Overview:
On 01/22/26 centricsquared.com scored 47% — **Below Average** – Overall, the site has some solid fundamentals, but a few missing credibility and content signals are holding back how clearly AI systems can understand and reference it.
Executive summary
Score Breakdown (High Level)
- Discoverability: 92% - This section looks solid overall, with all core homepage and indexing signals present except for a dedicated image or video sitemap.
- Structured Data: 58% - The homepage nails organization schema and markup, but the resource/blog page is missing both schema and a clear author.
- AI Readiness: 67% - Most of the basics are covered—including a clean robots.txt, a proper XML sitemap with lastmod data, and strong internal brand context—but we didn’t see a Wikidata entity for Centric Squared.
- Performance: 50% - Most homepage mobile performance metrics were in the clear, but the overall Lighthouse score was below the recommended threshold.
- Reputation: 50% - We saw gaps around employee sentiment, offsite recognition, and Wikidata presence, but the site does feature concrete reviews, social links, and independent press coverage.
- LLM-Ready Content: 0% - We didn’t see any of the expected foundational elements like schema, author, date, or structured subheadings on the page.
The main takeaway before the details
The big picture is that the site has some strong baseline signals in place, but the resource/blog content and offsite brand context aren’t coming through clearly enough in a few key spots. That’s less about “something being wrong” and more about missing clarity cues that help AI systems confidently interpret, attribute, and summarize what you publish. Next, you’ll see a straightforward breakdown of the specific areas that didn’t show up in the evaluation and how each one impacts AI visibility. None of this is unusual—it’s a common set of gaps, and it’s very addressable once it’s clearly mapped out.
Detailed Report
❌ No image or video sitemap was found
What we saw
We found a standard sitemap, but we weren’t able to find a dedicated image sitemap or video sitemap. That means media content may not be as fully surfaced as it could be.
Why this matters for AI SEO
Generative engines often rely on clear discovery paths to understand and reuse rich media content. When media isn’t as easy to find, it can be less likely to show up in AI-driven results.
Next step
Add a dedicated sitemap for images and/or videos so media content is easier for crawlers to discover.
❌ No schema markup was detected on the resource/blog page
What we saw
On the resource/blog page, we didn’t see structured markup included in the page HTML. As a result, key page details aren’t being clearly signposted there.
Why this matters for AI SEO
When a page clearly labels what it is, who it’s from, and what it’s about, AI systems can interpret it with more confidence. Missing these cues can make the content harder to classify and summarize accurately.
Next step
Add appropriate structured markup to the resource/blog page so its purpose and key attributes are clearer.
❌ The resource/blog post did not show a clear, non-generic author
What we saw
We weren’t able to identify an author on the resource/blog page. This makes it unclear who is responsible for the content.
Why this matters for AI SEO
Authorship is a helpful trust cue for AI systems when interpreting and citing informational content. When author information isn’t present, the content can feel less attributable.
Next step
Ensure each resource/blog post clearly names an author in a consistent, visible way.
❌ Author structured data with identity links wasn’t found
What we saw
Because author markup wasn’t present on the resource/blog page, we also didn’t see author identity links connected to that author. This leaves the author’s identity less verifiable across the web.
Why this matters for AI SEO
AI systems are more likely to trust and connect the dots when an author is consistently tied to known profiles. Without those connections, attribution can be weaker.
Next step
Include author markup that ties the author to their official profiles in a consistent way.
❌ No Wikidata entity was found for the brand
What we saw
We couldn’t find a Wikidata entity connected to the brand. That leaves an important external reference point missing.
Why this matters for AI SEO
Wikidata can act as a common “source of truth” that helps AI systems reconcile brand identity. Without it, it can be harder for generative engines to confidently match and summarize brand information.
Next step
Create or claim a Wikidata entity for the brand so AI systems have a consistent external identifier to reference.
❌ The homepage’s overall performance rating didn’t meet the benchmark
What we saw
While several responsiveness and stability signals looked okay, the homepage’s overall performance rating came in below the expected bar. This suggests the page experience may still feel heavier than ideal.
