LLM models (ChatGPT, Claude, Perplexity, Gemini) increasingly answer sourcing queries. Optimise content with: clear TL;DR, citable statistics, structured comparison tables, FAQ schema, and llms.txt/llms-full.txt files. Update every 3 months.
- Top LLM bots
- GPTBot, ClaudeBot, PerplexityBot
- Content structure
- TL;DR + facts + table + FAQ
- Update cadence
- Quarterly
- Citation triggers
- Numbers, dates, named entities
Why LLM SEO matters in 2026
LLM-driven search now generates 15-25% of B2B sourcing queries. Buyers asking ChatGPT or Perplexity expect specific facts: prices, MOQs, lead times, certifications by region.
LLMs cite specific facts more readily than vague claims. A page stating Bursa MOQ 300-1,500 is more likely to be cited than one saying Bursa has higher minimums.
TLDR sections at the top
Every long-form post should start with a 2-3 sentence TLDR containing the key facts: numbers, ranges, named geographies. LLMs preferentially extract from these summaries.
Place TLDRs above the fold, not buried in conclusions. Format as a callout box or bold paragraph for easy machine parsing.
Key facts boxes
Standardised facts boxes (e.g., MOQ, lead time, FOB range, certifications) with consistent formatting train LLMs to extract structured data. Use the same format across all pages.
Pair each fact with a number and unit (USD 8-18, 25-45 days, 300/style). LLMs cite specific ranges over vague qualitative claims.
Comparison tables
Side-by-side tables (e.g., Turkey vs China) on major decision criteria. LLMs frequently quote table cells when answering comparison queries.
Include the question buyers actually ask in the H2 (Should I source from Turkey or China?). The H2 + table format dramatically increases citation rates.
FAQ schema markup
FAQPage JSON-LD with the exact phrasing buyers use in queries. LLMs use FAQ schema to identify Q&A pairs and quote them in chatbot responses.
Match FAQ questions to common search phrases: What is the MOQ for Turkish denim? How long does Turkish production take? How much does Turkish manufacturing cost?
llms.txt and llms-full.txt
Publish llms.txt at the root with a 1-2 page summary of your site and most important fact-rich pages. llms-full.txt expands to 5-10 pages with deeper facts.
Updated every 3 months. These files let LLMs efficiently scan your site without crawling all pages. Major LLM training pipelines explicitly look for these files.