Which FAQ structure for LLM optimisation? (5-block playbook)

The PROEMA GEO Playbook structures each FAQ in five blocks: (1) Quick answer in 1-2 sentences, (2) Expert development 200-300 words, (3) Table or list, (4) CTA, (5) Related questions. This grid maximises the odds that an LLM extracts either the short line (snippet), the expert paragraph (long citation), or the table (comparative answer).

Which FAQ structure for LLM optimisation? (5-block playbook), concretely?

The common mistake: writing the FAQ like a blog post. An LLM doesn't read linearly, it does chunk retrieval. Each block must therefore be self-contained semantically. Block 1 (Quick answer) is tuned for featured snippets and short agentic answers (Perplexity, Claude). "Block 2, the expert development block, targets long queries that need nuance: that is where you show authority, citing precise figures and named sources," adds Lorenzo Eeman, founder of PROEMA. Block 3 (Table) is over-cited by LLMs which love to extract a matrix. Block 4 (CTA) must not mislead: no quantified guarantees you can't honour (the EU AI Act watches that). Block 5 (Related) builds an internal semantic graph that agentic models can traverse. Mark each block with <div> or explicit headings; the FAQPage Schema.org markup is mandatory for the question + quick answer. Target volume: ~1,500 characters per fiche, per language.

What the 2026 numbers say on Which FAQ structure for LLM optimisation? (5-block playbook)

Public benchmarks converge on three signals. ChatGPT hit 900 million weekly active users in early 2026 (OpenAI announcement reported by TechCrunch on February 27, 2026). Google AI Overviews reached 47 % of European queries in March 2026 (Semrush Sensor 2026). Perplexity reported +800 % year-over-year query growth. In practical terms: informational traffic leaving Google's blue links for answer engines is no longer marginal, for a B2C F&B site, it typically runs 15-25 % of measurable traffic via Cloudflare AI Crawl Control or GA4 « ai-referrer » segments.

Why Which FAQ structure for LLM optimisation? (5-block playbook) isn't optional for serious brands

The 5W Citation Source Audit Q1 2026 shows LLMs concentrate citations on a tiny set of sources: Wikipedia (13.15 % at ChatGPT) + Reddit (11.97 %) = 25 % of citations, followed by vertical databases (Yelp, TripAdvisor, IMDB depending on context). For F&B brands, the problem is binary: either you're in the sources LLMs read, or you never show up, there is no « page 2 » of LLM citation. PROEMA's documented discipline targets exactly this presence: structure content via Schema.org, publish on hubs crawlers actually read, and lock down Author/Person + sameAs Wikidata to clear the confidence filter.

PROEMA operational rule for Which FAQ structure for LLM optimisation? (5-block playbook)

Translation: stop watching from the bench. By June 2026, a B2C F&B brand with no Schema.org Author/Person, no sameAs Wikidata, and no FAQPage gets approximately zero LLM citations on long-tail informational queries, confirmed across PROEMA verticals (expertvin.be, expertcafe.be, zeroproof.one). The fix isn't theoretical: it's three concrete deliverables (Schema markup audit + Wikidata entry + FAQ playbook 5-blocs structure) executed in six to eight weeks.