Overview:
On 06/25/26 eyespyinvestigations.com scored 65% — **Decent** – Overall, the site shows a solid baseline for AI visibility, but a few trust and content clarity gaps are keeping it from feeling fully “easy to cite.”
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - The site has a strong technical foundation for discovery, though we didn't find any specialized sitemaps for images or video.
- Structured Data: 58% - The homepage identity is well-defined through organization schema, but the absence of a resource page means we couldn't confirm if your blog content is properly optimized for authorship.
- AI Readiness: 67% - This section looks mostly solid thanks to the open crawler access and clean sitemaps, but the lack of a Wikidata record is a notable gap for brand recognition.
- Performance: 67% - Mobile performance generally landed outside the "poor" range, with particularly strong marks for responsiveness and layout stability.
- Reputation: 69% - The brand shows strong offsite recognition and press coverage, but conflicting address data and negative client assertions in the data are impacting the overall reputation score.
- LLM-Ready Content: 44% - The site is well-maintained and industry-connected, but the fragmented section layout and generic authorship create missed opportunities for AI-readability and trust.
The main takeaway at a glance
The big picture is that your baseline visibility signals are generally in place, but the site doesn’t consistently come across as easy for AI systems to confidently attribute and summarize. The gaps here are mostly about clarity and credibility signals—less about “something being wrong,” and more about missing context that helps models feel sure they’ve got the right story. Below, we’ll walk through the specific areas where that context wasn’t found, grouped by section so it’s easy to scan. None of these are unusual, and having them clearly called out makes the path forward feel a lot more manageable.
Detailed Report
Discoverability
❌ Image or video sitemap not found
What we saw
We didn’t see an image or video sitemap available, so media assets don’t have a dedicated discovery path.
Why this matters for AI SEO
When media isn’t clearly surfaced, it can be harder for search and AI systems to reliably find, understand, and reuse those assets in results and summaries.
Next step
Add a dedicated image and/or video sitemap so media content is easier to discover and attribute.
Structured Data
❌ Resource/blog structured data not found
What we saw
We weren’t able to find usable structured data on a resource/blog page, because the evaluated resource page appeared missing or empty.
Why this matters for AI SEO
Without clear article-level signals, AI systems have less context to understand what a piece of content is, what it’s about, and how it should be referenced.
Next step
Ensure the resource/blog page is accessible and includes clear article-level structured data.
❌ Clear author attribution not found on resource/blog content
What we saw
We couldn’t verify a clear, non-generic author on the evaluated resource/blog page because the page appeared missing or empty.
Why this matters for AI SEO
AI engines lean heavily on authorship to judge credibility and decide whether content reflects real, attributable expertise.
Next step
Add a specific, named author to resource/blog content so expertise is easier to confirm.
❌ Author profile links (sameAs) not found
What we saw
We didn’t find author identity links connected to the author on the evaluated resource/blog page, because the page appeared missing or empty.
Why this matters for AI SEO
When author identity isn’t linked to consistent external profiles, it’s harder for AI systems to connect the writer to a real-world footprint.
Next step
Add author identity links that point to the author’s official profiles so attribution is easier to validate.
AI Readiness
❌ No Wikidata entity found for the brand
What we saw
We didn’t see a linked Wikidata entity associated with the brand.
Why this matters for AI SEO
Wikidata is a common reference point for knowledge systems, and missing that anchor can make brand identity harder for AI to verify and connect across sources.
Next step
Create and connect a Wikidata entity for the brand so AI systems have a consistent identity reference.
Reputation
❌ Negative client assertions were affirmed
What we saw
We saw negative client feedback being repeated in a way that suggests at least one model treated it as credible, including allegations around service quality.
Why this matters for AI SEO
When negative claims become part of the “common narrative,” AI responses may reflect them, which can reduce trust and willingness to recommend or cite the brand.
Next step
Document and address the specific negative claims showing up in the brand narrative so trust signals are clearer.
❌ Brand identity signals are inconsistent
What we saw
There was a conflict in physical location signals, with different sources pointing to different headquarters locations.
Why this matters for AI SEO
Identity inconsistencies make it harder for AI systems to confidently unify brand information, which can lead to uncertainty or mixed answers.
Next step
Align brand identity details across major public sources so the brand footprint reads as consistent.
❌ No matching Wikidata entity for the brand
What we saw
We didn’t find a Wikidata entity that matches the brand.
Why this matters for AI SEO
Without a recognized knowledge-graph entity, AI systems have fewer authoritative anchors to confirm “who you are” across the web.
Next step
Establish a matching Wikidata entry that clearly represents the brand.
❌ Wikidata identity anchors are missing
What we saw
Because no Wikidata entry was found, there were no official identity anchors available there (like confirmed identifiers tied to the brand).
Why this matters for AI SEO
Identity anchors help AI systems distinguish brands with similar names and reduce confusion when summarizing or recommending providers.
Next step
Add official identity anchors via a Wikidata presence so brand identity is easier to validate.
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
❌ Generic author name used
What we saw
The content is attributed to “TPP Web Team,” which reads as a group label rather than a specific, named expert.
Why this matters for AI SEO
AI systems are more likely to trust and reuse content when they can tie it to a real person with clear expertise.
Next step
Update authorship to a specific, named investigator (or clear subject-matter owner) tied to the content.
❌ Content sections are too thin for strong context
What we saw
The page is split into sections that are often very short, which leaves key ideas feeling fragmented.
Why this matters for AI SEO
When context is spread across thin blocks, AI models have a harder time extracting complete, reliable answers without losing nuance.
Next step
Expand key sections so each one fully explains a single idea in a more self-contained way.
❌ No structured table found (bonus)
What we saw
We didn’t find any structured tables on the evaluated page.
Why this matters for AI SEO
Tables can make details easier for AI to parse and restate accurately, especially for comparisons, steps, or definitions.
Next step
Add a simple table where it naturally helps summarize key information on the page.
❌ Subheadings aren’t consistently descriptive
What we saw
Several subheadings are generic (for example, navigation-like labels), rather than clearly describing what the next section answers.
Why this matters for AI SEO
Clear subheadings act like signposts for AI systems, helping them quickly map what the page covers and where specific answers live.
Next step
Rewrite section headings so they clearly describe the question or topic each section addresses.
❌ Key answers don’t show up early in sections
What we saw
A lot of sections don’t start with a substantial, clarifying intro paragraph, so the “point” doesn’t land quickly.
Why this matters for AI SEO
AI models often prioritize content that states the main answer or takeaway early, which improves extraction and reduces misinterpretation.
Next step
Make sure each main section opens with a clear, plain-English summary of the key takeaway.
❌ Readability is reduced by unexplained acronyms
What we saw
The content uses several acronyms that aren’t explained in-line, which can make the writing harder to follow.
Why this matters for AI SEO
When terms aren’t defined, AI systems are more likely to lose accuracy or miss important context when summarizing the page.
Next step
Define acronyms the first time they appear so the content is easier to understand and restate.
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.
