Artikel zu Measurement
Search Routes Out. LLMs Keep You In. Why AI Visibility Needs New ROI Math
AI referrals as a percentage of traffic are the wrong metric. Search was built to route out; LLMs were built to keep users in. The new measurement is being the source the answer is built from.
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.
Vector Alignment Scores Are Not Truth: Reading the Number Without Falling for It
Vector alignment scoring is a real upgrade over keyword research — and a real trap if you read the number as ground truth. Why production retrieval signals matter more than offline embeddings, and how Aurora closes the gap.
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.