Feature Specification: Analytics & Feedback

1. Overview & Vision

Analytics & Feedback provides the data-driven insights necessary to improve the AI Assistant's performance over time. By capturing user ratings and tracking query patterns, it identifies knowledge base gaps and ensures that the AI is delivering tangible value to the organization.

2. Personas & Stakeholders

Persona	Goal
Member	Provide feedback on AI accuracy to improve future responses.
Knowledge Admin	Identify "No Answer Found" queries to prioritize new data sources.
Executive	Measure the ROI of the AI Assistant (e.g., time saved vs. query cost).

3. User Stories

• As a user, I want to click a "Thumbs Down" icon so I can report a hallucination or incorrect answer.
• As an admin, I want to see a chart of the most frequently asked questions this month.
• As an admin, I want to know which documents are being cited the most by the AI.

4. Functional Requirements (FR)

• REQ-ANA-001: Message-level rating system (Helpful/Unhelpful).
• REQ-ANA-002: Organization-wide usage dashboard (Queries, Active Sessions).
• REQ-ANA-003: Feedback collection modal for "Unhelpful" ratings.
• REQ-ANA-004: Automated tracking of "No Relevant Context Found" events.

5. Non-Functional Requirements (NFR)

• Anonymization: Individual user IDs MUST be anonymized in aggregate admin views (v1.1).
• Latence: Analytics dashboard load time < 1 second.

6. Business Logic & Rules

• Aggregation: Data is grouped by orgId and can be filtered by Date Range (Day, Week, Month).
• Sentiment Scoring: System calculates a "Helpfulness Score" (Helpful / Total Ratings) for each source.
• Cost Calculation: (Optional) Estimates token cost based on model-specific pricing.

7. User Interface (UI/UX)

• Rating Widgets: Simple 👍/👎 icons below every AI message.
• Feedback Dialog: Text area for "How can we improve this answer?".
• Admin Dashboard: Visual grid with Recharts (Line charts for trends, Bar charts for top sources).

8. Information Architecture

• "Analytics" tab in the AI Assistant Admin portal.
• Feedback widgets integrated into the Chat window.

9. Data Model & Persistence

• Table: message_feedback.
• Fields: messageId, isHelpful, comment, orgId.

10. API & Service Layer

• POST /messages/:id/feedback
• GET /analytics/summary (Admin only).

11. Integration Patterns

• Recharts: For frontend data visualization.
• Worker: (Future) Periodic aggregation of raw logs into summary tables.

12. Security & Permissions

• RBAC: ai_assistant:view_analytics required for dashboard access.
• Privacy: Individual conversation content is hidden from admins by default.

13. Error Handling & Resilience

• Submission Error: Graceful retry if feedback submission fails due to network.
• Data Gaps: Inform admins if insufficient data is available for a selected time range.

14. Performance & Scalability

• Optimized queries using aggregate indexes.
• Support for organizations with 100,000+ monthly queries.

15. Globalization & i18n

• Support for multi-language feedback comments.

16. Accessibility (a11y)

• Aria-pressed states for rating buttons.
• Accessible charts with hidden data tables for screen readers.

17. Observability & Analytics

• Tracking of "Feedback Response Rate" (Ratings / Total Messages).

18. Testing & Quality

• Integration tests for feedback persistence.
• Validation of data aggregation logic across different timezones.

19. Constraints & Assumptions

• Assumes that users are willing to provide voluntary feedback.

20. Future Enhancements

• Proactive suggestions based on frequent queries.
• "Golden Answer" management (Manual override for specific questions).
• ROI reports (Estimated hours saved).