Flagged Conversation Statistics

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Request

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Headers

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Path Parameters

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Parameter Format

• Format: YYYY-MM-DD (ISO 8601 date)
• Timezone: UTC
• Default: Last 7 days if not provided

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Response

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200 OK - Successfully retrieved flag and completion statistics

{
  "message": "",
  "data": {
    "times": {
      "flagged": {
        "min": 5,
        "max": 120,
        "average": 25.8,
        "median": 20.0
      },
      "complete": {
        "fromFlagged": {
          "min": 10,
          "max": 300,
          "average": 85.5,
          "median": 72.0
        },
        "fromUnFlagged": {
          "min": 15,
          "max": 240,
          "average": 65.2,
          "median": 55.0
        }
      }
    },
    "counts": {
      "totalFlagged": 35,
      "completedFromFlagged": 28,
      "completedFromUnFlagged": 14
    }
  }
}

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401 Unauthorized

{
  "error": {
    "code": "UNAUTHORIZED",
    "message": "Missing or invalid token"
  }
}

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500 Internal Server Error

{
  "error": {
    "code": "SERVER_ERROR",
    "message": "Internal server error"
  }
}

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Example

curl -X GET 'http://localhost:2000/email-meter/stats/flags/2025-10-01/2025-10-07' \
  -H 'Authorization: Bearer your-jwt-token'

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Data Fields Explained

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Times - Flagged

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Times - Complete

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Counts

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Flag Analysis

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Flagging Efficiency

const flaggingEfficiency = {
  flagRate: data.data.counts.totalFlagged / totalConversations,
  completionRateFromFlagged: data.data.counts.completedFromFlagged / data.data.counts.totalFlagged,
  averageTimeToFlag: data.data.times.flagged.average,
  averageResolutionFromFlagged: data.data.times.complete.fromFlagged.average
};

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Resolution Comparison

const resolutionComparison = {
  flaggedVsUnflagged: data.data.times.complete.fromFlagged.average - data.data.times.complete.fromUnFlagged.average,
  flaggedSlower: data.data.times.complete.fromFlagged.average > data.data.times.complete.fromUnFlagged.average,
  percentageDifference: ((data.data.times.complete.fromFlagged.average - data.data.times.complete.fromUnFlagged.average) / data.data.times.complete.fromUnFlagged.average) * 100
};

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Use Cases

• Quality Control: Monitor flagged conversation handling
• Process Improvement: Identify issues requiring flagging
• Training Needs: Target training based on flag patterns
• Escalation Management: Track escalation effectiveness
• Performance Metrics: Measure flag resolution efficiency

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Flag Categories

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Common Flag Reasons

• Urgent: Requires immediate attention
• Escalation: Needs higher-level support
• Complex: Requires specialized knowledge
• Sensitive: Contains sensitive information
• Compliance: Requires compliance review

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Performance Targets

• Time to Flag: < 30 minutes for urgent issues
• Resolution from Flag: < 2 hours for urgent flags
• Flag Completion Rate: > 90% of flagged conversations resolved
• Flag Accuracy: > 80% of flags are appropriate

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Best Practices

1. Flagging Guidelines: Establish clear flagging criteria
2. Training: Train agents on when and how to flag
3. Monitoring: Track flag patterns and resolution times
4. Feedback: Provide feedback on flagging accuracy
5. Process Review: Regularly review flagging processes

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Related Endpoints

• Use /email-meter/stats/resolved-times for overall resolution metrics
• Use /email-meter/stats/agents-detailed for agent-specific flag data
• Use /email-meter/stats/response-times for initial response analysis

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Notes

• Flag times are calculated from conversation start to flag action
• Resolution times are calculated from flag to resolution
• Only manual flags by agents are included
• Automated flags are tracked separately
• Flag reasons may be analyzed for pattern identification