When an AI assistant answers a question, it pulls from a handful of sources and names a few. Being one of those names is the new front page of Google. The good news: which sources get cited is far more predictable — and more technical — than most marketers assume.
1. Be machine-readable, not just human-readable
Models extract structure, not vibes. The single highest-leverage move is valid schema.org JSON-LD — Organization, Product/Service, FAQPage — so a model can parse exactly who you are and what you offer without guessing from prose. This is the one lever with repeatedly observed citation lift.
2. Write atomic, quotable claims
Assistants lift short, self-contained, verifiable sentences. Compare:
- ❌ "We deliver world-class, synergistic solutions tailored to your journey."
- ✅ "Acme reduces onboarding time from 14 days to 3."
The second is a claim a model can quote. Structure pages as one idea per heading, with short standalone sentences and an FAQ that answers real questions directly.
3. Ground your identity
Models hedge on entities they can't confirm. Tie your profiles together with a consistent sameAs graph (LinkedIn, Wikidata, official pages) and use one canonical description everywhere. When models agree you exist and what you do, they cite you with confidence.
4. Let the crawlers in — and be fast
If your content only renders after JavaScript, much of it never reaches the model. Serve real HTML, allow AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) in robots.txt, publish a sitemap, and keep latency low.
5. Stay fresh and sourced
Recency and evidence both matter. Emit dateModified, keep content current, and back quantitative claims with a linked source — unsupported superlatives lower a model's trust and get filtered out.
Measure it
You can't improve what you can't see. Run your site through the Legible Readiness Index to score these signals across eight dimensions and get a prioritized list of exactly what to fix first.