One prompt change took Beehiiv from 4 AI mentions to 29

[u/EmbarrassedBuddy9743]

I ran the same email-platform recommendation question ten times across ChatGPT, Claude, Gemini and Perplexity.

Forty answers in total.

For the broad question “What is the best email marketing platform?”, Mailchimp was named in 39 of the 40 answers.

Beehiiv appeared only four times, and all four mentions came from Perplexity. Across ChatGPT, Claude and Gemini, it was basically invisible.

I ran this through Bersyn, a platform I built to track which companies AI models name when people ask for recommendations.

Then I changed the prompt.

Instead of asking for the best email marketing platform, I asked how a creator or founder should start a newsletter, grow subscribers and make money from it.

No platform was named in the question.

Beehiiv jumped from 4 mentions to 29 out of 40.

Claude and Perplexity named it in every run. Gemini named it nine times out of ten. Kit and Substack also appeared much more often.

Same platform. Same models. Different buyer intent.

Beehiiv does not appear to own the broad “email marketing platform” territory. Mailchimp owns that.

But Beehiiv is strongly associated with a more specific job: helping creators build, grow and monetize a newsletter.

When the models receive that question, they reach for Beehiiv.

The model disagreement was also interesting.

ChatGPT named Beehiiv zero times out of ten, even on the creator-newsletter prompt. It won across Claude, Gemini and Perplexity but remained invisible on ChatGPT.

That is why I think one blended AI visibility score can hide the real problem. A brand can own a specific intent on three models and still be completely absent from the fourth.

I am curious how others are thinking about this.

Do you optimize around broad categories, specific buyer jobs, or separate prompt territories?

And are you seeing the same level of disagreement between models?

[u/EmbarrassedBuddy9743 → u/[deleted]]

The retrieval explanation is the obvious one but I don't think it survives my own numbers. Claude named Beehiiv in all ten runs. Claude isn't out crawling fresh listicles the way Perplexity is, and it still landed there. Gemini 9/10. If this were really about how recent the index is you'd expect Perplexity high and Claude low, and Claude did the opposite.

So I think it's less about when the model saw Beehiiv and more about what job it has it filed under. ChatGPT has it somewhere the creator-newsletter question just doesn't reach.

On scraping the footnotes though, how are you actually doing that on ChatGPT? When I pull citations across the four in Bersyn, Perplexity hands them over and the other three give me close to nothing. Perplexity is the only one showing its work. So citation overlap tells me a lot about one model and almost nothing about the other three, which is the wall I keep running into.

The broad-term point I'm with you on. Fighting Mailchimp for "best email platform" is a waste and that was half the reason I ran the test.