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GEO engine-specific query panels before average AI score

Track ChatGPT, Perplexity, Gemini, and other engines separately before you flatten them into one comforting visibility number.

rare tactic low budget AI visibility, Analytics, SEO Stages: engine-specific tracking, query panels, visibility measurement, prompt variance, reporting discipline

Why this can grow a startup

A blended AI score can hide the thing that matters. The 2025 GEO paper says AI-search services differ significantly in domain diversity, freshness, cross-language stability, and sensitivity to phrasing. That means the product can look healthy in one engine and invisible in another while the average report stays polite. The smarter move is to keep a separate query panel for each engine, compare the exact prompts that matter to the market, and only aggregate after the team has seen the differences. That keeps content changes tied to a real retrieval environment instead of to a dashboard that irons out the whole problem.

Ian's take

From scaling consumer platforms across MENA and Southeast Asia, my default is to distrust growth work that only looks good in a slide. For SEO and AI search, I care less about clever keyword tricks and more about clarity. A reader, crawler, or AI search tool should quickly understand who this is for, why it works, what proof backs it, and what page deserves to be cited. I would run it small enough to learn quickly, then only scale the parts that real users repeat, save, reply to, or buy from. For this tactic, I would watch one clear growth signal before putting more time or budget behind it.

Action plan

  1. Define one narrow startup segment where geo engine-specific query panels before average ai score can create a measurable lift.
  2. Turn the tactic into one offer, page, campaign, or workflow for the AI visibility and Analytics channel.
  3. Use the evidence from arxiv.org to set the first version of the message, format, and audience.
  4. Launch a small test for 7 to 14 days with one success metric: one measurable growth signal.
  5. Review the result, keep the winning message, remove weak variants, and turn the learning into a repeatable growth playbook.

Source-backed example

The GEO paper compared AI-search behavior across services and found meaningful differences in domain diversity, freshness, cross-language stability, and phrasing sensitivity rather than one universal citation pattern.

Source: arXiv: Generative Engine Optimization: How to Dominate AI Search (arxiv.org)

GrowthDex source hub: arXiv: Generative Engine Optimization: How to Dominate AI Search

Last checked: 2026-06-10T04:09:52.000Z

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Ian Goh has helped grow consumer platforms across Southeast Asia, India, and MENA. His work includes scaling Tiki to 100M+ users, doubling BIGO's MENA revenue in 7 months, and increasing OYO's direct booking share across 6 Southeast Asian markets.

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If you want someone to pressure-test this against your real market, Ian works with founders on growth, market entry, and operator-led distribution.

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