Overview:
On 10/18/26 funwithcrayons.com/ scored 56% — **Fair** – Overall, the site has some strong visibility fundamentals, but a few content and trust gaps are keeping it from feeling fully established in AI results.
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - The site's discoverability is quite strong overall, though the absence of image or video sitemaps is a missed opportunity for this visual-heavy brand.
- Structured Data: 58% - The homepage features solid organization schema, but the lack of data for resource pages prevented us from verifying author-level details or article markup.
- AI Readiness: 67% - Overall, this section looks mostly solid, but we weren't able to find a Wikidata entry to help AI models verify the brand's identity.
- Performance: 50% - Mobile performance mostly landed outside the 'poor' range for stability and responsiveness, but the slow homepage load time is a clear bottleneck.
- Reputation: 65% - The site is well-recognized by AI models and has a strong social media presence, but the lack of third-party reviews and a Wikidata entry are clear gaps in its reputation.
- LLM-Ready Content: 20% - This page functions primarily as a shop landing page, so it’s missing the deep informational structure and specific authorship that AI systems use to verify expertise.
The main takeaway at a glance
The big picture is that the site is generally easy to find and access, but it doesn’t yet read as deeply explained or independently validated in the places AI systems tend to lean on. The gaps here are mostly about clarity and confidence signals, not anything “broken.” Next, we’ll walk through the specific areas that came up in Discoverability, Structured Data, AI Readiness, Performance, Reputation, and LLM-Ready Content. Once you see them laid out, it should feel pretty straightforward to prioritize what matters most.
Detailed Report
Discoverability
❌ Image or video sitemap not found
What we saw
We didn’t detect an image sitemap or video sitemap in the provided site data. For a site that’s heavily visual, that’s a noticeable missing signal.
Why this matters for AI SEO
Generative engines rely on clear, consistent signals to understand and surface visual assets at scale. When those signals are missing, image- and video-heavy pages can be harder to interpret and reuse confidently.
Next step
Add a dedicated image and/or video sitemap so your visual content is easier for crawlers to discover and catalog.
Structured Data
❌ Structured data on the resource / blog page couldn’t be evaluated
What we saw
A resource or blog page file wasn’t included in the provided inputs, so we weren’t able to check whether that page includes structured data. That leaves a blind spot around how deeper content is described.
Why this matters for AI SEO
AI systems tend to trust and reuse content more easily when supporting context is clearly defined across key content pages, not just the homepage. If deeper pages are missing those signals (or can’t be verified), it can limit how confidently the content is understood.
Next step
Make sure your main resource/blog pages are available to evaluate and include clear, consistent structured data similar to what’s present on the homepage.
❌ Resource / blog post author couldn’t be verified
What we saw
Because the resource/blog page wasn’t provided, we couldn’t confirm whether a specific, non-generic author is shown for that content. As a result, authorship signals for informational pages are unclear in this audit.
Why this matters for AI SEO
When authorship isn’t clearly established, AI summaries and citations have less to anchor to, which can reduce trust and attribution. Clear authorship also helps differentiate editorial content from general brand messaging.
Next step
Ensure each resource/blog post clearly identifies a real author (not just the organization) in a consistent, easy-to-understand way.
❌ Author profile identity links couldn’t be confirmed
What we saw
Since the resource/blog page wasn’t included, we couldn’t confirm whether the author information includes identity links that connect the author to recognized profiles. That makes the author’s footprint harder to validate.
Why this matters for AI SEO
Generative engines look for consistent identity references to evaluate credibility and reduce ambiguity. Without those connections, it’s harder for AI systems to confidently understand who created the content.
Next step
Where you list an author, include clear identity references that consistently point to the same real-world profile(s).
AI Readiness
❌ Wikidata entity not found for the brand
What we saw
We didn’t find a Wikidata entry tied to the brand in the provided results. That means there isn’t a clear public entity reference acting as a consistent identity anchor.
Why this matters for AI SEO
AI systems often use established entity references to connect brand details across sources and reduce confusion around identity. When that anchor is missing, it can be harder to consistently recognize and describe the brand.
Next step
Create and confirm a Wikidata entity for the brand so AI systems have a reliable reference point.
Performance
❌ Homepage main content appears slowly on mobile
What we saw
The homepage’s main content took a long time to show up on mobile, with the key content appearing around 14 seconds into the load. This aligns with the report’s overall pattern: the page is stable once it renders, but it takes too long to get there.
Why this matters for AI SEO
Slow-loading pages can reduce how efficiently content gets accessed and evaluated, especially on mobile where many crawls and user sessions happen. When key content appears late, it also increases the chance that the page’s meaning is captured incompletely.
Next step
Prioritize bringing the main homepage content into view faster on mobile so the page’s core context is available earlier.
Reputation
❌ Brand identity details aren’t fully consistent across key anchors
What we saw
We couldn’t confirm a consistent physical address in the brand identity signals surfaced by this evaluation. That leaves an important part of the brand’s “who/where” story incomplete.
Why this matters for AI SEO
Generative engines are more confident when a brand’s core identity details are consistent and easy to verify across sources. Missing or incomplete identity anchors can make it harder to treat the brand as established.
