Artikel zu AI Visibility
Meta's Muse: What the First Mass-Market AI Agent Means for Brand Visibility
Meta's Muse hit 5 million downloads in 22 days and buys on users' behalf. We pull together Meta's own claims, TIME's investigation, Profound's shopping study and the best Substack analysis to show how the agent picks products, and what brands need to change.
AI Visibility Is Three Problems, Not One: Retrieval, Knowledge Graph, Context Graph
AI visibility is not one metric. It is three structural problems on three different layers — retrieval, knowledge graph, context graph — each needing a different fix. How to diagnose which layer is broken before producing more content.
AI Visibility Needs Data for Decisions and Evidence for Conversations
AI visibility is not one metric. It is at least four — memory, retrieval, paraphrase, and competitive substitution — and each demands a different fix. How to measure them and bring the right evidence to a leadership conversation.
Don't Measure Once: How to Reliably Measure AI Visibility
New research shows that measuring a brand's AI visibility requires simultaneous and longer-term repeated measurements — not one-time ranking snapshots. Here are the key findings and what they mean for marketers.