The finding: SEO helps, but most citations live off the traditional map

A wave of 2026 vendor research keeps landing on the same uncomfortable pair of facts. Strong classic SEO still raises your odds of being cited by an LLM — and most of what LLMs actually recommend never shows up in a traditional rank tracker. A directional analysis circulated at roughly 29,562 domains echoes earlier work by Kevin Indig, whose study of ~98,000 citation rows from ~1.2M ChatGPT responses found that ranking #1 in Google correlates strongly with being cited: 43.2% of top-ranking pages were cited, versus far lower rates beyond position 20.

The catch is concentration and invisibility. In that same dataset, the top 30 domains captured 67% of citations within a topic, and ChatGPT retrieved roughly 6x more pages than it cited — about 85% of retrieved pages were never cited. Separately, The Digital Bloom reports that ~80% of ChatGPT-cited URLs don’t rank in Google’s top 100 for the same query. Both can be true: page-level relevance lifts your odds, while a long tail of citations comes from forums and community threads that classic metrics never measured.

Domain authority is not the signal people think it is

This is where the nuance bites. Page-level ranking helps, but domain-level authority scores largely don’t. Search Atlas’s correlation analysis across 21,767 domains found Domain Authority barely moves AI visibility — ChatGPT r ≈ −0.12, Perplexity r ≈ −0.18, Gemini r ≈ −0.09. Treat the exact coefficients as single-study, directional figures, but the direction matches a broader pattern: brand mentions and topical coverage now out-predict backlink-derived authority.

What controlled experiments actually killed

The most useful 2026 work is the experiments that failed. In OtterlyAI’s Markdown-vs-HTML test, .md mirrors of live pages — given equal footer-link discovery — drew 0% of AI-bot visits and zero citations over 14 days, while HTML versions pulled 7.4% of bot traffic and were the only format cited. The same body of work found llms.txt drew ~0.1% of AI-bot traffic, performing roughly 3x worse than an average content page. Search Engine Land’s review reaches the same verdict: there is no evidence llms.txt boosts inclusion, and several schema-markup “wins” survive only as correlations with plausible rival explanations.

What the data suggests actually works

  • Be indexed by Bing. ChatGPT discovers candidate pages via the Bing index, and Seer Interactive’s audit found ~87% of SearchGPT citations match Bing’s top results. Submitting via IndexNow accelerates discovery — a low-cost, high-leverage prerequisite.
  • Ship reference-grade, extractable HTML. Citations cluster in the upper sections of long-form pages (Indig found the 10–20% band performs best; 5,000–10,000-character pages earn the most). Quotable, self-contained passages beat clever formatting tricks.
  • Earn entity and brand coverage. Broad topical clusters and brand mentions correlate with citation more than isolated keyword pages.
  • Show up where LLMs read. OtterlyAI’s AI Citation Economy report (1M+ citations) puts community platforms at 52.5% of citations, with Reddit the single most-cited domain across ChatGPT, Perplexity and AI Overviews. Reddit’s question-and-thread structure maps cleanly onto long-tail intent, which is why it over-indexes.
  • Keep content fresh. Recency is the recommendation with the strongest evidence base for time-sensitive queries.

What is hype

Markdown mirrors, llms.txt files, and “chunking” your pages for crawlers are, on current evidence, near-zero-yield. Schema markup may help indexing hygiene but should not be sold as a direct citation lever. And any single vendor’s correlation coefficient — including the 29,562-domain figure — is directional, not gospel; most of this research is observational, platform-specific, and shifts month to month.

Bottom line

GEO/AEO is not a replacement for SEO; it’s SEO with a different distribution. Get into Bing, write citable HTML, build entity depth, and earn presence on the community sites LLMs trust. Then measure per platform — ChatGPT, Perplexity and AI Overviews overlap on as little as 11% of cited sources — because a win on one engine tells you little about the others.