AI Social Listening Insights Agent

How Cassidy automates social listening using AI

Step 1: Trigger on new mention or scheduled cadence

The Workflow activates when new social data lands—via API stream, webhook from your listening platform, or a scheduled pull—capturing mentions, engagement metrics, and metadata in real time.

Step 2: Enrich with AI classification

Cassidy runs each mention through sentiment, emotion, and aspect-based analysis, tagging topics, entities, and intent. It flags crisis-level content, identifies influencer mentions, and resolves ambiguous brand terms using your taxonomy stored in the Knowledge Base.

Step 3: Detect anomalies and prioritize signals

The Workflow compares incoming volume and sentiment against dynamic baselines, surfacing spikes, virality patterns, and competitive share-of-voice shifts that warrant attention.

Step 4: Route alerts and triage

High-priority signals are routed instantly—Slack for the PR team, Teams for community managers, email for executives—with severity labels, context snippets, and recommended response playbooks.

Step 5: Generate executive-ready insights

Cassidy synthesizes the data into digestible reports: brand health scorecards, aspect driver summaries, and "so what / now what" recommendations ready for leadership review or client delivery.

Step 6: Export and close the loop

Clean datasets, dashboards, and campaign wrap-ups are pushed to your BI tools or client portals, while feedback loops pipe aspect insights to product, creative, or CX teams for action.