Sentiment Analysis

Sentiment analysis captures not just whether AI mentions your brand, but how it describes you: warmly, neutrally, or with caution. A hedged or lukewarm description can cost you a buyer even when you are technically recommended.

What Rankry measures

Rankry classifies the sentiment of each mention, tracks it over time per engine, and surfaces the recurring adjectives, strengths highlighted, and concerns flagged across answers. It keeps the source sentences so you can see exactly what drove a shift.

Fields & metrics

FieldWhat it holds
Sentiment labelPositive, neutral, or cautious per mention.
Sentiment trendHow descriptions change over time.
Recurring strengthsWhat models consistently praise.
Recurring concernsCaveats or doubts that keep appearing.
Per-engine sentimentHow tone differs across models.

Example use case

Sentiment analysis flags that two engines repeatedly describe a product as "powerful but with a steep learning curve." The team publishes onboarding content and clearer positioning, and the recurring concern fades from later answers.

Related

FAQ

Sentiment analysis questions

Why does sentiment matter if I am already mentioned?
Because a cautious or hedged description can steer a buyer away even when you appear. How you are described is part of whether the mention actually helps you.
Does sentiment differ by engine?
Yes. Some engines hedge more than others, so the same brand can read as confidently endorsed on one model and qualified on another. Rankry tracks tone per engine.
Can I see what drives the sentiment?
Yes. Rankry surfaces the recurring strengths and concerns and keeps the source sentences, so the label is always backed by the actual wording.