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Case Study

Jameel Fragrance: Public Audit to Verified Reconciliation to Measured Improvement

A 4-phase case study for a real paying client: a public AI-visibility audit, a verified-tier reconciliation against private GA4/Search Console/PSI data, a scoped 1-month remediation plan, and a measured before/after — published only with the client's explicit permission.

Agentic AIVerified AuditAgent SkillsSEOAEOGEO
Source Code

Overview

This case study follows one real audit engagement — for jameelfragrance.com, a paying Opsome client, published with their explicit permission — through four phases: a public-signal audit, a verified reconciliation against the client’s own private data, a scoped remediation plan, and a measured before/after. Each phase below is filled in only once that phase’s real work is complete. Nothing here is a projection or an estimate presented as a result.

Status as of 19 August 2026: phases 1–4 have not started. Two prerequisite access items for phase 2 are cleared (PSI/CrUX API access, GA4 viewer access via service account) — see the Evidence and access note at the end.


Phase 1 — Public AI-visibility audit

What this will contain: a public-signal-only audit run with ai-visibility-skills — crawler access (robots.txt), sitemap discovery, structured data (JSON-LD), content extractability, and citation readiness — using only what’s visible without any client-granted access. Findings will be dated, sourced, and ranked critical/important/optional, following the same method demonstrated in the missioncontrolhq.ai audit.

Status: not yet run.


Phase 2 — Verified audit (private data reconciliation)

What this will contain: the phase 1 guesses reconciled against jameelfragrance.com’s own private data — GA4 traffic/conversion context, Search Console indexing data, and PageSpeed/CrUX field data — using the verified-audit methodology (described in a companion blog post; the underlying pack is part of a managed offering, not open-sourced). Each reconciliation will state whether the private data confirmed, contradicted, or was simply unable to speak to a given phase 1 finding — private traffic/conversion data will never be used to override a crawlability, indexing, or schema-validity finding, only to reprioritize which findings matter most.

Status: not yet run. Access prerequisites cleared: PSI/CrUX API key generated, restricted, and verified against a live PageSpeed response for jameelfragrance.com; GA4 service-account access confirmed with a successful live 28-day traffic pull.


Phase 3 — 1-month improvement plan

What this will contain: a scoped, dated remediation plan targeting the specific SEO/AEO/GEO gaps confirmed in phase 2, built with the relevant remediation skills (e.g. ai-search-remediation-plan). The plan will have an explicit start date, a fixed one-month window, and named, testable acceptance criteria per item — not a general recommendations list.

Status: not started — depends on phases 1–2 completing first.


Phase 4 — Before/after results

What this will contain: the same checks from phases 1–2, re-run after the one-month remediation window, with dated evidence showing what actually changed — not a repeat of the remediation plan’s intended outcomes.

Status: not started — depends on phase 3 completing and its window elapsing.


Evidence and access

Why This Matters

Most AI-visibility “audits” stop at phase 1 — a public checklist with no way to verify whether the fixes it recommends actually mattered. This case study is structured so that claim can’t be made here without evidence: phase 2 keeps public guesses and private data from contaminating each other, phase 3 commits to a specific plan before results exist, and phase 4 only reports what was actually measured after the fact.