GEO Six-Step Closed-Loop Optimizer

Problem addressed

When an enterprise brand is absent from AI answer engines such as ChatGPT, Doubao, or Kimi, or competitors are cited instead, traditional SEO rankings often do not explain the customer acquisition path. geo-six-step-optimizer treats AI visibility as an operational workflow: it checks whether AI systems understand, cite, and recommend the brand, then converts that finding into a repeatable optimization loop.

How it works

The skill organizes the work into six steps:
- Diagnose: review AI occurrence rate, recommendation rate, share of voice, and intent answer rate, then audit official sites, encyclopedias, social profiles, and third-party credibility.
- Keywords: build a four-layer keyword library across brand, industry, intent, and long-tail terms, with search intent, difficulty, and conversion value annotated.
- Content: produce AI-parseable assets such as FAQs, case studies, and white papers using H1-H6 structure, sourced facts, complete topics, and timely updates.
- Deploy: prioritize official-site Schema, encyclopedias, and high-authority platforms to create multiple citable sources.
- Monitor and iterate: recheck AI citations, competitor visibility, and customer source data, then feed ignored or outdated content into the next optimization cycle.

Limits and cautions

It fits teams running a long-term AI search visibility program rather than one-off campaigns. The provided guidance recommends at least six months of execution, data-backed decisions at each step, and ad-law compliance. The objective remains precise: help AI recommend the enterprise accurately.