Overview:
On 06/27/26 Www.anewresume.com scored 60% — **Fair** – Overall, the site is in a workable spot for AI visibility, but a few gaps in clarity and trust signals are holding it back.
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - The site has a rock-solid technical foundation for discovery, though it’s currently missing dedicated sitemaps for images and video.
- Structured Data: 58% - The homepage features a clean and valid schema implementation for the organization, but the absence of resource page data prevented us from confirming authorship or article-level markup.
- AI Readiness: 50% - The technical foundation for AI crawling is solid, but the site lacks clear brand context links and a Wikidata identity to establish authority.
- Performance: 50% - Mobile performance is generally solid with great responsiveness and stability, though the initial load time for the main content is currently dragging things down.
- Reputation: 69% - The brand has strong recognition and high-authority press mentions in Forbes, but negative client sentiment on review sites and a lack of structured data like Wikidata are the main bottlenecks.
- LLM-Ready Content: 48% - The site establishes strong credibility through identified experts and fresh content, but it would benefit from more descriptive subheadings and better-balanced section lengths to improve AI readability.
Where things look unclear today
The big picture is that a few core signals are coming through clearly, but some important context around identity, trust, and content clarity isn’t as easy for AI to confirm or reuse. None of this reads like something is “wrong” with the site—it’s more that certain details aren’t being reinforced in a way AI systems consistently pick up. The breakdown below walks through the specific areas where the evaluation couldn’t verify key signals or where the content structure makes extraction harder. Overall, these are the kinds of gaps that are common and straightforward to address once they’re clearly mapped.
Detailed Report
Discoverability
❌ Image or video sitemap not found
What we saw
We didn’t detect any dedicated discovery support for image or video content. For a site that uses visual elements, this leaves some of that content harder to surface consistently.
Why this matters for AI SEO
Generative engines often rely on clear, well-organized discovery signals to find and interpret non-text assets. When those signals aren’t present, visual content can be underrepresented in AI-driven results.
Next step
Add dedicated discovery support for your image and/or video content so those assets are easier for engines to find and understand.
Structured Data
❌ Resource/blog page structured data couldn’t be evaluated
What we saw
A resource/blog page file wasn’t available in the evaluation packet, so we couldn’t confirm what structured data is present on content listings or articles. That creates a blind spot around how your content is described.
Why this matters for AI SEO
When content pages don’t have clear, machine-readable context, AI systems have a harder time classifying what the page is and how it should be trusted or reused. That can reduce how confidently your articles show up in AI answers.
Next step
Make sure your resource/blog page and article templates include structured data that clearly describes the content and its key entities.
❌ Blog post author identity couldn’t be verified
What we saw
Because a resource/blog post page wasn’t available to review, we weren’t able to verify whether posts consistently show a clear, non-generic author identity in a way engines can interpret. This is less about whether an author exists and more about whether it’s being clearly signaled.
Why this matters for AI SEO
Authorship is one of the strongest ways to communicate expertise and accountability. If AI systems can’t confidently connect content to a real author entity, they may treat the content as less attributable.
Next step
Ensure blog posts consistently identify the author in a clear, structured way that can be understood as a specific person or entity.
❌ Author “sameAs” links couldn’t be verified
What we saw
We couldn’t confirm whether author information includes profile/identity links that help connect the author to the broader web. This was not verifiable due to the missing resource/blog post page data.
Why this matters for AI SEO
Generative engines lean on corroboration to reduce ambiguity about who an author is. Without consistent identity connections, it’s harder for AI to trust that the author entity is the same person across sources.
Next step
Add consistent author identity links on content pages so the author can be corroborated across the web.
AI Readiness
❌ No clear About/Team brand context path found
What we saw
From the homepage navigation and links available in the evaluated HTML, we didn’t find an internal path that clearly points to an About, Company, Team, or Leadership-style page. That makes it harder to quickly understand who is behind the business.
Why this matters for AI SEO
AI systems look for straightforward brand context to confirm legitimacy and interpret authority. When that context isn’t easy to locate, the brand story can become fragmented or less certain in AI-generated summaries.
Next step
Create and clearly surface a dedicated brand context page that explains who you are and what the business does.
❌ No Wikidata entity found for the brand
What we saw
No matching Wikidata item ID was identified for the brand in the provided dataset. That removes one common “known entity” reference point.
