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Custom Fields for Insights

Custom Fields are where MiaRec stores AI insight outputs (scores, categories, extracted values). Once a field is populated, it becomes usable in:

  • Conversation details (Analytics view)
  • Dashboards (averages, distributions, trends, drilldowns)
  • Search and filters (e.g., CSAT < 3)
  • Reports/exports (where enabled)

Administration > Customization > Custom Fields

When to create a new Custom Field

Create a Custom Field when you want to:

  • capture a new business-specific metric (e.g., “Reservation Start Date”)
  • store a score (e.g., CSAT, lead score)
  • store a classification (e.g., churn risk: Low/Medium/High)
  • store extracted entities or text (e.g., “Next actions”)

If a prebuilt AI Task already maps to a prebuilt field, you may not need to create anything—just enable the task.

Field type selection (practical guidance)

Choose the field type based on how you plan to use the value:

  • Number (integer/decimal) — scoring, averages, thresholds, range filters
    Examples: CSAT (1–5), Lead Score (0–100)
  • Dropdown / choice — consistent categorization and easy dashboards
    Examples: Churn Risk (Low/Medium/High), Call Outcome
  • Date — extracted dates for timeline analysis
    Examples: Reservation Start Date, Follow-up date
  • Text — summaries, reasons, notes, explanations
    Examples: Call summary, “CSAT explanation”, “Top objection detail”

Recommendation: prefer Dropdown over free text for categories you want to chart consistently.

Step-by-step: create a field for AI Insights

  1. Go to Administration > Customization > Custom Fields.
  2. Click Add (or equivalent).
  3. Configure:
  4. Name (human-readable)
  5. Computer name (stable identifier; avoid spaces; don’t change after rollout)
  6. Description (what the field represents)
  7. Type (Number / Dropdown / Date / Text)
  8. Enable AI Insights integration:
  9. Check the AI Insights checkbox to make the field available to AI Tasks
  10. Configure display:
  11. Choose a Display group (e.g., "CX Metrics", "Sales Metrics") so the value appears in Conversation Details → Analytics.
  12. Save the field.

Custom Field configuration - Integer type

Figure: Custom Field configuration showing AI Insights checkbox and Dashboard option.

Thresholds and labels (scores like CSAT)

For numeric scoring fields, thresholds help you:

  • show labels (e.g., “Dissatisfied”)
  • apply colors for quick scanning
  • create clickable buckets in dashboards

Example CSAT thresholds (1–5): - 1 = Very Dissatisfied - 2 = Dissatisfied - 3 = Neutral - 4 = Satisfied - 5 = Very Satisfied

Keep thresholds consistent across teams to avoid KPI confusion.

Enable the Dashboard checkbox when creating the field to automatically generate a dashboard. This creates:

  • average score display
  • distribution buckets (based on configured thresholds)
  • trend over time
  • clickable drilldown to matching conversations

Custom Field - Threshold configuration

Figure: Threshold configuration for numeric fields. Define buckets with labels and colors for dashboard visualization.

Storing "value + explanation"

Many AI insights are best represented as: - a structured value (score/category/date) - plus an explanation for a human reviewer

MiaRec stores explanations automatically alongside the insight value. When you configure an AI Task to return both a value and an explanation, the explanation is displayed in the Conversation Details view next to the metric value without requiring a separate custom field.