underneath. Generic headings can reduce clarity and make summaries less precise.

Next step

Rewrite the more generic subheadings so they describe the specific question or takeaway each section answers.

Does Anything Seem Off?

Thanks for taking our free GEO Grader for a spin. When we started this journey, the tool had a fairly long processing time to check everything we wanted both onsite and offsite, so we made a few adjustments on the backend to speed things up. As a result, there are times when the grader may not get everything 100% right. If something feels off, we recommend running the tool a second time to confirm the results. From there, you’re always welcome to reach out to us to schedule a GEO consultation, or to have your SEO provider validate the findings with a more detailed crawl and manual review.