Valid answers
180/180
30 questions, 6 platforms, and 1 collection round
Evidence
GEO Lens Self-Diagnosis Benchmark
The GEO Lens benchmark is a repeatable self-diagnosis process. Each month, GEO Lens can run a fixed question set to record brand mentions, competitor or alternative appearances, cited sources, uncovered questions, and month-over-month changes. The first production run in July 2026 retrieved 180 out of 180 answers, with a 9.4% mention rate, 8.3% Top3 rate, 76.1% source coverage, and 0% owned-domain citation rate.
Last updated: 2026-07-05/GEO Lens public guidance
July 2026 baseline results
| Field | Result | Interpretation |
|---|---|---|
| Valid answers | 180 / 180 | 30 questions, 6 platforms, and 1 collection round |
| Mention rate | 9.4% | Product and tool-comparison questions performed best |
| Top3 rate | 8.3% | Recommendation position is still weak |
| Source coverage | 76.1% | Many answers cite sources, but not GEO Lens owned domains |
| Owned citations | 0% | The next cycle should prioritize owned-source and external proof |
Flow
- 1Valid answers
- 2Mention rate
- 3Top3 rate
- 4Source coverage
- 5Owned citations
Evidence sample
2026-07 self-diagnosis benchmark
GEO Lens ran its first production self-diagnosis benchmark in July 2026 across 24 stable questions, 6 exploratory questions, and 6 available production platforms. The public version shows redacted aggregate metrics only.
Mention rate
9.4%
Product and tool-comparison buckets performed best
Top3 rate
8.3%
Estimated from visible answer ordering
Owned citations
0%
No retrieved answer cited geo.9fox.ai or 9fox.ai
Monthly benchmark board
Board1Stable questions
2Target platforms
3Cited pages
4Content backlog
Each run records questions, platforms, mentions, competitors, source pages, and next actions to create a repeatable GEO operating rhythm.
Question bucket coverage
Structure1Product definition
2Pricing and credits
3Report interpretation
4Agency presales
5Retest comparison
Stable trend questions should be separated from exploratory questions so month-over-month results remain comparable.
2026-07 bucket results
| Bucket | Valid answers | Mention rate | Next action |
|---|---|---|---|
| Product definition | 24 / 24 | 50.0% | Strengthen entity, product, and citation pages |
| Methodology | 24 / 24 | 0% | Tie GEO, SEO, and AEO definitions back to GEO Lens examples |
| Report interpretation | 24 / 24 | 0% | Add report-reading, source-attribution, and retest evidence |
| Tool comparison | 18 / 18 | 27.8% | Expand GEO Lens vs manual ChatGPT and SEO-tool comparisons |
2026-07 alternative signals
| Alternative category | Count | Interpretation |
|---|---|---|
| Traditional SEO tools | 50 | AI still frames many queries through traditional SEO |
| AI SEO consulting services | 28 | Consulting/service language is easier for AI to cite |
| GEO diagnosis service providers | 10 | GEO service entities exist but remain fragmented |
| Manual ChatGPT questioning | 9 | Comparison pages should explain systematic diagnosis value |
- This run was collected on 2026-07-05 across Doubao, DeepSeek, Yuanbao, Qianwen, Baidu AI, and Kimi.
- This is the first baseline. Stable monthly questions should remain fixed while exploratory questions are reported separately.
- The most important finding is 0% owned-domain citation, so the next cycle should prioritize owned sources and credible external mentions.
- Benchmarks should use GEO Lens self-data or fully redacted aggregate data, not private customer reports.
Why benchmark the product itself
GEO Lens sells AI visibility diagnosis, so its own visibility should be measured with the same product logic and reported transparently.
How to use benchmark results
Turn findings into a backlog for public pages, docs, pricing clarity, report examples, third-party mentions, and technical SEO fixes. The July 2026 baseline points first to owned-domain citations, methodology pages, report interpretation, pricing/payment clarity, comparison pages, and external proof.
Frequently Asked Questions
Should the question set stay stable?
Yes. A stable core question set makes month-over-month comparison possible.
Can benchmark data include customers?
Public benchmark data should use GEO Lens self-data or aggregated redacted data only.
Does benchmark visibility prove conversion?
No. It measures AI answer visibility signals, not guaranteed traffic or revenue.
Measure AI visibility repeatedly
Use fixed questions and clear evidence to track whether visibility improves.
Methodology note
The July 2026 run covered 24 stable questions, 6 exploratory questions, 6 available production platforms, and 1 collection round. Public versions use redacted aggregate metrics only.