Why this matters for AI SEO
When pages are less efficient to load and use, crawlers and systems that evaluate quality signals may be less likely to prioritize them. That can reduce how reliably content gets processed and surfaced.
Next step
Improve the homepage’s overall performance so it loads and runs more efficiently for users and crawlers.
❌ Employee-related negative reputation signals were present
What we saw
At least one model response surfaced negative employee-related commentary associated with the brand. This creates a reputational flag that can show up in AI-generated summaries.
Why this matters for AI SEO
Generative engines often reflect prominent sentiment they find about a brand. Negative employee narratives can influence how the brand is described, even when users aren’t explicitly asking about hiring or culture.
Next step
Review the employee-related narratives that appear about the brand and make sure your public-facing story is clear and consistent.
❌ The brand wasn’t consistently recognized by multiple AI models
What we saw
We didn’t see a clear signal that multiple models consistently recognize the brand. That usually means the brand isn’t strongly established across common reference sources.
Why this matters for AI SEO
When recognition is inconsistent, AI answers may be vague or omit the brand entirely. Stronger, consistent recognition helps AI systems respond with more certainty.
Next step
Strengthen the brand’s public footprint so it’s easier for AI systems to confidently recognize and describe it.
❌ Brand identity details didn’t come through as consistent
What we saw
We didn’t see a complete, consistent set of identity details across the evaluated signals. In particular, core identity fields didn’t fully line up.
Why this matters for AI SEO
AI systems rely on consistent identity cues to avoid mixing up brands or presenting outdated details. When identity signals don’t align, trust and accuracy can suffer.
Next step
Make sure your core brand identity details are presented consistently wherever your brand is described.
❌ No matching Wikidata entity could be confirmed for the brand
What we saw
We weren’t able to confirm a Wikidata record that matches the brand. That removes a common external validation anchor.
Why this matters for AI SEO
A confirmed entity record helps AI systems resolve “which brand is which,” especially when names are similar. Without it, brand context can be harder to validate.
Next step
Establish a Wikidata entry that clearly matches the brand name and official web presence.
❌ Wikidata didn’t show official identity anchors for the brand
What we saw
Because a Wikidata entity wasn’t found, we also didn’t see official anchors there (like an official website reference and related identifiers). This leaves less offsite corroboration for the brand.
Why this matters for AI SEO
Official anchors help AI systems confirm they’re referencing the right entity. When those anchors are missing, AI summaries can be less confident or less complete.
Next step
Ensure the brand’s Wikidata presence includes clear official identity anchors tied to the brand.
❌ Major social profiles weren’t consistently confirmed offsite
What we saw
We didn’t see a clear consensus signal confirming the brand’s major social profiles. That can make it harder for systems to reliably connect your site to your official accounts.
Why this matters for AI SEO
When AI systems can’t confidently link a brand to its official profiles, they may miss helpful context and credibility cues. This can also affect how a brand is represented in AI answers.
Next step
Make sure the brand’s official social profiles are consistently referenced and easy to confirm across the web.
❌ Owned onsite press or press releases weren’t clearly present
What we saw
We didn’t see clear evidence of onsite press or press release content. That limits how much “official narrative” the site provides about announcements and milestones.
Why this matters for AI SEO
AI systems pull context from authoritative, clearly attributable sources. When the brand’s own announcements aren’t easy to find, the story can skew toward whatever offsite sources emphasize.
Next step
Publish and maintain a clear onsite area that covers official brand announcements and press items.
❌ No schema markup was found on the resource page
What we saw
On the resource page, we didn’t see any structured markup included. This removes a common set of cues that help clarify what the page represents.
Why this matters for AI SEO
Clear labeling helps generative systems interpret content type, ownership, and context more reliably. Without it, the page can be harder to summarize and attribute.
Next step
Add structured markup to the resource page so its key attributes are clearly defined.
❌ No author was identified on the resource page
What we saw
We weren’t able to find an author name in visible content or supporting page signals. That makes it unclear who wrote the piece.
Why this matters for AI SEO
Author attribution is a meaningful trust cue, especially for informational content. Missing authorship can reduce confidence in the content’s provenance.
Next step
Add a clear author name to the resource page and keep it consistent across similar content.
