The questions buyers ask, answered in the first sentence.
Answer first, then the reasoning. Including the answers that cost us the sale.
Where a claim rests on a model rather than a live observation, the answer says so in the same sentence.
Is query fan-out real or a theory?
Real and documented. Google describes AI Mode running several related searches per question, and the searches ChatGPT, Perplexity, and Copilot run have been captured and measured at scale. What changes by tool is how far the smaller questions drift from yours, from almost the same words to a near-total rewrite.[src]
Can you see the exact smaller questions for my brand?
On some tools, yes. We capture live fan-outs where they're visible. On Google's and Gemini's surfaces, nobody can, and vendors claiming otherwise are modeling without saying so. Citabld models those tools too, and labels every such row MODELED, checked against the tools we can measure.
How is Citabld different from SEO?
SEO optimizes pages to rank for the words people type. Citabld builds coverage across the smaller questions the AI builds from those words: a different target (a quote inside the answer, not a spot on a links page), a different unit (a passage, not a page), and a different metric (how often the AI names you, not your rank). The fields overlap; the layer that pulls the answer doesn't.
How is Citabld different from VISIBLD?
VISIBLD audits and monitors your AI visibility: where you appear, how you're described, what changed. Citabld is the architecture and content layer that moves those numbers: the question library, the priorities, the production. They pair; each stands alone.
How long until we see citations?
Honest answer: decision-stage topics can move in weeks once the content ships; awareness-stage influence works on the AI's trained picture and moves on a quarterly timeline. We tag every topic by stage and measure it with the metric that can actually move, and we show you which is which before you spend.
Do you write the content, or just tell us what to write?
We write it. The second phase is a full content operation: long pillar pages, short answer blocks, comparison pages with honest verdicts, explainer and research posts, third-party placements, review programs, and structured product feeds. Each piece is drafted, sourced, edited, voice-checked, and shipped by us against the approved priority list.
How in-depth is the content you produce?
Full depth. A priority topic becomes a complete page, built block by block, with original information rather than restated consensus. Every piece carries a written note in its brief on what it contains that no competing piece contains. Pieces that can't answer that don't get written.
How do you keep the content in our voice?
We build a Voice Card from 8 to 12 samples of your actual writing: sentence rhythm, vocabulary, and the claims you will and won't make. Every piece passes a voice check against that card before it ships. Our voice never appears in your content.
What is the free fan-out, and what does it cost?
It costs nothing. Submit one buyer question with a short intake and Citabld generates a sample of the smaller questions the AI would pull against, grouped into topics, with every row labeled MODELED because nothing in a free sample is captured live. It's one question's slice of the full library.
Which tools can you actually measure?
We capture live fan-outs on the tools that expose them, with Perplexity as our calibration anchor because its questions stay close to the original and stable. Google's surfaces and Gemini expose no query logs to anyone, so their rows are modeled from how those tools behave and labeled MODELED without exception.
Who owns the question library?
You do. The Query Map is delivered as a working database you can execute with any team, including one that isn't us. It doubles as your tracked-prompt inventory for measurement, so it keeps reporting after the engagement ends.
Why do you score some topics as unwinnable?
Because some surfaces can't be moved with content. Topics owned by governments, medical bodies, or Wikipedia are facts problems, not content problems, and we fix your facts on those surfaces instead and charge less. Naming them before you spend is the point of scoring.
Do we need VISIBLD to work with Citabld?
No. Each stands alone. VISIBLD measures where you appear in AI answers; Citabld builds the architecture and content that moves it. Running both closes the loop of audit, architecture, production, and measurement, but the Query Map and production work without it.
What do you need from us to start?
Your category, your competitors as you see them (we'll correct that against the AI's view), access to buyer language like sales calls, tickets, or the communities your buyers post in, and 8 to 12 samples of your writing for the voice standard. The mapping call scopes the rest.