Most people optimizing for AI search are focused on the wrong metric.

Getting cited by an AI model feels like a win but a citation doesn't mean you're actually influencing the answer. 

And after sampling AI search prompts over 20,000 times, the data makes that painfully clear.

In this episode, Devesh and Benji from Grow and Convert sit down with Bernard from Clearscope to break down what's really driving AI recommendations and what isn't. 

They get into why Gemini searches an average of 5.7 times per query while ChatGPT barely searches at all, why Google appears to be actively suppressing brand citations even when it mentions you, and why the GEO "hacks" everyone's pushing right now (schema, Reddit, you name it) aren't moving the needle.

The bigger takeaway: training data controls 70–80% of what AI recommends. Web search only affects 20–30%. Which means the content strategy that actually works in this new era isn't about producing more it's about going way more specific.

In this episode:

• Why getting cited by AI ≠ influencing the answer

• Gemini vs. ChatGPT: how differently they search (and why it matters for your strategy)

• The brand suppression finding: why mentioning yourself might be hurting your citations

• Why "Content 2.0" is about persona-specific, long-tail content not volume

• How Grow and Convert is evolving Pain Point SEO for the AI search era

Relevant articles:
Invisible prompts: https://www.growandconvert.com/ai/invisible-prompts/
Topic Based GEO: https://www.growandconvert.com/ai/topic-based-geo/