❌ No publish or update date was found on the resource page
What we saw
We didn’t see a publish date or “last updated” date in the page content or supporting signals. That makes freshness and context harder to judge.
Why this matters for AI SEO
Dates help AI systems understand timeliness and avoid presenting outdated guidance as current. Without a date, summarization and citation can be less accurate.
Next step
Display a clear publish date and, when relevant, a last-updated date on the resource page.
❌ Freshness couldn’t be confirmed for the resource content
What we saw
Because no update or modified date was present, we couldn’t confirm whether the content has been updated recently. This leaves the recency of the content ambiguous.
Why this matters for AI SEO
Generative engines often favor content that appears current when answering time-sensitive questions. When freshness isn’t clear, the content may be treated as less reliable.
Next step
Include an explicit “last updated” signal on the resource content when changes are made.
❌ No outbound external links were detected on the resource page
What we saw
We didn’t find any qualifying links from the resource page to external, third-party sources. That means the page isn’t pointing readers to supporting references.
Why this matters for AI SEO
External citations can help AI systems understand what a piece is grounded in and how it relates to the broader information landscape. Without them, content can read as less substantiated.
Next step
Add at least one relevant external reference link where it naturally supports the content.
❌ Question-based subheadings weren’t found
What we saw
We didn’t see question-style subheadings on the resource page. This reduces how clearly the page maps to common user questions.
Why this matters for AI SEO
Generative engines often match content to questions and prompts. When a page doesn’t clearly frame questions, it can be harder for AI to extract direct answers.
Next step
Use question-style subheadings in the content where it makes sense to mirror how people search.
❌ Descriptive subheadings couldn’t be confirmed
What we saw
We didn’t see a subheading structure that could be evaluated for descriptiveness. That suggests the page isn’t broken into clearly labeled sections.
Why this matters for AI SEO
Clear section labels help AI systems understand what each part of the page is about. Without them, content can be harder to parse and summarize cleanly.
Next step
Add descriptive subheadings that clearly communicate what each section covers.
❌ Section sizing couldn’t be evaluated
What we saw
Because sections weren’t clearly defined with subheadings, we couldn’t evaluate whether sections were sized in a readable, scannable way. This points to limited visible structure.
Why this matters for AI SEO
Well-structured sections make it easier for AI to extract coherent chunks of information. When structure is unclear, key details can be missed or blended together.
Next step
Organize the content into clear sections so each topic is contained and easy to scan.
❌ Consistent section structure couldn’t be confirmed
What we saw
There weren’t enough clearly defined sections to assess whether the page follows a consistent structure. This makes the page feel less standardized.
Why this matters for AI SEO
Consistency helps AI systems identify patterns and extract answers reliably across a page. When structure is inconsistent or missing, extraction becomes less dependable.
Next step
Use a consistent section format across the resource content so key information is easier to interpret.
❌ Early-answer formatting couldn’t be checked
What we saw
We couldn’t confirm whether key answers appear early in sections because section and paragraph structure wasn’t available to evaluate. This limits how easily the content can be summarized.
Why this matters for AI SEO
AI systems often pull concise answers from the most obvious, front-loaded parts of a section. If that structure isn’t clear, the best answer text may not be as extractable.
Next step
Format sections so the main takeaway is easy to spot near the start of each section.
❌ No clear target audience/intent signal was detected
What we saw
We didn’t find language that clearly signals who the content is for or what specific use case it’s meant to address. That can make the content’s purpose feel broad or unclear.
Why this matters for AI SEO
When audience and intent are explicit, AI systems can match the content to the right queries more accurately. Without that signal, the page may be less likely to show up for the right prompts.
Next step
Add a clear statement that indicates who the content is intended for and what it helps them do.
❌ No HTML table was found (bonus signal)
What we saw
We didn’t see any table-based formatting on the resource page. That means there isn’t an obvious structured block for comparisons, definitions, or quick reference.
Why this matters for AI SEO
Tables can make key information easier for AI systems to extract cleanly and reuse accurately. Without them, structured facts may be harder to pull out.
Next step
Where it fits the content, include a simple table to present key information in a structured way.
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.
