## The Dashboard Looks Great. The Results Don't.
We've talked to brands 6-12 months into their GEO/AEO journey. A disturbing pattern emerges: AI Visibility is up, but traffic from LLMs is down and actual citations are declining.
How is this possible?
## Why AI Visibility Metrics Are Broken
### Problem 1: Snowflake Responses
Every AI response is unique. Run the same prompt 10 times and you'll get 10 different answers. The factors that influence which brands get mentioned include:
- User's conversation history
- Account-level personalization
- Model version and recent updates
- Time of day and server load
- Random sampling in token generation
GEO tools measure a statistically irrelevant sample (100 prompts) out of billions of possible permutations.
### Problem 2: The Citation Mirage
In a test of "top rated sneakers" across ChatGPT accounts, the results varied dramatically:
Account 1: New Balance mentioned 3 times (winner)
Account 2: Hoka mentioned 3 times (winner)
Same prompt. Different accounts. Completely different results. Which brand "won"?
### Problem 3: Zero-Click Erosion
Even when you do get mentioned, citations are declining. AI models increasingly:
- Provide complete answers without linking sources
- Embed product cards with direct checkout
- Summarize multiple sources without attribution
Your "visibility" might be up, but the traffic value of that visibility is approaching zero.
## What to Measure Instead
Focus on metrics that actually connect to business outcomes:
- Direct AI referral traffic — check server logs for AI bot patterns
- Brand search volume — are more people searching for your brand?
- Content engagement — are people spending time on your content?
- Conversion from AI-referred visits — what's the actual revenue impact?
- Share of voice in AI conversations — measured over time, not snapshots
## The Bottom Line
Don't let a dashboard with a purple gradient convince you that vanity metrics are real outcomes. Measure what matters.
Part of our Intelligence analysis series.
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