Detailed Report:

Discoverability

❌ No image or video sitemap found

What we saw

Neither an image nor a video sitemap was detected in the sitemap index or at standard URLs. This makes it harder to reliably surface your visual assets as part of the site’s footprint.

Why this matters for AI SEO

Generative systems often pull in brand and product understanding from a mix of text and media. When visual content is harder to discover at scale, AI may build a less complete picture of what your site offers.

Next step

Publish an image and/or video sitemap and make sure it’s discoverable from your main sitemap index.

Structured Data

❌ Resource/blog page markup couldn’t be verified

What we saw

The resource page file that was evaluated appears to be missing or empty, so we couldn’t confirm whether the blog/resource content includes structured signals. As a result, this part of the site couldn’t be assessed the same way as the homepage.

Why this matters for AI SEO

AI systems rely on consistent, page-level signals to understand what a piece of content is and how to categorize it. When those signals aren’t available (or can’t be confirmed), content is more likely to be treated as lower-confidence.

Next step

Make sure the resource/blog page loads and exposes the expected page content so it can be properly understood and classified.

❌ Blog/resource posts didn’t show a clear, non-generic author

What we saw

Because the evaluated resource page file was missing or empty, we couldn’t identify a specific author for the content. That means the page isn’t presenting a clear person or entity responsible for the information.

Why this matters for AI SEO

When AI is deciding what to quote or summarize, authorship is a big trust cue. If author identity isn’t clear, AI may be more cautious about using the content as a source.

Next step

Add a clear, non-generic author attribution on resource/blog content so the author can be recognized consistently.

❌ Author profiles lacked confirmable external identity links

What we saw

The evaluated resource page file was missing or empty, which prevented verification of any author identity links (like profile references) tied to the author. In practice, this means there isn’t a confirmed external footprint for content authors in the evaluated snapshot.

Why this matters for AI SEO

External identity references help AI connect the dots between a person, their expertise, and the content they publish. Without that connective tissue, authorship tends to carry less weight in generative answers.

Next step

Ensure author profiles include consistent external identity references that AI systems can use to confirm who the author is.

AI Readiness

❌ Sitemap didn’t include freshness details

What we saw

The sitemap was detected, but it did not include update/freshness fields for URLs in the evaluated output. That leaves AI and search systems with less clarity on what’s changed recently.

Why this matters for AI SEO

Generative engines tend to prefer sources they can treat as current and actively maintained. When freshness is unclear, systems may be slower to reflect updates or may lean on older information.

Next step

Add update/freshness information for sitemap URLs so recency is easier to interpret.

❌ No clear “About” or brand-context path from the homepage

What we saw

We weren’t able to find internal links on the homepage using common brand-context cues like “about,” “company,” or “team.” This makes it harder to quickly confirm who you are and what you stand for.

Why this matters for AI SEO

AI systems look for clear, consolidated brand context to avoid misrepresenting a company. If that context isn’t easy to find, the brand can be treated as lower-confidence in summaries and recommendations.

Next step

Make sure there’s an obvious, crawlable path from the homepage to a dedicated brand-context page.

❌ No Wikidata entity found for the brand

What we saw

No Wikidata item ID was found for the brand in the evaluated results. That limits how easily AI knowledge systems can reconcile your official identity.

Why this matters for AI SEO

Wikidata is a common reference point used to validate and disambiguate brands. Without it, AI engines may have a harder time confidently connecting your site to a single, verified entity.

Next step

Create or claim a Wikidata entity for the brand and connect it to your official web presence.

Performance

❌ Homepage main content appears very slowly

What we saw

The homepage’s primary content took a long time to fully appear in the measured snapshot (over 14 seconds). That delay can make the page feel heavy, especially on mobile.

Why this matters for AI SEO

If key content is slow to show up, it can reduce how reliably systems interpret and reuse what the page is actually about. Slow initial rendering also weakens the overall experience signals AI-adjacent systems often correlate with quality.

Next step

Reduce the time it takes for the homepage’s main content to display so the primary message is available quickly.

Reputation & Brand Trust

❌ No Wikidata entity found for the brand

What we saw

No matching Wikidata entity was found for the brand in this reputation snapshot. That leaves a gap in third-party identity confirmation.

