Sentiment Scoring

Sentiment scoring adds a qualitative dimension to AI brand monitoring. Brand mention rate tells you how often your brand appears in AI responses. Sentiment scoring tells you what the AI is saying about your brand when it does appear.

A brand might have a high mention rate but poor sentiment — being cited frequently as an expensive or complicated option, for example. Conversely, a brand with a lower mention rate but consistently positive sentiment may have a more favourable AI presence than raw mention counts suggest.

Sentiment analysis in AI contexts uses NLP techniques to classify the framing of brand mentions: positive signals include phrases like 'leading solution', 'highly recommended', 'most popular'; negative signals include 'expensive', 'limited features', 'customer complaints'; neutral signals are factual statements without evaluative language.

Sentiment in AI responses is partly determined by the source content the AI retrieved — if the highest-authority sources discussing your brand use negative framing, the AI is likely to reflect that framing.