We Checked Whether On-Site SEO Predicts AI Citations. The Data Says Mostly No.

Every GEO ("generative engine optimization") tool, including ours until

recently, sells some version of the same pitch: fix your robots.txt, add

Schema.org markup, write FAQ schema, and AI engines will cite you more.

We build one of these tools — Causabi scans sites for AI-crawler readiness

and generates fix files (robots.txt, llms.txt, JSON-LD, FAQ blocks). As part

of validating our own scoring weights, we ran the numbers on whether the

score actually predicts getting cited. Short version: it mostly doesn't,

once brand prominence is in the picture.

What we measured

We scored 44 domains on a 6-category on-site readiness algorithm:

• robots.txt (AI bots allowed or blocked)


• Schema.org (Organization/LocalBusiness JSON-LD completeness)


• FAQ schema (FAQPage markup, 3+ entries)


• content depth/structure


• brand/NAP signals


• freshness (dateModified, recency)

Then we checked how often each domain actually got cited by an AI engine

(Claude, via its web-search tool, one measurement window, a fixed prompt set

per domain).

What we found

• On-site score vs. citation rate: Pearson r ≈ -0.08, Spearman ρ ≈ -0.03.
  Functionally no correlation — if anything, a very slight negative one,
  which is more likely noise than a real inverse relationship at this
  sample size.


• 86% of the 44 domains got zero citations in the window, independent of
  their score.


• The domains that did get cited clustered almost entirely by brand
  prominence — well-known domains got cited at a noticeably higher rate
  (~0.16 of prompts) than everyone else (~0 for the rest of the sample),
  regardless of how well-optimized their markup was.

Why I'm not overselling this

n=44 is small. This is an internal validation exercise for our own product,

not a peer-reviewed study, and I don't want it read as one. Specific caveats:

• Single engine (Claude) this round. Citation behavior differs meaningfully
  across ChatGPT, Gemini, Grok, and Perplexity — we haven't run the same
  check across all four yet.


• One time window, no longitudinal before/after. We didn't take a domain,
  improve its score, and watch citations change over months. That's the
  actually convincing experiment and we haven't run it yet.


• Prompt-domain matching wasn't blind. Some prompts were picked because a
  domain plausibly related to that topic, which likely biases toward
  domains that would get mentioned anyway.


• "Brand prominence" is a fuzzy variable that probably absorbs some real
  content-quality signal we're not capturing separately. We can't fully rule
  out that what looks like "brand wins" is partly "genuinely better/more
  authoritative content wins," which on-site markup scoring doesn't measure.

What we still think is true, with more confidence

Some things aren't correlational guesses — they're closer to mechanical

facts:

• 
  robots.txt blocking is binary. If GPTBot, ClaudeBot, or similar are
  disallowed, that engine cites you zero times, by construction. About 89%
  of sites we've scanned block at least one AI crawler by default, usually
  by accident (a blanket Disallow: / that predates AI bots existing).


• 
  FAQ schema changes extraction, not inclusion. For content that's
  already in an engine's consideration set, structuring it as self-contained
  Q&A chunks seems to affect whether it gets pulled into a RAG-style
  citation — this lines up with published research on chunking behavior. But
  that's a "how you're cited" lever, not a "whether you're cited" lever.

Where that leaves the product

We're rewriting our own copy to say what the score actually measures:

AI-crawler readiness and machine-readability, not citation probability. No

tool — ours included — can promise the second one. If your on-site work is

mostly aimed at "getting cited more," the more binding constraint for most

sites is probably brand/mentions elsewhere, not another Schema.org type.

The scoring engine and fix generator are open source (MIT) if you want to

see the logic or run it on your own site without touching our SaaS:

pip install causabi-geo

geo-optimizer analyze https://yourdomain.com

geo-optimizer fix https://yourdomain.com --output ./out

Repo: https://github.com/SHADRINMMM/causabi-geo

Site (hosted version + monitoring): https://causabi.com