This framework structures how GEO audit findings are scored, prioritised and turned into action. It is the decision layer on top of the raw audit checklist.
Dimensions
The framework scores five dimensions on a 0-100 scale:
- Crawlability — can AI crawlers discover, access and parse your content?
- Entity clarity — how unambiguously do engines recognise your brand entity?
- Content extractability — how quotable and answer-first is your content?
- Authority — how credible is the evidence web around your brand?
- Measurement — how reliably can you observe your own visibility?
Scoring rules
Each dimension is scored from verifiable evidence: a dimension with unverifiable evidence scores as unknown and is flagged, never guessed. Overall readiness is not an average — the framework treats the five dimensions as dependencies: crawlability gates everything, entity clarity gates content impact, authority gates citation depth, and measurement gates learning.
Priority matrix
Findings are placed on an impact-vs-effort matrix:
- Quick wins (high impact, low effort): robots.txt corrections, schema fixes, answer-first restructuring of priority pages.
- Strategic investments (high impact, high effort): entity governance, original research, content programmes.
- Housekeeping (low impact, low effort): sitemap hygiene, consistency fixes.
- Deprioritised (low impact, high effort): anything not feeding the prompt portfolio.
Sequencing rule
Work streams are ordered by dependency, not preference: technical foundations first (crawlability, schema), then content, then authority. This mirrors the implementation playbook and the strategy service.
Output
The framework’s output is a single-page scorecard with a sequenced roadmap — the artefact an AI visibility audit delivers. Re-run the framework quarterly to show movement; the scorecard is the management layer of GEO reporting.