AI Perception Score Tracking

Most AI brand tools count mentions and label sentiment. That's the marketing layer. But buyers don't stop at the first mention, they probe. They ask 'is this brand right for a 200-person company?', 'what are its weaknesses?', 'who's better for enterprise?'. The model's answers to those probing questions are what actually shapes the deal.

AI Perception Score exists to measure that probing layer. It is the difference between 'we are mentioned in AI' and 'we know what AI tells a serious buyer when they push'.

A AI Perception Score run uses a 40+ question battery covering: ideal customer profile, target company size, pricing perception, top strengths, top weaknesses, closest competitors, recommended use cases, recommended alternatives, category leadership claim, and defensibility narrative.

Each question is asked to all 8 models. Each answer is scored on accuracy (does it match your reality?), positioning alignment (does it match your intended positioning?), and narrative coherence (is the model telling a consistent story across questions?).

Almost every brand we run AI Perception Score on has at least one major surprise, a weakness AI cites that the team didn't know was being cited, an ideal-customer mismatch, or a competitor named as 'the obvious choice' for the brand's actual core segment.

These are the items that show up in real buyer conversations and have, until now, been invisible to the brand team. AI Perception Score makes them measurable, traceable to sources, and trackable over time.