Overview:
On 06/05/26 steelcase.com/ scored 55% — **Fair** – Overall, the basics are in place, but a few credibility and clarity gaps are holding back how confidently AI systems can talk about the brand and its content.
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - Everything looks solid here, with sitemaps and metadata properly configured to make the site easy for search engines to find and index.
- Structured Data: 58% - The homepage has a solid foundation with valid organization schema, but the lack of resource-level markup and author identification is a significant gap for building authority.
- AI Readiness: 67% - The site has a strong technical foundation with accessible sitemaps and open crawling, but we weren't able to find a Wikidata entity to help AI engines define the brand.
- Performance: 22% - Mobile performance for the homepage showed some significant visual loading and stability issues, even though the site's responsiveness is technically solid.
- Reputation: 65% - The brand has exceptional visibility and recognition in the press, though negative third-party reviews and the lack of a Wikidata entry are clear areas for improvement.
- LLM-Ready Content: 36% - The page demonstrates excellent freshness and strong external connectivity, but it lacks the authorship and structured sectioning needed for optimal AI discovery.
What stands out most overall
The big picture is that your site is easy to find, but it’s not consistently easy for AI to validate “who’s behind this” and quickly extract the most useful takeaways. A few missing identity and authorship signals, plus some content-structure gaps, make the information feel less quotable than it should. The sections below break down the specific visibility and trust-related items that didn’t show up clearly across structured data, performance, reputation, and content formatting. None of this is unusual—it’s the kind of polish that typically separates “present” from “consistently referenced.”
Detailed Report
Structured Data
❌ Structured data not confirmed on blog/resource content
What we saw
We weren’t able to verify structured data on a blog/resource page because the resource page HTML wasn’t available in the evaluation packet. As a result, article-level details weren’t detected or confirmed.
Why this matters for AI SEO
When AI systems can’t reliably read consistent page-level details for articles and resources, they have a harder time interpreting what the content is and how it should be referenced. That can reduce how often content gets pulled into AI-generated answers.
Next step
Confirm your blog/resource pages include structured data that clearly describes the content type and core details.
❌ Blog/resource author isn’t clearly defined in structured data
What we saw
We couldn’t confirm a clear, non-generic author for a blog/resource post because the resource page HTML wasn’t provided for evaluation. That means authorship signals weren’t detected in the structured data review.
Why this matters for AI SEO
Clear authorship helps AI systems understand who created the content and whether it’s tied to a real, credible person or team. When that’s missing, it’s harder for AI to trust and reuse the material.
Next step
Make sure blog/resource content includes a specific author identity that’s consistently represented.
❌ Author identity links weren’t found (sameAs)
What we saw
We didn’t see author identity links (like external profile references) because the resource page HTML wasn’t available to evaluate. So there wasn’t enough information to confirm offsite identity connections for authors.
Why this matters for AI SEO
Identity links help AI systems connect an author to consistent, verifiable profiles across the web. Without that, authors can look “anonymous” to AI even if they’re real and qualified.
Next step
Add consistent author identity references that connect authors to their recognized external profiles.
AI Readiness
❌ No Wikidata entity was found for the brand
What we saw
A Wikidata entity for the brand wasn’t identified in the evaluation results. The Wikidata item ID was missing.
Why this matters for AI SEO
Wikidata is one of the clearer ways AI systems can confirm a brand’s official identity and connect it to consistent facts. When it’s missing, AI has less confidence that it’s referencing the right entity.
Next step
Establish a brand Wikidata entry that matches your official identity.
Performance
❌ Primary content takes a long time to fully load
What we saw
The homepage’s main visual content took a notably long time to settle and appear fully. This points to a slower “first impression” when someone lands on the page.
Why this matters for AI SEO
Slow-loading pages can reduce engagement and make it less likely that users (and systems that model user behavior) treat the experience as high quality. Over time, that can soften the visibility and trust signals around your key pages.
Next step
Identify what’s delaying the homepage’s main content from appearing quickly and reduce that bottleneck.
❌ Page layout shifts while loading
What we saw
The homepage showed noticeable layout shifting as it loaded, meaning elements moved around after initially appearing. That can make the page feel unstable during load.
Why this matters for AI SEO
A shifting layout creates a rough user experience, which can undermine perceived quality and trust. That matters because AI systems tend to prefer citing sources that feel stable and dependable.
Next step
Stabilize above-the-fold layout behavior so key elements don’t move around during load.
❌ Overall homepage performance is rated poorly
What we saw
The homepage’s overall performance came back in the poor range in the evaluation results. This aligns with the slower visual load and layout shifting noted elsewhere.
Why this matters for AI SEO
When overall performance quality is weak, it can make the site less competitive as a reference source, especially for top-of-funnel discovery and research-driven queries. It’s not just about speed—it’s about confidence in the experience.