Why this matters for AI SEO

Generative engines often cross-check brand identity using knowledge sources they trust. Without a solid entity reference, AI can be less certain about which “version” of the brand it should trust.

Next step

Establish a Wikidata entity that clearly represents the brand and aligns with your official site.

❌ Identity signals weren’t consistent on a verified address

What we saw

While the name and domain were consistent, a verified physical address was not found across the majority of evaluated responses. This creates a “missing piece” in the brand’s public identity footprint.

Why this matters for AI SEO

When AI can’t consistently confirm basic business identity details, it tends to hedge more in how it describes or recommends a brand. Clear identity consistency supports trust and reduces confusion.

Next step

Make sure your official business address is consistently available across the brand’s trusted public references.

❌ Negative customer assertions were surfaced

What we saw

Negative client assertions were identified in the data, including concerns about product authenticity and shipping delays. This kind of feedback can become part of the brand narrative AI systems pick up.

Why this matters for AI SEO

Generative results are strongly influenced by trust and sentiment. If negative themes are prominent, AI may reflect them directly or soften recommendations, even when other signals look strong.

Next step

Review the surfaced negative themes and ensure your public-facing brand story addresses the concerns clearly and consistently.

❌ Homepage didn’t link directly to major social profiles

What we saw

No direct links to major social media platforms were found in the homepage HTML. That makes it harder to confirm official profiles from the site itself.

Why this matters for AI SEO

AI systems look for consistent corroboration across official channels. When official profiles aren’t clearly connected from the website, it can reduce confidence in which social entities are truly brand-owned.

Next step

Add clear, direct links from the homepage to the brand’s official social profiles.

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 clear, non-generic author shown

What we saw

No visible author name was identified on the page, and no author information was found in the structured data provided. The result is content that reads as “unattributed,” even if it’s well-intentioned.

Why this matters for AI SEO

AI systems weigh who said something almost as much as what was said, especially for health-adjacent topics. Without clear authorship, the content can be treated as less trustworthy or less cite-worthy.

Next step

Add a specific author name to the article and make sure it’s consistently presented on the page.

❌ Sections were too short for reliable extraction

What we saw

The content was broken into sections, but the average section length was about 105 words, which is on the thin side for conveying a complete idea. This can make individual sections feel a bit “snackable,” but not always reusable.

Why this matters for AI SEO

Generative engines prefer chunks that fully answer a sub-question in one place. Short sections can force AI to stitch context across multiple areas, which increases the chance of misinterpretation.

Next step

Rewrite key sections so each one can stand alone as a complete answer with enough supporting context.

❌ No tables to summarize key information

What we saw

No HTML tables were found in the content. That means there aren’t any structured “at-a-glance” blocks for comparisons, definitions, or quick takeaways.

Why this matters for AI SEO

Tables are an easy win for AI readability because they express relationships clearly (like definitions, pros/cons, steps, or ingredient notes). Without them, AI has to infer structure from paragraphs alone.

Next step

Add at least one simple table where a summary, comparison, or definition list would help the reader.

❌ Subheadings were often generic

What we saw

Most subheadings weren’t descriptive, with examples like “Join the club” and “Shop by Collection.” That makes it harder to tell what a section is actually going to answer.

Why this matters for AI SEO

AI uses headings as signposts to map content into topics and subtopics. Generic headings reduce how confidently systems can label and extract the right parts of the page.

Next step

Update headings so they clearly reflect the specific question or topic each section addresses.

❌ Key answers didn’t show up early in sections

What we saw

Many sections opened with very short lines or lists rather than a clear introductory paragraph that frames the takeaway. As a result, the “what this section is about” signal is delayed.

Why this matters for AI SEO

Generative engines tend to extract the first clear, complete answer they see. If the takeaway is buried, the model may miss it or pull a weaker summary.

Next step

Start each major section with a short, plain-language summary that states the main point up front.

❌ Acronyms appeared without nearby definitions

What we saw

Several acronyms (ORMEs, EMF, DNA, USPS) appeared without quick definitions nearby. That can be confusing for both readers and automated summarizers.

Why this matters for AI SEO

When terminology isn’t defined, AI may guess the meaning based on broader web context, which isn’t always aligned with your intent. Clear definitions help models summarize more accurately and confidently.

Next step

Add short, on-the-spot definitions the first time each acronym appears.

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.