When do GEO consulting results appear in AI answers?

Update cycles vary by AI engine type. Real-time search engines (Perplexity, Copilot, Gemini Live) often reflect changes within 2-4 weeks, while training-data-based engines (default ChatGPT) can take weeks to months. GEO performance must be managed with separate timelines per engine.

Update Cycles by AI Engine

1. Real-time search engines
   - Perplexity: Web-search based. Citations can appear within 2-4 weeks of crawling.
   - Copilot (Microsoft): Bing index based. With IndexNow applied, reflected within days.
   - Gemini Live and Google AI Overviews: 2-4 weeks after Google indexing.
2. Training-data-based engines
   - ChatGPT (default model): Relies on data included at training time, reflected during periodic training updates.
   - Claude (default model): Same. Reflected per training update cycle.
   - Exact cycles are undisclosed, but in practice this runs on a weeks-to-months scale.
3. Hybrid engines
   - ChatGPT Browse and Search: Mix of real-time and training-based responses.
   - For the same question, results can differ by user session.

Timeline After Applying GEO Consulting

• 0-2 weeks: Technical setup, Schema, and llms.txt applied. AI crawlers prompted to revisit.
• 2-4 weeks: First citation cases observed in real-time engines (Perplexity, Copilot, Gemini).
• 4-8 weeks: Citations in Google AI Overviews and Naver (Korea's dominant search engine, ~58% market share) ramp up.
• 2-6 months: Training-based reflection becomes visible in ChatGPT and Claude.
• After 6 months: Compounding effect drives cumulative growth in mention frequency within AI answers.

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How 238lab Monitors

• Because update speed varies by engine, we cross-measure core question sets monthly across engines (internal documentation).
• We report Share of Voice separately by engine.
• We interpret performance using trend lines from multiple measurements rather than a single reading.

Key Considerations

• AI results vary by session, timing, and user, so one-time measurement is inaccurate.
• Training-data-based engines need time to reflect corrections. We communicate this to clients in advance.
• Urgent corrections (responding to misinformation) are requested separately through each engine's official feedback channels.

238lab also offers GEO performance measurement as a standalone service line. The ultimate goal is to embed a system for continuously monitoring AI answer status within the client's own organization.