Eunice

Co-founder @ prev @google @amazon @nasdaq

[Eunice @okShipIt]

When clicks get rare, the answer itself becomes the shelf. Your brand has to be visible before the buyer opens a tab, not only after they land on your site.

[Eunice @okShipIt]

Read more here: https://t.co/KcoJQBkp8z

[Eunice @okShipIt]

Before I hit publish now, I ask one question.

Would this be expensive for someone else to fake?

If the answer is no, I'm not done yet.

[Eunice @okShipIt]

Pew also found users clicked a link inside the AI summary in only about 1% of visits. So a source link is not a traffic strategy. It is shelf placement with a tiny door underneath.

[Eunice @okShipIt]

Pew found users clicked traditional results in 8% of visits when a Google AI summary appeared, versus 15% without one. The click did not vanish. But the pre-click answer got stronger.

[Eunice @okShipIt]

If the buyer never clicks, the answer has to do more brand work. That means your goal is not only ranking. It is being named, explained correctly and connected to the right buying context.

[Eunice @okShipIt]

SparkToro reported 68.01% of U.S. Google searches ended without a click in early 2026. So the answer page is not only a traffic surface. It is a memory surface.

[Eunice @okShipIt]

A dashboard can hide the problem if it collapses everything into one score. Separate named, cited, ghosted, missing and misdescribed. Different failures need different fixes.

[Eunice @okShipIt]

Search Console can show that a URL appeared in a generative AI feature. It will not fully tell you whether the answer named you, explained you correctly, or made a competitor memorable.

[Eunice @okShipIt]

Google now has Search Console reports for generative AI features like AI Overviews and AI Mode. Good. But appearance is not the whole story. You still need to inspect what buyers actually saw.

[Eunice @okShipIt]

Read more here: https://t.co/KcoJQBkp8z

[Eunice @okShipIt]

I read a post today that could have been published by literally any SaaS company in the world.

Same structure, same advice, same three bullet points.

They just swapped in their product name.

[Eunice @okShipIt]

The prompt-mining habit: collect 25 real buyer questions, group them into definition, comparison, risk, use case and buying prompts, then build from the cluster closest to money.

[Eunice @okShipIt]

A buyer prompt should carry a situation. “AI visibility software” is thin. “Why does ChatGPT recommend my competitor and not us?” is closer to the real question a founder asks.

[Eunice @okShipIt]

Generic prompt lists create generic dashboards. Start from customer language instead. The closer the prompt is to how buyers talk, the more useful the AI visibility audit becomes.

[Eunice @okShipIt]

Lost-deal notes are better than generic prompt lists. They show the questions buyers asked right before they chose someone else. That is where decision-stage content should start.

[Eunice @okShipIt]

Support tickets are prompt mines. They show the questions customers ask after the sale. Those questions often expose the page you should have written before the sale.

[Eunice @okShipIt]

Sales calls reveal buying prompts because buyers say the quiet part out loud: what they doubt, what they compare, what they fear, and what they need to defend internally.

[Eunice @okShipIt]

AirOps’ useful point on prompt mining: your best AI-search prompts are probably not in a keyword tool. They are hiding in sales calls, support tickets, chat logs, Reddit threads and lost-deal notes.

[Eunice @okShipIt]

Read more here: https://t.co/Za0gi4FGga

[Eunice @okShipIt]

There's a question I heard inside my own head at Google that I've never fully shaken.

An engineer on my project needed help I had.

And my first instinct was: if I share this, what's left that's mine?