Ahrefs platform-gap queue before all-model average
Split AI visibility by platform before averaging the report into one score, because the missing model is often the real repair queue.
Why this can grow a startup
A blended AI visibility number is tidy and often useless. Ahrefs makes the stronger point in its free checker: one brand can appear often in Perplexity while barely showing up in ChatGPT or Google AI Overviews. That difference is operationally valuable. Each platform leans on a slightly different source mix, answer style, and citation habit, so the fix is rarely the same everywhere. A team that watches the split can tell whether it needs stronger owned pages, better third-party proof, or more direct community presence in the places a specific model seems to trust. The average score hides the work. The platform gap list tells you where to start.
Source-backed example
Ahrefs says its AI Visibility Checker reports mentions by platform so teams can see where a brand appears often and where it is missing entirely.
Source-reported evidence
Source: Ahrefs: Free AI Visibility Checker · Browse Ahrefs: Free AI Visibility Checker tactics
Ahrefs says the free report breaks mentions out by platform across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews.
Attributed to the cited source; GrowthDex has not independently verified it. Use this as context, not as a forecast, benchmark, or recommended target.
Evidence scope: claims and metrics are attributed to the linked source; GrowthDex has not independently replicated the reported result. Check the original context and validate fit before applying it. Read the evidence methodology.
When to use it
Use this when AI Search, Analytics, SEO is relevant to platform breakdown, repair queue, ai visibility and you can run a bounded test with a low budget.
When not to use it
Do not use it as a substitute for customer evidence, a clear owner, or a measurable stop condition. Local platform rules and market behavior still need checking.
How to do it
- Choose one target segment and define the exact next action this tactic should prompt.
- Adapt the tactic to AI Search and Analytics, using evidence from Ahrefs: Free AI Visibility Checker as context—not as a promised result.
- Record a baseline for: Qualified search visitors who complete the intended next action. Set a guardrail that would make you pause the test.
- Run a narrow pilot and choose a test window that fits the normal decision or use cycle; do not scale before you have observed the full cycle.
- Compare the signal with its baseline. Scale only if the intended action improves without crossing the guardrail; otherwise revise one variable or stop and record what you learned.
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