Everything I test in live sprints - prompt targeting, citation tracking, what actually moves an LLM's answer - lands here first, before it goes near a client deck.
A three-month dataset shows AI search citing what people publish on LinkedIn far more than it cites their profile page - and the shift happened fast.
New ecommerce data shows brands get recommended by name while a different site gets the citation underneath. Two outcomes, not one.
Three platforms, three different citation mechanics. What actually gets you cited by each one, backed by primary research rather than the recycled stats doing the rounds this year.
A new study of 95,000 Claude search records shows it citing sources in a genuinely different way to ChatGPT, starting with which search index it actually reads from.
A plain-English guide to what's actually in your robots.txt file - some AI bots decide whether you get cited, others don't, and blocking the wrong one can cost more than blocking none.
A fact-check of the AI search claims circulating this year - what the research actually supports, and the one claim I couldn't verify.
What the data says most marketing teams are actually doing about AI search visibility, and the specific tools the ones ahead of the curve use.
What two independent studies, covering nearly 1.4 million AI citations between them, actually show about getting cited on LinkedIn - and the myth the data doesn't support.
A practical checklist for vetting an AI search consultant - what to check before you sign, not just what to ask on the call.
A 2025 study tested it directly: inject a fresher date into identical content and every model ranked it higher - what that means for how often you publish.
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