Skip to content

Sentiment Analysis

Sentiment analysis shows how AI models describe your brand, not just whether they mention it. Rankry classifies each mention as positive, neutral, or negative, tracks the balance over time, and surfaces the recurring strengths and concerns in the answers. It appears in the Insights panel within your report.

  • What Sentiment measures
  • Where to find it
  • How to interpret it
  • Best practices and limitations

For each model, Rankry extracts claims about your brand and classifies them. It reports the share of positive, neutral, and negative claims, a summary verdict, and the recurring themes that drive the result.

Sentiment is shown in the Insights panel of your report, alongside the other metrics. Each sentiment finding links to the response it came from.

ReadingMeaning
Mostly positiveMost claims are favorable
MixedRoughly balanced
ConcerningNegative claims outweigh positive ones

A hedged or lukewarm description can cost you a buyer even when you are mentioned, so read Sentiment together with Visibility and Position.

  • Address recurring concerns directly with content, such as a page that answers a common objection.
  • Watch sentiment per model; some models hedge more than others.
  • Use the stored responses to catch and correct factual errors about your brand.

Sentiment is inferred from model answers, which vary and can reflect outdated information. Treat a single negative answer as a signal to investigate, not a verdict.

Why does Sentiment matter if I am already mentioned?

Section titled “Why does Sentiment matter if I am already mentioned?”

A cautious or negative description can steer a buyer away even when you appear. How you are described is part of whether the mention helps you.

Yes. Some models hedge more than others, so the same brand can read as confidently endorsed on one and qualified on another.

Yes. Rankry surfaces recurring strengths and concerns and keeps the source claims behind each.