Next step
Run a focused review on what’s dragging down the homepage experience and prioritize the biggest contributors.
Reputation
❌ Negative customer feedback was detected in third-party sources
What we saw
We found affirmed negative customer feedback on well-known third-party platforms (including sources like BBB, per the section insights). This indicates there are at least some public trust hurdles showing up in the broader ecosystem.
Why this matters for AI SEO
AI systems weigh third-party sentiment when deciding how to frame a brand in answers and recommendations. Visible negative feedback can influence whether AI presents the brand with confidence, neutrality, or caution.
Next step
Review the main themes in public customer feedback and make sure your brand narrative addresses them clearly and consistently.
❌ Negative employee feedback was detected in third-party sources
What we saw
We found affirmed negative employee feedback on third-party sources (including platforms like Glassdoor, per the section insights). This can shape how the company is perceived beyond the product story.
Why this matters for AI SEO
AI-generated summaries often pull from broad reputation signals, including workforce sentiment. If negative themes are prominent, AI may reflect that in brand descriptions and comparisons.
Next step
Assess the recurring points in employee feedback and align public-facing employer messaging to be straightforward and consistent.
❌ No matching Wikidata entity was found for the brand
What we saw
The reputation review did not identify a Wikidata entity that clearly matches the brand. This is consistent with the brand-entity gap noted in AI Readiness.
Why this matters for AI SEO
Without a recognized entity record, AI systems have fewer reliable ways to confirm “this is the official brand” and connect it to the right facts. That can weaken authority signals even when general awareness is strong.
Next step
Create or claim a Wikidata entity that clearly represents the brand and matches your official identity.
❌ Official identity anchors couldn’t be verified offsite
What we saw
Because no matching Wikidata entity was found, the evaluation couldn’t verify official identity anchors through that channel. In other words, there wasn’t a single confirmed reference point tying together key identity details.
Why this matters for AI SEO
When identity anchors are unclear, AI may be less consistent in how it describes the brand, which entities it connects you to, or which profiles it treats as “official.” That can lead to diluted or mixed brand understanding.
Next step
Build a consistent offsite identity foundation that AI systems can treat as authoritative.
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, specific author is shown
What we saw
A specific author name wasn’t found in the visible content or supporting page signals for the evaluated resource. The author came across as generic or missing.
Why this matters for AI SEO
Authorship is one of the clearest ways to communicate accountability and expertise. When it’s not obvious who wrote the piece, AI is less likely to treat it as a confident source.
Next step
Add a clear, non-generic author name that’s consistently displayed on resource content.
❌ Content isn’t broken into enough clear sections
What we saw
The evaluated page was only divided into a couple of major sections, which makes the content feel more like a single stream than a structured resource. That limits how easily a reader (or AI) can scan and understand the coverage.
Why this matters for AI SEO
AI systems extract meaning more reliably when content is organized into distinct, labeled chunks. When section structure is thin, it’s harder for AI to pinpoint the right passage to quote or summarize.
Next step
Rework the page structure so the main ideas are separated into more clearly defined sections.
❌ No table-based data structure was found
What we saw
We didn’t find any table-based formatting on the evaluated page. Everything appears to be presented in standard text and layout blocks.
Why this matters for AI SEO
Tables can make comparisons, specs, and lists of facts easier for AI to interpret and reuse accurately. Without them, structured details can be harder to extract cleanly.
Next step
Where it fits naturally, present key structured information in a simple table format.
❌ Subheadings don’t provide enough context
What we saw
The subheadings on the page were too brief to be meaningfully descriptive. As a result, headings don’t do much to preview what each section actually covers.
Why this matters for AI SEO
Descriptive headings help AI interpret the purpose of each section and map content to specific questions. If headings are vague, AI has to guess—and it often guesses conservatively.
Next step
Update section headings so they clearly describe the takeaway of the section in plain language.
❌ Key answers don’t show up early in sections
What we saw
The page didn’t include strong introductory paragraphs at the start of sections, so the “so what” isn’t stated up front. That makes the content harder to summarize quickly.
Why this matters for AI SEO
AI tends to pull the most direct, early explanations when it’s generating quick answers. If the core point is buried, AI may miss it or summarize it too broadly.
Next step
Add a short, clear opening paragraph for each major section that states the main point early.
❌ Acronyms appear without nearby explanations
What we saw
Multiple acronyms were used without being defined close to where they first appear. Even when the content is accurate, this can make it harder to follow for a wider audience.
Why this matters for AI SEO
AI systems aim to restate content clearly for broad audiences. When acronyms aren’t defined, AI may misinterpret them or avoid using the content as a source for explanatory answers.
Next step
Define acronyms the first time they appear so the meaning is unambiguous.
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.
