Question buckets
4
Trigger, exploration, evaluation, and action
Methodology
GEO Diagnosis Methodology
GEO Lens uses fixed questions, fixed platform scope, and comparable retest methodology to observe brand mentions, recommendation position, source attribution, and competitor gaps in AI answers. It is not a one-off manual prompt or a ranking promise; it is a sampled diagnosis process that turns AI answers into metrics, evidence, and actions.
Last updated: 2026-07-05/GEO Lens public guidance
GEO Lens diagnosis scope
| Step | What happens | Why it matters |
|---|---|---|
| Brand profile | Collect name, aliases, domains, category, competitors, and products | Keeps the diagnosis grounded in the real business |
| Question buckets | Cover trigger, exploration, evaluation, and action intent | Avoids relying on one or two ad hoc prompts |
| Platform collection | Collect AI answers by platform, round, and mode | Compares how different AI systems respond |
| Metric calculation | Calculate mentions, Top3 exposure, source coverage, and competitor gaps | Turns answers into reviewable evidence |
| Report and retest | Generate a report and preserve baseline scope | Lets teams verify whether improvements changed the signal |
Standard diagnosis flow
- 1Create brand
- 2Confirm questions
- 3Select platforms
- 4Generate report
- 5Retest with same scope
Evidence sample
GEO Lens methodology evidence block
The methodology page should be directly citable by search and AI systems. This block fixes the diagnosis definition, question buckets, metrics, data sources, limitations, and external-source work.
Core metrics
9
Mentions, Top3, sources, competitors, stages, platforms, retests
Data sources
6
Brand profile, questions, AI answers, sources, competitors, metrics
Outcome boundary
No guarantee
No ranking, traffic, conversion, or AI recommendation promise
Citable methodology structure
Structure1Definition
2Question buckets
3Metric formulas
4Source attribution
5Limits
A citable methodology should define GEO Lens first, then explain buckets, metrics, sources, and limitations in extractable blocks.
Source-building path
Sources1Owned methodology
2Report sample
3Benchmark
4Directories and reviews
When owned-domain citation is 0%, the next step is to make owned pages, machine-readable files, and third-party mentions reinforce each other.
Citable definitions
| Concept | GEO Lens wording | Required limit |
|---|---|---|
| GEO diagnosis | A fixed-scope diagnosis of brand mentions, positions, sources, and competitor gaps inside AI answers | Sampled evidence, not a ranking guarantee |
| TEEA buckets | Trigger, exploration, evaluation, and action intent questions | Prompt wording can change results |
| Source attribution | Website, directory, media, review, case, and action-path sources behind AI answers | Not every platform returns stable sources |
| Retest | A repeat run with the same brand, questions, platforms, rounds, and mode | Exploratory questions should be tracked separately |
External-source priority
| Source type | Target content | Acceptance signal |
|---|---|---|
| AI/SaaS directories | Product, pricing, and report sample | Public profile links back to GEO Lens |
| Industry articles | Methodology, metrics, and benchmark | Article naturally cites geo.9fox.ai |
| Safe case studies | Redacted before/after and retest evidence | No sensitive customer data exposed |
| Community Q&A | Report reading, GEO vs SEO, tool selection | Useful answer with real context, not spam |
- The methodology page is the main owned citation target for GEO Lens definitions.
- External mentions must be real; do not fabricate listings, reviews, or media coverage.
- Keep the public methodology, report sample, `/geo-methodology.md`, and `/llms-full.txt` aligned.
Why fixed question buckets matter
AI answers are sensitive to prompt wording. Fixed buckets help teams separate awareness, exploration, evaluation, and action-stage questions instead of overreading one random answer.
Why raw evidence matters
Metrics show direction, but raw answers, sources, and competitor context explain the reasons. A report should always let users return to the evidence.
Frequently Asked Questions
How is GEO diagnosis different from manual prompting?
GEO diagnosis fixes questions, platforms, rounds, and metrics. Manual prompting is better for exploration but weaker as a baseline.
What are TEEA question buckets?
They are trigger, exploration, evaluation, and action questions that cover the user journey inside AI answers.
Are more platforms always better?
More platforms broaden coverage but increase cost. Start with the platforms your audience uses most.
Why should retests keep the same scope?
Baseline and retest results are more comparable when questions, platforms, rounds, and mode stay consistent.
Can diagnosis results prove business growth?
No. They measure AI-answer visibility signals and should be combined with traffic, conversion, and business data.
Diagnose AI visibility with a fixed scope
Understand the methodology before reading metrics and recommendations.
Methodology note
Results depend on brand inputs, question set, platforms, rounds, collection time, and external AI system behavior. Reports should be read with those limits visible.