The GEO Audit Imperative
Most B2B websites ship content that works for Google but fails in generative AI engines. The distribution is stark: your best-performing SEO page might barely register in Claude. Your thought leadership piece, invisible to Perplexity. Your case study, nowhere in ChatGPT's outputs.
This isn't random. AI models train on different data than search crawlers index. They reward different signals. They answer different questions. And they pull from sources using different trust models.
If you're serious about visibility in ChatGPT, Claude, Perplexity, and AI Overviews, you need to audit what you have—not with SEO frameworks, but with a GEO lens. This is where most teams fail. They assume their SEO foundation is enough. It isn't.
Why Your SEO Content Isn't GEO Content
Different Training Data, Different Cutoffs
Google crawls the live web continuously. Claude trained on data through early 2024. ChatGPT through April 2024. Perplexity indexes differently than either. This means:
Recent content has zero inherent advantage in AI search (training date matters more than publish date)
Content from well-known domains gets indexed faster into training data, but obscure sources sometimes get higher quality signals
Entire categories of your site may predate a model's training window entirely
Citation Weight ≠ Ranking Weight
When ChatGPT surfaces a source in citations, it's applying a citation model, not a ranking algorithm. These reward clarity, specificity, and quotability differently than traditional SEO. A dense how-to with 20 variations on the same idea ranks well in Google. It performs poorly in generative engines because AI models prefer clean, direct statements with limited redundancy.
AI models aren't looking for content optimized for skimming. They're looking for content optimized for extraction and synthesis. If a model can't cleanly pull a fact from your writing, it won't cite you—even if Google ranks you first.
The Audit Framework: Four Dimensions
1. Training Data Inclusion
Start here: Is your content likely in any major model's training set? If your website launched after mid-2023, or if you're behind a paywall, the odds drop sharply. Cross-reference your domain against known training datasets (Common Crawl archives, Hugging Face training data) and audit publication dates relative to each model's cutoff.
2. Query Alignment
Map your top 50 pages to the queries people ask in AI engines. These are different from Google queries. They're longer, more conversational, and often implicit. Someone searches Google for "API authentication best practices." They ask Claude, "How do I securely authenticate API calls without exposing keys in production?" Your content needs to match the second query's specificity, not just the first.
3. Citation Strength
Pull your content and score it on factual density—claims per paragraph. Test it: Can you extract a discrete fact in two sentences or less? If your paragraphs meander, citation probability drops. Run a sample through GPT-4 and ask it to cite you. If it rewrites instead of quoting, your structure isn't GEO-ready.
4. Source Trust Signals
AI models weight institutional credibility heavily. Academic institutions, government bodies, and recognized brands outrank typical B2B sites. If you're not one of these, you need to compensate with specificity, citations of your own, and clear expertise signals. Author bios, credentials, and methodology transparency matter more in GEO than they do in SEO.
Audit Tooling and Signals to Track
You won't find a plug-and-play GEO audit tool yet. Instead, combine existing tools with manual checks:
Use Common Crawl Index to verify your content's presence in historical snapshots
Sample your pages in ChatGPT, Claude, and Perplexity under relevant queries and log what surfaces
Compare your domain authority against domains currently cited in AI outputs for your key topics
Audit content structure: count facts per 100 words, measure average sentence length, test quotability
Check for AI-specific metadata (schema markup, author entity data, publication dates)
Document which pages show up in AI results. Which don't. Which get cited vs. referenced secondhand. This data becomes your roadmap.
How Modulus Approaches This
We run full-stack GEO audits for B2B teams—starting with a query-to-source analysis across all major generative engines. We map your content against training data cutoffs, test for citation strength, and score structural readiness. The output is a prioritized roadmap: which pages to optimize for GEO, which to rebuild, and which to deprecate because they're training-data-restricted.
From there, we retarget your best content for AI discoverability, adjust for query length and conversational specificity, and build authority signals that matter to generative models, not just traditional crawlers.
If you're ready to audit what you have and see where AI search visibility actually lives, explore Generative Engine Optimization (GEO) with our team.
Originally published at modulus1.co.
