A user on Reddit left a comment after checking their score:
"I'd like to know more about how the score is actually calculated. I see in the FAQs you've briefly outlined some metrics used, but I'd like a more thorough explanation. Perhaps worth doing a blog post?"
Fair ask. Here's the full answer.
Why scoring AI visibility is different from Google rankings
Google rankings are relatively transparent. You can check your position for a keyword, track backlinks, measure page speed. The rules are documented.
AI visibility doesn't work that way.
When someone asks ChatGPT "what's the best Notion template for budgeting?" — there's no ranked list, no position 1 through 10. There's just: does your product get mentioned, or not?
We had to build a scoring system that reflects this reality. The result is a 0–100 score built from five dimensions, each measuring a different layer of how AI systems perceive and surface your product.
The 5 dimensions we measure
How many independent third-party domains mention your product. This is the baseline — if AI sees no external mentions, nothing else matters.
Quality matters as much as quantity. Mentions on Tier-1 sites (TechCrunch, G2, ProductHunt) carry far more weight than unknown blogs. This is where trust compounds.
Does your product appear in "best of" or "top recommended" lists? Does it earn explicit recommendation language from reviewers? Being recommended is very different from just being known.
Reviews on Product Hunt, Reddit, G2 act as trust signals. More credible community mentions means higher AI confidence in recommending you. "Free Gumroad alternatives" threads — does your name appear?
"X vs Y" and "alternatives to X" content signals market relevance. Being compared means AI treats your product as a legitimate category player — not a footnote.
What the scores actually look like
In the Reddit thread where we launched, three real scores told three very different stories.
The gap nobody talks about
The most important insight from building this tool:
Being known by AI and being recommended by AI are not the same thing.
Most creators assume that if they exist online, AI will find them and surface them. That's partially true — AI does index a lot. But AI doesn't recommend everything it knows. It recommends what it has seen described, compared, and discussed across multiple independent sources.
The bridge between those two states is external signal: other sources mentioning your product by name, in the context of recommendations. A directory listing. A Reddit thread. A comparison article. An honest review somewhere credible.
One or two of those can move a 40 to a 60. A handful of them, consistently, is how you reach 80+.
How scores change over time
AI systems update their training data. A product that scores 0 today can score 40 in a month if it gets listed in the right places. A product at 40 can reach 80 if it starts showing up in community discussions and comparison contexts.
This is why we built the dashboard — check once, make changes, come back and see if the number moved.
One of the users in our Reddit thread put it well: "I'll come back in a few weeks to try again and see if the score improves." That's exactly the right approach.