Overview:
On 07/03/26 ellis-comms.com/ scored 58% — **Fair** – Overall, the site has a solid base for being found, but a few credibility and content clarity gaps make it harder for AI systems to confidently describe the brand.
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - Overall, the site is in great shape for discovery with clean metadata and sitemaps, though we didn't see any specialized sitemaps for images or video.
- Structured Data: 33% - The site has a basic technical foundation for schema, but it's missing the critical organization and author-level data that search engines use to verify expertise and trust.
- AI Readiness: 67% - The site has a solid technical foundation with a clean robots.txt and sitemap, though it’s currently missing a Wikidata entry to help search engines verify its brand identity.
- Performance: 50% - Mobile performance generally landed in a decent range for responsiveness and layout stability, but the initial loading speed for main content is significantly delayed.
- Reputation: 81% - The brand shows strong offsite signals through press and social media, though inconsistent address data across sources and a lack of Wikidata presence are current bottlenecks.
- LLM-Ready Content: 24% - The resource lacks individual authorship and external citations, though it maintains a cohesive professional tone and includes clear update dates.
The main takeaway at a glance
The big picture is that the site has a workable foundation for AI visibility, but a few key signals don’t consistently reinforce who the brand is and why its content should be trusted. Most of the gaps aren’t “errors” so much as missing clarity around identity, attribution, and how easily content can be reused in AI answers. Below, we’ll walk through the specific areas where the review flagged missing or unclear signals, organized by section. None of this is unusual, and it’s the kind of cleanup that tends to be very straightforward once it’s clearly mapped.
Detailed Report
Discoverability
❌ Image or video sitemap missing
What we saw
We weren’t able to find an image sitemap or a video sitemap for the site. That means visual assets may be harder to reliably surface through standard discovery paths.
Why this matters for AI SEO
When AI-driven search experiences pull in rich results, they often depend on consistent discovery of core media assets. If those assets are harder to find, they’re less likely to be used confidently in AI summaries and results.
Next step
Add and publish a dedicated image and/or video sitemap so visual assets are easier to discover.
Structured Data
❌ Organization identity not defined on the homepage
What we saw
We didn’t see Organization- or LocalBusiness-type structured data on the homepage. As a result, the site’s primary entity isn’t being explicitly introduced in a way machines can consistently interpret.
Why this matters for AI SEO
AI systems lean on clear entity definitions to connect your site to the “real world” brand they’re trying to describe. When that entity signal is missing, it can create uncertainty about who the site represents.
Next step
Add an Organization-style structured data definition on the homepage so the brand is clearly identified.
❌ Resource/blog structured data couldn’t be evaluated
What we saw
A resource or blog page wasn’t provided for review, so we couldn’t confirm whether structured data is present on that type of page. This leaves a gap in what we can validate about how content pages are described.
Why this matters for AI SEO
Content pages are often what AI engines quote, summarize, or use to answer questions. If those pages aren’t clearly described, it can reduce confidence in what the content is and how it should be attributed.
Next step
Provide a representative resource/blog URL and ensure that page includes clear, content-appropriate structured data.
❌ Author clarity couldn’t be confirmed on content pages
What we saw
Because a resource or blog page wasn’t provided, we couldn’t verify whether posts have a clear, non-generic author. That makes it harder to confirm whether content is tied to a real person.
Why this matters for AI SEO
AI systems tend to trust and reuse content more readily when authorship is specific and consistent. If authorship isn’t clear, it weakens the signal of expertise and accountability.
Next step
Make sure posts use a specific author identity (not a generic label) and supply a blog URL for validation.
❌ Author identity links couldn’t be confirmed
What we saw
We couldn’t evaluate whether author profiles include identity links (like consistent profile references) because a resource/blog page wasn’t provided. This leaves the author’s broader identity less verifiable.
Why this matters for AI SEO
When author identity can be corroborated across the web, AI systems have an easier time treating that author as a trustworthy source. Without those anchors, attribution can be weaker or less consistent.
Next step
Ensure author profiles include consistent identity links and share a sample blog post URL for review.
AI Readiness
❌ No Wikidata entity found for the brand
What we saw
We didn’t detect a Wikidata Item ID for the brand. That means there isn’t a strong, standardized reference point we can tie back to for identity verification.
Why this matters for AI SEO
Many AI systems use widely recognized entity databases to confirm names, relationships, and key brand facts. When that entity reference isn’t available, the system has fewer “hard anchors” to rely on.
Next step
Create and/or connect the brand to a Wikidata entity so the identity is easier to verify.
