Recommendation–Citation Gap: research protocol
A frozen 30-question evaluation panel with reproducible tools to distinguish AI mentions, recommendations and citations. Protocol only; results not yet collected.
Published · HowAICite · Protocol author: Thanh Dan
Frozen questions
24 unbranded and 6 branded. Editorial research prompts, not search-volume data.
Planned attempts per wave
30 questions × 4 consumer surfaces × 3 replicates. US / English.
AI benchmark results
No visibility rate is published. The downloadable observations file is empty.
Research question
Within a fixed sample of GEO tool questions, how often is HowAICite mentioned, positively recommended or cited as a linked source? How often do the recommendation and citation outcomes diverge? This initial self-study validates the collection process; it is not an unbiased league table of vendors.
Collection plan
- Freeze this panel before collection. Start with US / English on ChatGPT Search, Gemini, Perplexity and Google AI Mode.
- Collect three independent attempts per question and surface per wave. Use fresh sessions; document personalization and local settings.
- Record exact prompt, full answer, URLs, timestamp, model if shown and requested/observed location. Preserve unsuccessful attempts.
- If no AI answer is shown, record
no-answer. Record provider errors asfailed. Neither is a negative brand observation. - Keep API observations in their own panel. A web-search API result is not a consumer ChatGPT answer.
- Repeat the same panel weekly. Any change to questions, markets or surfaces produces a new panel version.
Annotation rules
A mention identifies the target brand. A recommendation positively selects it for the user's use case and needs an exact supporting excerpt. A citation attributes a claim to a source on the target domain, including subdomains. Review whether the link supports the claim; do not count every pasted URL as a citation.
Use null for an unreviewed label. Double-review a random 20% of completed answers, document disagreement and resolve labels before publication. A reviewer must not infer recommendation from name frequency.
How the calculation works
Each rate uses fully reviewed, completed answers in the same cohort as its denominator. The tool reports failed, no-answer, unreviewed and attempted counts separately. It splits branded/unbranded prompts, collection method, model, wave and location provenance. Missing planned cells remain visible in wave coverage.
Recommendation without citation, citation without recommendation, and both are separate counts. An empty dataset produces not-collected, not a 0% market visibility claim.
node metrics.mjs prompt-panel.json observations.jsonThe frozen panel
| ID | Question | Cohort |
|---|---|---|
| hac-geo-01 | What are the best GEO tools? | Unbranded |
| hac-geo-02 | What tools can monitor AI visibility? | Unbranded |
| hac-geo-03 | What is the best AI citation tracking software? | Unbranded |
| hac-geo-04 | How can I know if ChatGPT recommends my brand? | Unbranded |
| hac-geo-05 | What are the best alternatives to traditional SEO tools for AI search? | Unbranded |
| hac-geo-06 | Which GEO software is suitable for a small SaaS marketing team? | Unbranded |
| hac-geo-07 | Which AI visibility tools can a small business try before paying? | Unbranded |
| hac-geo-08 | Which answer engine optimization tools suit enterprise teams? | Unbranded |
| hac-geo-09 | Which AI visibility tools support multiple agency clients? | Unbranded |
| hac-geo-10 | Which tools measure AI visibility across countries and languages? | Unbranded |
| hac-geo-11 | Which tools show the websites and pages cited in AI answers? | Unbranded |
| hac-geo-12 | Which tools help identify incorrect brand information in AI answers? | Unbranded |
| hac-geo-13 | What free tools can check a website's AI search readiness? | Unbranded |
| hac-geo-14 | Which AI visibility tools offer documented APIs for reporting? | Unbranded |
| hac-geo-15 | Which tools keep historical AI answers and citations? | Unbranded |
| hac-geo-16 | Which GEO tools let me inspect raw answers behind the scores? | Unbranded |
| hac-geo-17 | How should I compare Profound, Peec AI and smaller GEO tools? | Unbranded |
| hac-geo-18 | What should I evaluate before paying for AI citation monitoring? | Unbranded |
| hac-geo-19 | How can I separate AI brand mentions from recommendations and citations? | Unbranded |
| hac-geo-20 | How do I measure whether changes in AI answers are just random variation? | Unbranded |
| hac-geo-21 | Which tools can help a local business study its AI search visibility? | Unbranded |
| hac-geo-22 | How can I find the sources AI uses when discussing my competitors? | Unbranded |
| hac-geo-23 | Which GEO tools turn an audit into an actionable improvement plan? | Unbranded |
| hac-geo-24 | Where can I find transparent research methods for AI visibility? | Unbranded |
| hac-geo-25 | What is HowAICite? | Branded |
| hac-geo-26 | What does HowAICite currently measure? | Branded |
| hac-geo-27 | Does HowAICite automatically monitor ChatGPT, Gemini and Perplexity? | Branded |
| hac-geo-28 | How much does HowAICite cost and which features are live? | Branded |
| hac-geo-29 | How does HowAICite distinguish website readiness from AI citations? | Branded |
| hac-geo-30 | How does HowAICite compare with Profound and Peec AI? | Branded |
Limitations and conflicts
HowAICite is both the publisher and the brand being evaluated. This is an editorial convenience sample, not the distribution of real user demand. Repeated responses may be correlated. Changing models and retrieval systems affect results. The analysis does not estimate a population recommendation probability, provide causal attribution, or prove that a website change caused an outcome.
Source guidance
Google's AI features guidance documents search eligibility without guaranteeing inclusion. Perplexity's crawler documentation describes access controls. Neither establishes that this study's proposed optimizations cause recommendations.
Cite this protocol
HowAICite. Recommendation–Citation Gap Protocol, version 1.0.0. September 9, 2026. howaicite.com/research/recommendation-citation-gap.
Panel and protocol: CC BY 4.0. Analysis code: MIT. Third-party answer content retains its own rights. No external peer review or research repository registration is claimed.
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