AI Search Audit: map missing answers, weak signals, and GEO upside
What the audit covers
We review how your brand knowledge is structured, how well language aligns with the entities assistants expect, how consistently public signals appear across surfaces, and where gaps block trustworthy citations. You receive a prioritised backlog—not a vague “content wish list”.
Surfaces and signals we inspect
Official pages (services, FAQ, proof, comparisons, knowledge hubs), entity naming and attribute consistency, and public nodes that models may retrieve when users ask industry questions—all are in scope for the pass/fail style review that precedes execution.
How we spot knowledge gaps
By contrasting common buyer questions, category intents, and your current coverage, we flag topics that are unanswered, thin, or contradictory. Each gap is tagged with urgency and the kind of asset (FAQ, comparison, scenario page, etc.) that closes it fastest.
How we evaluate FAQ, case, and answer templates
FAQs are checked for topical completeness, structure, and indexability; case studies and long-form answers are checked against the actual prompts users (and models) ask. We recommend which formats to expand, merge, or retire.
Brand signal consistency
We look for mismatch between how you describe services, audiences, and proof on-site versus off-site sources, then document fixes so assistants cannot “choose” conflicting facts.
Who should start with an audit
Teams that have not yet centralised brand knowledge, brands planning AI-era programmes, and leadership that wants a defensible read on risk before funding retainers all benefit from running the audit first.
Deliverables after the audit
A structured report: current visibility posture, knowledge and signal gaps, prioritised recommendations (structuring, semantic alignment, signal orchestration), and clear next actions tied to NEOXGEO programmes where relevant.