Where BRAND is strong—
and what it should do next.
A shorter way into a detailed analysis. Start with the findings, move into practical actions, and open the evidence only when you need it.
All client, sub-category, Theme, product, competitor, athlete, program, and source names have been anonymized. The experience demonstrates the research and decision framework without revealing the original client.
The executive story
BRAND is already strong in several parts of the market. The biggest gaps are specific: Sub-Category 2 visibility, Sub-Category 3 Theme 2 preference, and Sub-Category 4 Themes 2 and 4.
Where the issues differ
BRAND does not have one generic “AI visibility” problem. The right response changes by sub-category and by strategic pillar.
By sub-category
Switch between all-up and 18–24 results, compare Theme-level performance, see the attributes AI associates with BRAND, and open the relevant actions.
By strategic pillar
Use this view to answer the same question across Sub-Category 1, Sub-Category 2, Sub-Category 3, and Sub-Category 4 without reading four separate sections.
Action portfolio
Every action states what BRAND would actually create, the first practical step, the evidence required before scaling, and how progress should be measured.
Now, test, decide
Some actions are low-regret information fixes. Others are pilots. Product and portfolio commitments should wait for stronger evidence.
Decision tools
These tools turn the recommendations into usable templates. Product and competitor names remain anonymized in this proposal version.
Method and sources
The simulator remains the primary, repeatable evidence. External sources are shown as anonymized source numbers in this proposal version and are intentionally not linked.
How to read the study
BRAND was the first brand recommended in the AI response.
BRAND appeared anywhere in the AI response.
Attributes the AI explicitly connected to BRAND in the relevant Sub-Category, Theme, or Scenario.
Each Scenario contains four model responses, so Scenario percentages move in 25-point steps and should be used diagnostically.
AI discovery; known but not chosen first; real product or operating issue; or mixed / not enough evidence.