SEO has Google Search Console. You get clicks, impressions, rankings — a clear feedback loop.
GEO has nothing.
You publish structured content, optimize for AI citation patterns, write comparison articles and FAQ pages. Then you wait. And you have no idea if ChatGPT, Claude, or Perplexity is actually recommending your brand more often.
This is the core problem with GEO in 2026: the work is visible, the results are not.
Why Traditional Analytics Can't Help
Google Analytics tells you who clicked your link. It can't tell you:
- Whether ChatGPT mentioned your brand when someone asked for a recommendation
- Whether your brand appears in AI answers for industry keywords
- Whether AI describes your brand accurately or incorrectly
- How your AI visibility compares to competitors
When a user asks an AI "what's the best project management tool?", there's no referral traffic if the AI answers without linking to your site. No impression. No click. The recommendation just happens — invisibly.
This is the measurement gap that every brand doing GEO currently faces.
What "AI Visibility" Actually Measures
AI visibility isn't binary (mentioned vs. not mentioned). It breaks down into two distinct dimensions:
Discovery Score — Are you found when users don't already know you?
This is pure GEO territory. It asks: when someone searches for a solution category (not your brand name), does AI recommend you? A brand can be well-known but have zero discovery score if AI never brings it up in generic recommendations.
Brand Score — When AI does mention you, what does it say?
This measures sentiment accuracy and consistency. Does the AI describe your brand the way you'd describe it? Is it positive, neutral, or subtly negative? Do different AI models agree on your narrative, or does ChatGPT say one thing while Claude says another?
The combined score (Discovery × 60% + Brand × 40%) gives you a single comparable number.
The Before/After Problem
GEO optimization cycles take 4-8 weeks. You publish comparison content, get cited in Reddit threads, build structured FAQ pages. After 6 weeks, has anything changed?
Without measurement, you're guessing.
The correct approach:
- Baseline scan — Run an AI visibility report before you start any GEO work. Record your scores across query types.
- Identify your blind spots — Which scenario types does AI never mention you in? That's where your content gap is.
- Execute targeted content — Create content specifically targeting your blind-spot query types.
- Rescan after 4-6 weeks — Compare scores. Did discovery improve? Did the narrative accuracy change?
Without step 1 and step 4, you have no idea if step 3 did anything.
What Good GEO Progress Looks Like
A B2B SaaS brand starts with a Discovery Score of 34. They publish three structured comparison articles and get cited in two industry newsletters. Six weeks later: Discovery Score 51. A 50% improvement directly attributable to specific content actions.
A consumer brand with high brand awareness (Brand Score 78) but low discovery (Discovery Score 29) learns that AI never recommends them in recommendation query types. They shift content focus from brand storytelling to problem-solution framing. Discovery Score improves to 44.
The pattern: awareness ≠ discoverability.
The Specific Queries That Matter
- Recommendation queries ("best [category] for [use case]") — highest purchase intent
- Comparison queries ("[Brand] vs [Competitor]") — where AI citation often wins or loses deals
- Beginner queries — high volume, often the first AI interaction a new user has
- Trust queries ("is [Brand] reliable") — where brand score matters most
The Measurement Framework
- Monthly baseline scans — Same brand, same keywords, same competitor, every 30 days
- Track by query type — Aggregate scores hide the signal
- Monitor narrative accuracy — Is AI saying what you want it to say?
- Competitor benchmarking — Your score relative to whoever AI recommends instead of you
GEO without measurement is just content production. The feedback loop is what turns it into a strategy.
Anchor is an AI brand visibility scanner that measures how well brands appear in AI-generated recommendations.
