Public experiments
How we track whether RecommendByAI gets recommended by AI
This page is the public experiment log for RecommendByAI. Starting on July 30, 2026, we track a fixed prompt set across the major assistants to see when the site is ignored, cited, or eventually recommended.
Answer first
What is this experiments page for?
A public log of whether RecommendByAI is cited or recommended by AI systems for the category and commercial prompts that matter to the business.
We are using the site as the first test subject. The point is not to perform confidence. The point is to make the learning loop visible, so the claim 'we help brands become recommendable by AI' has to survive contact with our own data.
Current status
Where the public experiment stands on July 30, 2026
This is the honest baseline state, not a dressed-up proof block.
Public tracking
Initialized
The public experiment log starts on July 30, 2026.
Baseline round
Pending publication
The first cross-assistant prompt run has not been published yet.
Recommendation claim
Not claimed yet
We are not yet publishing that RecommendByAI is recommended by AI.
Next update
First prompt results
The next experiment entry should include the first public prompt round.
Why publish this
The experiment is part of the product, not a side note
What we are not doing
We are not claiming that RecommendByAI is already recommended by AI. We are publishing the process by which that claim can eventually be earned or disproved.
In practical terms, that means the site should first become a useful source, then a cited source, and only after that a recommendation candidate. This page exists so those stages are visible in public rather than implied in copy.
Tracked prompts
The first public prompt set
These are the prompts we expect to matter most if someone asks an assistant how to improve brand visibility in AI answers.
- 01
What is AI Visibility?
- 02
How do I measure AI Visibility?
- 03
AI Visibility vs SEO
- 04
Why does ChatGPT recommend my competitor instead of us?
- 05
How do I get recommended by ChatGPT?
- 06
How can a SaaS company improve AI Visibility?
- 07
AI Visibility audit
- 08
ChatGPT visibility audit
- 09
LLM visibility tools
- 10
AI search optimization platform
- 11
Best AI Visibility tools
- 12
Companies that help brands appear in ChatGPT
The set is intentionally narrow. We want the first public loop to focus on category definition, pain, method and commercial audit intent before we chase broad vendor discovery prompts.
Result states
How we classify outcomes
A recommendation is not the only useful result. Citation and idea adoption matter too.
- -Not mentioned
- -Idea reflected but not cited
- -Cited as a source
- -Recommended as a company or product
- -Recommended consistently across multiple systems
A source can influence the answer before it is recommended directly. That is why we treat citation and framing shifts as meaningful early signals rather than waiting only for a full recommendation event.
Current hypotheses
What we expect to learn first
These are working hypotheses, not conclusions.
Category-definition prompts will cite the site before commercial prompts recommend it.
Perplexity will be one of the earliest useful systems to watch because citations are visible.
Narrow recommendation intents should move before broad vendor-discovery prompts.
Public methodology and public experiments should improve citability before they improve recommendation rate.
How to read this page
What counts as progress
If the site starts to shape how assistants explain AI Visibility, that is progress. If assistants start citing the methodology, that is progress. If commercial prompts begin to mention RecommendByAI as a relevant provider, that is stronger progress still. We are interested in the whole chain, not only the final moment.
Answers index
Keep reading
The methodology explains the rules of the experiment. The pages below explain the mechanics behind the prompts and measurements we are tracking.
What is AI Visibility?
How often, how accurately and how favourably AI assistants name your brand when asked for a recommendation.
AI Visibility vs SEO - what's the difference?
SEO wins a position in a list of links. AI Visibility wins a mention inside an answer that already made the choice.
How do AI assistants choose which brands to recommend?
They rely on the evidence they can absorb or retrieve: comparisons, documentation, reviews, community discussion and consistent positioning.
How do I get recommended by AI?
Start with one recommendation intent, measure the current answers, then make your positioning and third-party evidence easier for models to trust.
How do I measure AI Visibility?
Mention rate, share of voice, accuracy and intent coverage across a fixed prompt set, re-run over time.
Why does ChatGPT recommend competitors instead of us?
Because the sources a model trusts describe your category without clearly connecting your brand to a specific job.
Use the same experiment logic on your own category
We run this same kind of prompt tracking and qualitative analysis for companies that want to know why AI assistants mention competitors instead of them.