Customer Feedback Collector Agent
Captures and analyzes post-interaction feedback to drive service excellence
Description
Challenge Insurers often miss key customer sentiment signals due to delayed, unstructured, or inconsistent feedback collection. Without timely insights, minor dissatisfaction can escalate into grievances, churn, or reputational damage. The Customer Feedback Collector Agent solves this by automatically gathering feedback after critical customer touchpoints—like onboarding or claims—classifying responses through NLP, and flagging high-risk inputs for action. It creates a closed feedback loop that empowers continuous experience improvement across business functions.
How It Works The agent activates after defined lifecycle events—such as claim settlements, policy issuance, or service escalations. It sends personalized feedback prompts via the customer’s preferred channel (email, SMS, WhatsApp, or app push). Once responses are collected—whether structured ratings or open-text—the agent applies sentiment analysis and NLP-driven classification to detect tone, urgency, and topic. Urgent feedback is routed to service desks, while aggregate insights are fed into dashboards for CX, compliance, and operations teams to act upon. Non-respondents receive a single reminder, and opt-outs are automatically honored.
Benefits
Increases feedback response rates by 30–45% via personalized multichannel prompts
Delivers 90–95% sentiment classification accuracy using NLP models
Cuts negative feedback resolution time by up to 50%
Ensures 100% coverage of post-claim and onboarding experience feedback
Reduces repeat grievances by 20–25% through early detection
Provides actionable insights that power measurable service improvements
Enhances trust by showing customers their feedback is acknowledged and acted on
Features
The Customer Feedback Collector enables always-on voice-of-customer intelligence. It combines smart survey delivery, AI-powered classification, and escalation routing to convert customer sentiment into actionable inputs—while ensuring regulatory compliance and seamless integration with existing systems.
Features & Capabilities:
Event-Triggered Outreach: Automatically initiates feedback collection post key events (e.g., claim payout)
Multichannel Delivery Engine: Sends surveys via SMS, WhatsApp, email, or app notifications
Sentiment & Urgency Analyzer: Uses NLP to classify tone, urgency, and content type (complaint, praise, suggestion)
Custom Survey Templates: Tailors questions based on context—onboarding, claims, support interactions
Escalation & Routing Engine: Flags critical responses for immediate handling via ticketing or CRM systems
Feedback Reminder Automation: Sends one-time nudge if initial survey is ignored
Opt-Out Compliance: Suppresses feedback prompts for users with communication restrictions
Experience Dashboard Integration: Pushes insights to analytics teams for trend monitoring and service planning
Feedback Audit Trail: Maintains structured records of all interactions and classifications
Continuous Learning Loop: Incorporates new keywords, patterns, and edge cases to refine NLP accuracy.
Eligibility Logic
Decision Logic Flow:
This agent applies feedback logic to ensure surveys are timely, relevant, and actionable. By combining lifecycle event tracking with customer preferences and intelligent response handling, it ensures feedback flows are precise and compliant.
Key Logic Pathways Followed:
Event Trigger Rule → Send feedback only after specific milestones (e.g., policy issue, claim closure).
Channel Preference Rule → Choose WhatsApp, SMS, or email based on recorded communication preferences.
Response Timeout Rule → If no response in 3 days, send one-time follow-up and then close feedback loop.
Urgency Detection Rule → Negative sentiment or flagged keywords (e.g., “fraud,” “cheated”) trigger priority escalation.
Survey Routing Rule → Assign survey type based on event (claim vs onboarding) for better relevance.
Opt-Out Compliance Rule → Do not send surveys to customers who’ve opted out of marketing or feedback messages.
Response Categorization Rule → Auto-classify feedback as compliment, complaint, or suggestion using NLP tagging.
