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In practice
The analysis is a matrix built from measurement: run the prompt set (the buyer’s real questions, clustered by intent), record for each answer which brands are named, which pages are cited, and which attributes each brand is described with — then read the matrix for the empty cells where competitors sit and you don’t.
The gaps come in types, each with its own fix: intent gaps (absent from “best for use case” prompts while present on “what is” prompts — the comparison layer needs placement work), attribute gaps (present but misdescribed — positioned as the wrong thing, missing the specification buyers filter on — the entity and description work), citation gaps (named but never sourced — the citability work on your own pages), and topic gaps (whole subtopics where the category’s answers exist without you — the content and placement map).
The matrix converts directly into the programme: each gap cell points at a page to publish, a page to place on, or a description to correct — the surgical version of “improve AI visibility”, with priorities set by the buyer’s journey (comparison-intent gaps outrank definitional ones for revenue). The maintenance is the measurement itself: the matrix re-runs with the monitoring cadence, gaps close visibly or don’t, and the honest reporting layer shows movement per cell rather than a mood. The discipline it prevents: the shotgun of “more mentions everywhere”, which volume-optimises the wrong cells and leaves the buying moments unowned.
See also: Prompt sets, AI search visibility monitoring, Mention-to-citation workflows.
Checklist: Brand Mentions Campaign.
Related service: Brand mentions.