Next step
Add a clear, consistent physical address wherever your core brand identity is presented publicly.
❌ No matching Wikidata entity was identified
What we saw
The evaluation didn’t surface a Wikidata entry that clearly matches the brand. This overlaps with the AI readiness finding and reinforces that the brand’s entity footprint is thin.
Why this matters for AI SEO
Without a recognized entity reference, AI systems have fewer trusted ways to connect brand mentions across the web. That can reduce consistency in how the brand is described or cited.
Next step
Establish a Wikidata entity that clearly maps to the brand name and official site.
❌ Wikidata identity anchors weren’t present
What we saw
Because no matching Wikidata entity was found, there weren’t official identity anchors confirmed there (like an official website reference or other identifiers). In this snapshot, that leaves the brand without those third-party anchors.
Why this matters for AI SEO
When identity anchors are present and consistent, AI systems can reconcile brand details with less ambiguity. Missing anchors can make it harder to confirm that references across sources point to the same entity.
Next step
Make sure the brand’s entity references include clear official anchors that connect back to the correct web presence.
❌ Third-party customer reviews weren’t found
What we saw
We didn’t see third-party reviews or customer feedback sources tied to the brand in the provided results. That’s one of the bigger missing external trust signals in this report.
Why this matters for AI SEO
AI systems tend to place more confidence in brands that have independent validation beyond their own site and social presence. Reviews and feedback add real-world credibility signals that can influence how a brand is summarized.
Next step
Build a visible footprint of third-party customer feedback on reputable review platforms relevant to your audience.
❌ Concrete review sources weren’t identified
What we saw
No specific, attributable review sources were identified in the results, which goes hand-in-hand with the lack of third-party reviews overall. In practice, there’s nothing for AI systems to point to as a “source of customer sentiment.”
Why this matters for AI SEO
Generative engines prefer concrete sources they can reference when forming opinions about trust and user satisfaction. If sources aren’t present or are too vague, those trust signals often don’t get reflected in AI-generated overviews.
Next step
Ensure customer feedback is published on clearly attributable third-party sources that are easy to recognize and reference.
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 specific author was identified
What we saw
The page didn’t identify an individual author in a visible way, and it only referenced the organization name. That makes it hard to tell who is responsible for the content.
Why this matters for AI SEO
AI systems tend to trust content more when it’s clearly attributable to a real person with a consistent identity. Without that, the content can read as less verifiable or less editorial in nature.
Next step
Add a clear, non-generic author attribution for the page.
❌ Content hasn’t been updated recently
What we saw
The last modified date detected was July 18, 2025, which is more than a year old relative to today’s date. In this snapshot, the page reads as potentially dated.
Why this matters for AI SEO
Generative engines often weigh freshness when deciding what to reuse for current answers. When updates look old, the content may be less likely to be treated as a “best current source.”
Next step
Refresh the page so it reflects a more current update window.
❌ No non-social external references were found
What we saw
All detected outbound links pointed to social platforms, and there weren’t any external informational references. That means the page isn’t connected to any supporting sources in this snapshot.
Why this matters for AI SEO
AI models are more confident when content is grounded in a broader web context with recognizable references. Without that, the page can feel more self-contained and less supported.
Next step
Include at least one relevant, non-social external reference link that adds context for readers.
❌ Content isn’t chunked into readable, informational sections
What we saw
The page was mostly made up of product carousels and call-to-action blocks, without substantial paragraph-based sections. As a result, there isn’t much structured narrative for an AI system to summarize.
Why this matters for AI SEO
Generative engines do best when a page clearly explains the topic in digestible sections. When content is mostly UI elements and short blurbs, the page can be harder to interpret and reuse.
Next step
Add a few clearly separated sections with enough descriptive text to explain the topic beyond the product grid.
❌ No HTML table was found
What we saw
We didn’t find a table on the page. That means there isn’t a structured place where key info can be presented in a scannable way.
Why this matters for AI SEO
Tables can make important details easier for AI systems to extract accurately, especially when users are looking for quick comparisons or specifics. Without structured formatting, key details can be easier to miss.
Next step
Add a simple table where it naturally fits to summarize key details a reader might want to scan.
❌ Subheadings are too generic to carry meaning
What we saw
Subheadings were mostly short labels or generic sections (for example, category-style headings) rather than descriptive topic statements. That limits how clearly the page signals what each section is actually about.
Why this matters for AI SEO
Clear subheadings help AI systems map the structure of a page and pull the right parts for summaries. When headings don’t describe the content, the page becomes harder to “chunk” correctly.
Next step
Rewrite subheadings so they describe the actual questions, themes, or takeaways in each section.
❌ Key answers don’t show up early on the page
What we saw
The page didn’t use standard paragraph structures early on, and the existing text blocks were too short to communicate clear answers. In practice, the page leads with UI elements rather than explanations.
Why this matters for AI SEO
AI systems often look near the top of a page for the clearest summary of what it’s about. If the “why/what/how” isn’t stated early, it’s easier for the content to be underused or misunderstood.
Next step
Add a short, clear opening section that quickly explains the page’s main value and key points.
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.