Why this matters for AI SEO
Knowledge bases can act as a cross-check for identity and legitimacy. Without a recognized entity record, AI systems may have less confidence when reconciling brand details across sources.
Next step
Establish a Wikidata entity for the brand so AI systems have a stable reference for identity.
Performance
❌ Main page content appears slow to load
What we saw
The primary content area of the homepage took longer than expected to fully appear during evaluation. This points to a noticeable loading delay for the main “first impression” content.
Why this matters for AI SEO
When core content is slow to show up, it can limit how efficiently engines and users reach the parts of the page that communicate meaning and value. That can reduce reliable extraction and summarization in some AI experiences.
Next step
Reduce the time it takes for the homepage’s main content to render so the primary message is available sooner.
Reputation
❌ Negative client feedback is being surfaced
What we saw
We saw explicit mentions of negative client feedback appearing in the offsite reputation signals reviewed. This creates a trust headwind, even when other recognition is strong.
Why this matters for AI SEO
Generative engines tend to incorporate reputation themes when summarizing or recommending brands. If negative feedback is prominent, it can show up in AI answers and influence how the brand is framed.
Next step
Review the surfaced negative feedback themes and ensure your public-facing brand narrative addresses trust concerns clearly and consistently.
❌ Brand identity details don’t show strong consensus
What we saw
A consistent physical address wasn’t identified across the majority of models used in the reputation snapshot. That makes the brand’s “official” identity footprint feel less pinned down.
Why this matters for AI SEO
When identity details vary or can’t be confirmed consistently, AI systems may be less confident about which brand profile is authoritative. That can dilute trust and reduce certainty in brand summaries.
Next step
Standardize and reinforce the brand’s core identity details across the web so engines see a consistent, confirmable footprint.
❌ No Wikidata entity found
What we saw
No matching Wikidata record was found for the brand in the dataset. This leaves one major public identity reference point missing.
Why this matters for AI SEO
Wikidata can help AI systems validate entities and reconcile brand attributes across sources. Without it, brand verification can rely more heavily on inconsistent third-party references.
Next step
Create and validate a Wikidata entity that represents the brand accurately.
❌ Wikidata identity anchors aren’t present
What we saw
Because no Wikidata entity was found, there were no official-site or identifier anchors available there either. That removes an easy “source of truth” connection.
Why this matters for AI SEO
Identity anchors help AI systems connect a brand name to the correct official presence. Without clear anchors, it’s easier for entity matching to get fuzzy.
Next step
Ensure the brand’s identity record includes clear, official reference anchors that point back to the right online properties.
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
❌ One section is too long to digest cleanly
What we saw
A single section (“SERVICES OFFERED INCLUDE:”) runs as one continuous block of roughly 800+ words. That makes it harder to scan and harder for AI systems to pull out discrete, reusable chunks.
Why this matters for AI SEO
Generative engines work best when information is packaged into clear, bounded units. Overly long blocks can lead to missed details or partial extraction when AI summarizes the page.
Next step
Break the oversized section into smaller, clearly labeled segments so each idea stands on its own.
❌ No table-based structure detected
What we saw
We didn’t detect any HTML tables used to structure key information. That means there’s no compact, standardized layout for details that could otherwise be easy to reference.
Why this matters for AI SEO
Structured layouts make it easier for AI to extract and restate specifics accurately. Without them, AI often has to infer relationships from prose, which can reduce precision.
Next step
Add at least one table where it naturally fits to present important details in a clean, scannable format.
❌ Subheadings are often too generic to anchor meaning
What we saw
Many subheadings are short and broad (for example, headings that read like navigation labels rather than descriptive topic markers). This makes it harder to understand what each section is actually about at a glance.
Why this matters for AI SEO
AI systems use headings as signposts to categorize and retrieve information. When headings are generic, the content underneath can be harder to classify and less likely to be pulled into relevant answers.
Next step
Rewrite key subheadings to be more descriptive so each section’s purpose is immediately clear.
❌ Sections don’t lead with clear, substantive answers
What we saw
Most sections start with very short intro text (often a brief question or single sentence). That means the page tends to delay the “main point” rather than stating it upfront.
Why this matters for AI SEO
Generative engines often prioritize early, direct statements when extracting answers. When openings are thin, AI may miss key context or summarize the section too generally.
Next step
Strengthen the opening of each major section so the core takeaway is clear right away.
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.