Performance
❌ Main content is very slow to appear on mobile
What we saw
The primary page content took an unusually long time to fully appear on mobile (over 36 seconds for the largest visible element). This suggests the initial load experience is significantly delayed.
Why this matters for AI SEO
If content is slow to load, crawlers and AI-driven systems may capture an incomplete view of the page or deprioritize it compared to faster, clearer sources. Over time, that can affect how reliably your pages are understood and surfaced.
Next step
Reduce the time it takes for the main page content to appear, especially on mobile.
Reputation
❌ Conflicting brand address information across sources
What we saw
We found inconsistent location details across different platforms, with the address appearing as both London (UK) and West Hollywood (CA). That inconsistency prevented a clean, unified identity match.
Why this matters for AI SEO
AI systems look for consistent, repeatable brand facts to decide what’s “true” about an entity. When key identity details conflict, it can create hesitation in how confidently the brand is described or referenced.
Next step
Standardize the brand’s official address details across major third-party profiles and listings.
❌ No Wikidata presence to confirm brand identity
What we saw
No Wikidata entry was found for this specific brand entity. As a result, there isn’t a single authoritative entity record to corroborate core business facts.
Why this matters for AI SEO
Wikidata is a common reference point used to validate entities in knowledge-style systems. Without it, identity confirmation relies more heavily on scattered mentions, which can be less deterministic.
Next step
Establish a Wikidata entity for the brand so key identity details can be verified.
❌ Missing verifiable identity anchors tied to a knowledge entity
What we saw
Because no Wikidata entry exists, we couldn’t confirm “identity anchors” that typically help lock in official details. This keeps the brand’s reference footprint less standardized than it could be.
Why this matters for AI SEO
AI visibility improves when brand facts can be traced back to stable, widely recognized entity references. When those anchors aren’t available, systems may be more cautious about firm details.
Next step
Add a Wikidata entity and align the brand’s key identifiers to it for consistent verification.
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
❌ Author is generic rather than a real person
What we saw
The post lists the author as “admin,” which reads like a placeholder instead of a specific individual. That makes it hard to tell who’s actually responsible for the content.
Why this matters for AI SEO
AI systems tend to place more trust in content that has clear, consistent authorship. Generic authorship can reduce perceived expertise and make attribution less reliable.
Next step
Update the post to show a specific author with a real name and profile.
❌ Content freshness is outside the last-year window
What we saw
The last update date shown (2025-03-04) is more than a year old relative to today’s date. That makes the page look less current at a glance.
Why this matters for AI SEO
For many topics, AI systems prefer sources that appear current and maintained. Older updates can make the content less likely to be treated as the best available reference.
Next step
Refresh the article and update the on-page “last updated” signal to reflect the most recent revision.
❌ No supporting outbound references
What we saw
We didn’t find links to independent third-party sources; outbound links were limited to internal pages or social profiles. That makes the article feel less grounded in external validation.
Why this matters for AI SEO
AI systems often look for corroboration and sourceability when summarizing or citing information. Without references, the content can be harder to trust and reuse.
Next step
Add a small set of relevant third-party references that support key claims in the article.
❌ Sections are too short and fragmentary
What we saw
While the post uses subheadings, the sections are very brief (around ~41 words on average). That creates a choppy read and limits how much meaning sits in each chunk.
Why this matters for AI SEO
LLMs extract answers more reliably when each section contains a complete thought with enough context to stand on its own. Fragmented sections can make it harder to pull clean, quotable passages.
Next step
Expand each section so it contains a fuller explanation rather than a quick snippet.
❌ Key answers don’t show up early in sections
What we saw
The early paragraphs under sections didn’t meet the minimum length needed to clearly deliver an “answer first” summary. That makes the page feel like it takes longer to get to the point.
Why this matters for AI SEO
AI systems often prioritize content that states the takeaway quickly and clearly. When the core answer is delayed or too thin, the page is harder to interpret and reuse in generated responses.
Next step
Rewrite section openers so each one starts with a clear, direct takeaway before adding detail.
❌ No table included (bonus)
What we saw
No table was detected in the content. This means the article misses a simple structured format that can make comparisons and definitions easier to parse.
Why this matters for AI SEO
Well-structured formatting can help AI systems extract facts, groupings, and quick summaries more cleanly. When everything is only in paragraph form, it can be harder to pull out crisp, structured answers.
Next step
Add a small table where it naturally fits (e.g., a comparison, checklist, or glossary-style summary).
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.
