This example uses validated measurements from our own preserved self-test to demonstrate the evidence structure, reviewed findings and decision boundaries of the A$249 Pro Audit. The exact question taxonomy, provider configuration, source correlations, weighting and intervention sequence remain private.
A Pro Audit preserves the starting point and later evidence separately so movement is not created by overwriting the baseline.
The public example intentionally shows only the evidence necessary to understand the conclusion. Exact prompts, source-level correlations and private diagnostic rules are withheld.
The operator review separates the observation from the interpretation so a customer can see what is known and what remains a hypothesis.
Observed: In the later clean comparison, OpenAI surfaced Am I Recommended? in 4 of 5 Discovery & shortlist questions, with recorded positions from #1 to #4.
Reviewed interpretation: The business became repeatedly discoverable in one buyer context. That movement is measurable, but no single public change is credited as the cause.
Observed: The clean comparison recorded 4/40 OpenAI appearances overall and 0/40 Gemini appearances.
Reviewed interpretation: Broad discovery improved while other buyer contexts and the second provider did not automatically move with it. The next plan therefore stays targeted rather than assuming one fix solves every visibility gap.
Observed: OpenAI produced measurable recommendation appearances while Gemini remained at 0/40 in the preserved comparison.
Reviewed interpretation: Provider disagreement is kept visible instead of being hidden behind one blended score. A Pro review treats that disagreement as evidence to investigate, not as proof of a hidden penalty.
Measurement record, provider-by-provider outcomes, recurring alternatives, reviewed public-evidence gaps, strengths worth protecting and a prioritised plan for what deserves attention next.
Exact question taxonomy, provider configuration, source-correlation rules, internal weighting, intervention sequencing and accumulated research relationships are not included in the public deliverable.
We keep dated measurements separate so later movement can be compared rather than remembered.
A surfaced business, missed question or public-evidence difference is observable. The hidden reason a model chose it is not.
The reviewed plan focuses attention on the strongest measured gaps rather than creating a generic marketing checklist.
A later comparison can measure movement, but it still cannot prove that one intervention caused every change.
Prefer more context first? Read the public self-audit or review the full Pro scope.