Automated quality management and conversation analysis.
Overview
Quality AI enables you to:
- Evaluate 100% of customer interactions.
- Identify coaching opportunities automatically.
- Monitor compliance and adherence.
- Drive continuous improvement with data.
How It Works
┌───────────────────────────────────────────────────────┐
│ Customer Interactions │
│ (Voice, Chat) │
└───────────────────────────┬───────────────────────────┘
│ ▼ │
┌───────────────────────────────────────────────────────┐
│ Quality AI Engine │
│ │
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Speech/ │ │ Evaluation │ │ Insight │ │
│ │ Text │ │ Scoring │ │ Generation │ │
│ │ Analysis │ │ │ │ │ │
│ └─────────────┘ └─────────────┘ └─────────────┘ │
└───────────────────────────┬───────────────────────────┘
│ ┌──────────────────┼──────────────────┐ │
│ ▼ ▼ ▼ │
┌────────────────┐ ┌───────────────┐ ┌────────────────┐
│ Auto-Scores │ │ Coaching │ │ Compliance │
│ & Evaluations │ │ Assignments │ │ Monitoring │
└────────────────┘ └───────────────┘ └────────────────┘
Evaluation Criteria
Standard Criteria
Pre-built evaluation criteria available out of the box:
| Criteria | Description |
|---|
| Greeting | Proper introduction and identification |
| Empathy | Acknowledging customer emotions |
| Issue understanding | Correctly identifying the problem |
| Resolution | Providing an accurate solution |
| Closing | Proper wrap-up and next steps |
| Compliance | Following required disclosures |
Form: Customer Service Standard
Criteria:
- greeting (10%)
- empathy (15%)
- issue_understanding (20%)
- resolution (30%)
- product_knowledge (15%)
- closing (10%)
Pass threshold: 80%
Apply to:
- queue: support
- channel: all
Auto-Scoring
How It Works
AI evaluates interactions in four steps:
- Speech/text analysis — Transcribe and analyze the conversation.
- Criteria matching — Map conversation content to evaluation criteria.
- Scoring — Assign scores based on evidence found.
- Confidence flagging — Flag low-confidence scores for human review.
Conversation Mining
Topic Analysis
Automatically identify and track conversation topics:
| Analysis | Description |
|---|
| Topic clustering | Group conversations by theme |
| Sentiment by topic | Track sentiment for each topic |
| Volume tracking | Monitor topic frequency |
Taxonomy Builder
Create Taxonomies
Define and manage a structured topic hierarchy for consistent, business-relevant conversation analysis:
Taxonomy: Customer Interaction Analysis
├── Communication (L1 - Strategic)
│ ├── Call Handling (L2 - Product/Service Category)
│ │ ├── Clarity (L3 - Customer Contact Reason)
│ │ ├── Tone (L3 - Customer Contact Reason)
│ │ └── Active Listening (L3 - Customer Contact Reason)
├── Knowledge (L1 - Strategic)
│ ├── Product (L2 - Product/Service Category)
│ │ ├── Features (L3 - Customer Contact Reason)
│ │ └── Pricing (L3 - Customer Contact Reason)
├── Problem Solving (L1 - Strategic)
│ ├── Issue Diagnosis (L2 - Product/Service Category)
│ │ ├── Solution Accuracy (L3 - Customer Contact Reason)
│ │ └── Efficiency (L3 - Customer Contact Reason)
└── Compliance (L1 - Strategic)
├── Legal & Regulatory (L2 - Product/Service Category)
│ ├── Disclosures (L3 - Customer Contact Reason)
│ └── Data Handling (L3 - Customer Contact Reason)
Analytics
Reports
| View | Description |
|---|
| My Dashboard (Agent) | Assigned evaluations, sentiment trends, and resolution effectiveness |
| Supervisor View (Agent-Specific) | Per-agent insights with sentiment, resolution quality, and L3 topic analysis |
| Agent Dashboard (Supervisor Evaluation) | Language-specific, recent evaluation data for coaching |
Dashboards
Quality Dashboards
- Agent Performance Report: Scores, pass/fail, metric adherence, coaching assignments.
- Interaction Evaluation & Conversation Analytics Report: Sentiment, topics (L3), agent metrics, evaluation outcomes.
- Evaluation Form Summary Report: Metric adherence, compliance stats, fatal violations, overall trends.
Setup Quality AI
Complete these steps to get Quality AI running.
- Go to User Management > Role Management > New Role > Other Modules. Learn more.
- Assign the Supervisor role or create custom roles with QM permissions. Learn more.
- Assign Supervisors and Auditors to the relevant queues so they can access the right interactions. Learn more.
3. Enable Features
- Enable Conversation Intelligence, Auto QA, and Bookmarks in Quality AI Settings. Learn more.
- Enable Answer and Utterance suggestions in GenAI Settings. Learn more.
4. Create Evaluation Metrics
- Choose a measurement type: By Question, Question Answer Pair, or Adherence (Static or Dynamic). Learn more.
- Create evaluation metrics. Learn more.
- Set the count type: Entire Conversation or Time Bound. Learn more.
- Assign a name, description, channel, and pass score.
- Select metrics, assign weights, and link the form to queues. Learn more.
- Enable Agent Scorecards in Quality AI Settings.
- Create agent attributes using evaluation metrics.
- Create scorecards, assign attributes and weights.
- Assign scorecards to agents or groups and set a default scorecard. Learn more.
- Create L1, L2, and L3 topics for conversation classification.
- Enable or adjust resolution tracking for L3 topics.
- Save and version taxonomy changes. Learn more.
8. Analyze Interactions in Conversation Mining
- Use filters to review scored interactions. Learn more.
- Save filters to reuse them in audit assignments. Learn more.
9. Create Audit Allocations
- Assign interactions to auditors for manual evaluation.
- Create allocations with filters and sampling.
- Assign interactions to auditors.
- Evaluate interactions using assigned forms.
- Use AI-assisted audits and navigation. Learn more.
10. Run AI-Assisted Manual Audits
- Use AI-assisted audits for faster, more consistent scoring.
- Navigate interactions using adherence moments and violations. Learn more.
- Use the Dashboard to track individual QA progress and queue statistics. Learn more.
- Use the Conversation Intelligence Dashboard for contact center-wide performance trends. Learn more.
