Customer Feedback Classifier Agent
Classify and route feedback for faster issue resolution
Description
Challenge:
Customer feedback comes from multiple channels—emails, surveys, chat logs, call transcripts, and social media. Manual analysis is slow, inconsistent, and error-prone, delaying issue resolution, trend identification, and compliance tracking. Organizations struggle to turn unstructured feedback into actionable insights, impacting customer satisfaction, regulatory adherence, and service quality.
How It Works:
The Customer Feedback Classifier Agent uses NLP and machine learning to process structured and unstructured feedback. It detects sentiment (positive, neutral, negative) and intent (complaint, query, suggestion, appreciation) and categorizes feedback accordingly. Urgent or high-risk feedback is flagged and routed to the relevant business unit (claims, policy servicing, sales, or compliance). Outputs include dashboards, reports, and structured data for CX, compliance, and product teams, ensuring audit-ready visibility and faster action.
Benefits:
Automates 90–95% of feedback classification across multiple channels
Reduces average response time to customer grievances by 35–50%
Detects negative sentiment with 98% accuracy
Ensures 100% compliance in routing regulated complaints
Improves first-contact resolution by 30–45%
Provides actionable insights for trend analysis and service improvement
Features
This agent ensures customer feedback is accurately categorized, prioritized, and routed for timely, compliant, and consistent resolution.
Features & Capabilities:
Data Ingestion: Collects feedback from email, survey, chat, call transcripts, and social media
Sentiment Analysis: Detects positive, neutral, and negative sentiment using NLP
Intent Classification: Identifies complaint, query, suggestion, or appreciation
Priority Flagging: Escalates high-risk or urgent feedback (financial, fraud, or regulatory)
Routing: Sends categorized feedback to the correct business unit with priority tagging
Reporting & Dashboards: Generates insights for CX, compliance, and product teams
Audit Logging: Maintains full classification and routing logs for governance
Trend Analysis: Aggregates recurring issues for proactive service improvements
Operating Blueprint
Knowledge Sources:
Customer communications: emails, chat logs', call transcripts
surveys: NPS, CSAT, CES structured datasets
Social Media: mentions, complaints, engagement data
CRM data: customer profiles, past interactions, resolution history
Regulatory Databases: complaint categories, mandatory response Guidelines
Business Rules:
Sentiment Categorization: Classify as Positive, Neutral, Negative
Complaint Prioritization: Escalate complaints tied to financial loss, fraud, or regulatory breaches
Mandatory Routing: Route compliance-related feedback directly to legal/compliance teams
Service Recovery: Immediate acknowledgment for negative feedback from high-value customers
Duplicate Feedback: Consolidate multiple entries from the same customer into one case
Category Mapping: Link policy, claims, or servicing references to relevant line of business
Trend Analysis: Aggregate weekly/monthly for recurring issue detection
Tool Workflow:
Collect feedback from multiple channels
Clean and normalize text; enrich with metadata (customer ID, channel, timestamp)
Apply NLP for sentiment, emotion, and intent extraction
Classify feedback into categories (Complaint, Suggestion, Query, Praise, Compliance Risk)
Route to appropriate business unit with priority tagging
Generate dashboards and periodic reports for CX, compliance, and product teams
Maintain audit logs for governance and regulatory compliance
Badges
Classification
Capabilities
