sentiment-intelligence

Multi-dimensional sentiment analysis classifies brand mentions into specific emotion categories like trust, excitement, frustration, and loyalty. This tracks nuanced emotional responses and maps them directly to your product lines.

Brand health scoring generates a longitudinal score by tracking sentiment trends and detecting emerging stories about your brand. It identifies narrative shifts, assesses their risk level, and suggests proactive responses to prevent escalation.

You can analyze emotional responses to a product launch by processing brand mentions through batch analysis. This identifies which specific product features are generating excitement, frustration, or confusion among your audience.

Yes, sentiment analysis maps detected emotions and brand perception directly to individual product lines. This isolates feedback to show exactly which products are driving positive loyalty or negative frustration.

The analysis stores historical data in a BrandHealthSnapshot model to calculate a longitudinal brand health score. Accumulating this historical mention data allows the system to accurately track and trend your brand perception over time.

Narrative shift detection identifies emerging themes and stories about your brand from mention data. It evaluates the risk level of these narratives and suggests targeted responses to address negative perception before it escalates.