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Published
22/100

Agent Conversion Optimization launches to track AI agent recommendations

AISeijin Jung introduces Agent Conversion Optimization, a tool that tracks which recommendations agents such as Muse, Instinct, and Dots make, and why. It shows share of recommendations versus competitors, maps agent paths to checkout, and has Helena deploy fixes to improve discoverability.
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Today, we're introducing Agent Conversion Optimization → http://agentconversion.ai

Muse, Instinct, Grok Bot already process $10B+ a year in GMV via agentic commerce. No GEO tool today tracks who they recommend.

So we built it.

Each agent behaves very differently from typical LLMs, so we track them separately, then Helena deploys the fixes.

1/ Daily tracking of who Muse, Instinct, Dots recommend, and why
2/ Share of recommendations vs your competitors
3/ Agent path to check out audit
4/ Fixes deployed by Helena to improve your discoverability

This is hard to do reliably with little bias given how these agents behave, so we're starting with only 100 initial customers.

Demo:

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Seijin Jung · x.comPublished · added here

Original title: Today, we're introducing Agent Conversion Optimization → http://agentconversion.ai