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Documentation Index

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What others say about you is harder to influence and has less impact than what you say about yourself. Recent research shows that 94.7% of AI citations come from corporate content — the pages brands publish themselves — with UGC (Reddit, forums, Medium) accounting for less than 6% across most verticals (Kevin Indig, The Science of What AI Actually Rewards, March 2026, analysing 98,217 ChatGPT citations across seven verticals). The leverage sits on your own pages, because they are the part you directly change and where change lands immediately. That is where zued focuses its analysis and recommendations.
In most verticals, no. Kevin Indig’s March 2026 analysis of 98,217 ChatGPT citations found corporate content accounts for 94.7% of all citations, with Finance at just 0.5% UGC and Healthcare at 1.8%. The “Reddit effect” that reshaped organic search in 2024 and 2025 has not translated proportionally to AI citations. Three verticals did show measurable UGC value: Crypto (9.2%), Product Analytics (6.9%) and HR Tech (5.8%), where community content answers a meaningful share of queries. Outside those, invest in your own authoritative content first. zued focuses exclusively on what you can change yourself, which is also where the data says the leverage sits.
No. The most consistent finding from recent citation research is that AI citation is a content architecture problem, not a content quality problem. Thin single-intent pages are structurally locked out of AI citations regardless of how well they are written. Word count, list density and named entity counts are flat or even negative predictors at the aggregate across verticals (Kevin Indig, The Science of What AI Actually Rewards, March 2026). What zued analyses — content architecture, chunk-level alignment, technical signals, schema coverage per page type, internal linking between related URLs — is exactly where the actual leverage is.
Audit prompts are designed to be repeatable and neutral, not to replicate any individual user’s phrasing. Real users have chat history, memory, and personalisation that produce unique, non-reproducible responses. Even if you had the exact text of a real user’s prompt, running it in a neutral session wouldn’t produce the same answer. zued’s prompts run in consistent sessions so the same probe produces a comparable result every week — that consistency is what makes trend tracking reliable.
ICPs are extracted from your page content — not from your CRM or external data. zued clusters persona signals from all your URLs into 5–6 profiles that represent how your existing pages position themselves. If your content addresses a broader range of audiences, you can edit the generated ICPs manually to better reflect them.
AI responses are non-deterministic — the same prompt can produce different answers across runs. This is a fundamental property of how AI engines work, not a measurement issue. Small week-to-week swings are usually sampling noise, not real change. Treat any single snapshot as a point estimate with a margin of error around it, and look for movement that persists across multiple snapshots before reading it as a trend. The larger the jump and the more consistent it is week over week, the more likely it reflects a real shift in how AI engines describe your topic.
No — each engine uses its own crawler with its own user agent. Blocking GPTBot in robots.txt has no effect on PerplexityBot or Bingbot. But blocking any single one means zero visibility for that engine’s users. zued’s bot accessibility check shows exactly which crawlers are blocked, per URL.
All URL data, analysis results, and snapshot history are preserved — nothing is deleted. Weekly snapshots stop, but all existing URLs and their history remain visible.
Each AI engine retrieves and interprets content differently. Your page might align well with Gemini’s consensus but drift significantly from what ChatGPT tells users about the same topic. zued scores each engine separately so you can see exactly where and why the gaps differ.
Prompt tracking tools check if your brand appears in AI responses — they answer are you mentioned? zued goes deeper: it compares what AI engines say against what your pages actually contain, identifies specific content gaps, and tells you what to change so your content aligns with the AI consensus and adds information gain. It’s the difference between monitoring whether you show up and knowing what to fix so you show up accurately.
The AI consensus on a topic doesn’t shift day-to-day. What changes meaningfully between weeks is whether your content supports that consensus — and whether your fixes moved the needle. Weekly cadence gives you time to implement recommendations and measure their impact without noise from daily fluctuations.
No. The architectural signals that drive AI visibility compound across engines — better structure, stronger claims, and clearer entity definitions help every engine. The differences between engines are matters of degree, not kind. Which specific signals weigh most does vary by vertical (see Kevin Indig, The Science of What AI Actually Rewards, March 2026 for a cross-vertical analysis showing signal relevance is more vertical-specific than the AEO industry assumes), so the right order is to cover the architectural fundamentals first, then tune for your vertical. Optimizing for a single engine in isolation is the wrong move in every case we have seen. See AI Engines for more.