SOPHUS3 / SAMPLE REPORT

Where an overall AI visibility score hides the gaps

An anonymised European automotive brand · UK, Germany and France

Published evidence: 9 March 2026. Sample layout prepared September 2026. Not a live audit or a report about the reader’s brand.

The decision

Which topics deserve investigation before prioritising content and AI discovery work?

Topic	Published finding	How to interpret it
Finance	More than 40%	Mention rate in relevant responses
Electric vehicles	43% behind	Gap to the best-in-class brand
Aftersales	56% behind	Gap to the best-in-class brand

What this tells us

Finance strength does not establish visibility across the ownership journey. EV and aftersales require topic-level investigation. These percentages have different denominators and must not be compared as three equivalent scores.

What a project report should specify

Question set, language, market, model and version, sampling dates, repeated runs, comparator definition and sources cited. The published summary does not disclose all of these; this sample does not invent them.

Next steps

Agree the customer questions and markets that matter.
Measure a consistent sample and examine variation.
Review source coverage and authority behind weaker topics.
Test content improvements and measure again.