Sentiment in Search Party measures the tone and stance of AI responses to the prompts you care about. The goal is to show you how models portray your brand, products, or topics over time.
We track sentiment across three levels:
Prompt level: Sentiment tied to specific queries
Provider level: Sentiment across responses from different LLMs
Workspace level: Overall sentiment trends across all prompts and providers in your workspace
Sentiment is classified into three categories:
Positive
Negative
Neutral
Search Party applies quantitative scoring to assign sentiment, then further categorizes it by intent type, such as:
Recommendation
Comparison
Alternative
Definition
Evaluation
Troubleshooting
Purchase
Other
This dual layer of classification (tone + intent) provides more context than sentiment alone.
Key Benefits
Clear understanding of how AI systems position your brand or competitors
Trends over time show whether perception is improving or declining
Intent classification reveals why a response carries a certain sentiment, not just whether it’s positive or negative
Common Use Cases
Marketing teams: Track if AI responses frame your product as the recommended option versus alternatives
Product teams: Spot negative sentiment tied to troubleshooting or evaluation to identify improvement areas
Sales teams: Monitor purchase-related prompts to see if AI sentiment aligns with your desired positioning
Why It Matters
Traditional search reporting focused on keyword rankings and traffic. In the AI era, sentiment is the proxy for reputation and influence. Understanding sentiment in Search Party lets you see, at scale, how AI systems portray you and whether that perception is moving in your favor.