FeedbackLoop AI — Customer feedback analysis platform
AI deployment blueprint for Customer feedback analysis platform. Automates feedback routing using HubSpot, Slack, Supabase, Claude.
AI Readiness Score
Structured customer data in HubSpot, feedback likely stored in Supabase, existing sentiment analysis process
Technical team with existing Claude usage, but may need dedicated implementation time
Budget range supports moderate AI implementation with room for scaling
Clear workflow patterns for feedback routing, existing API integrations, well-defined pain points
3-4 month timeline realistic for phased implementation of feedback routing system
Good API coverage with HubSpot, Slack, Supabase. May need webhook setup for real-time processing
How This System Works
Architecture
Event-driven feedback processing system that captures feedback from multiple sources, automatically classifies and routes it, monitors sentiment trends in real-time, and provides product insights
Data Flow
Feedback flows from HubSpot tickets, Slack mentions, and direct submissions into the Feedback Classifier which enriches and routes it appropriately. The Sentiment Monitor continuously analyzes trends, while the Roadmap Connector aggregates insights for product planning.
Implementation Phases
Establish automated feedback classification and routing
Add continuous sentiment tracking and alerting
Connect feedback insights to product planning
Prerequisites
- -HubSpot webhook configuration
- -Slack bot setup with appropriate permissions
- -Supabase database schema for feedback storage
Assumptions
- -Feedback volume supports meaningful trend analysis
- -Team will actively use routed feedback in Slack
- -Customer tier information available in HubSpot for impact analysis
Recommended Agents (3)
How It Works
- 1Detect new feedback entry
Monitor HubSpot tickets, Slack mentions with #feedback, Supabase feedback table
Webhook listener - 2Extract and enrich feedback context
Pull customer details, account tier, interaction history
HubSpot API - 3Classify feedback using Claude
Analyze content for category, priority, sentiment, and routing
Claude API - 4Route to appropriate channels
Post to #product-feedback, #engineering, or #customer-success based on classification
Slack API - 5Update feedback database
Store classification results, link to customer record, track routing
Supabase API
Data Flow
Inputs
- HubSpot — Support tickets and customer communications(Ticket JSON)
- Slack — Feedback mentions in channels(Message JSON)
- Supabase — Direct feedback submissions(Database record)
Outputs
- Slack — Routed feedback with classification(Channel message)
- Supabase — Enriched feedback record(Database update)
Prerequisites
- -Webhook endpoints configured for HubSpot and Slack
- -Supabase triggers for new feedback entries
- -Slack bot with posting permissions
Error Handling
Retry with exponential backoff, fallback to basic keyword classification
Store in pending queue, alert admin, retry in 5 minutes
Integrations
| Source | Target | Data Flow | Method | Complexity |
|---|---|---|---|---|
| HubSpot | Feedback Classifier | Ticket creation triggers, customer data lookup | webhook + api | moderate |
| Slack | All Agents | Feedback mentions inbound, classified feedback and reports outbound | bot_api | low |
| Supabase | All Agents | Bidirectional - feedback storage, classification updates, analytics | rest_api | low |
Schedule
0 */1 * * *0 9 * * *0 9 * * 1Recommended Models
| Task | Recommended | Alternatives | Est. Cost | Why |
|---|---|---|---|---|
| Feedback classification and sentiment analysis | Claude Sonnet 3.5 | GPT-4Claude Haiku for cost optimization | $200/month at expected volume | Strong performance on nuanced text analysis, good API reliability for production use |
| Product insights and trend analysis | Claude Sonnet 3.5 | GPT-4 for alternative perspective | $100/month for weekly reports | Excellent at synthesizing patterns from multiple data sources and generating actionable insights |
Impact
What Changes
Quality Gains
- ✓Faster response to customer sentiment changes
- ✓Data-driven product roadmap decisions
- ✓Reduced feedback falling through cracks
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