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AI advisor converts detected customer issues into recommended actions your team can review and approve. It helps reduce manual work by preparing strategy, messaging, and execution suggestions in one place.

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What AI advisor provides

  • Recommended workflow path for each detected issue
  • Suggested segmentation logic
  • Drafted email copy aligned to your brand tone
  • Suggested timing and cadence
  • Outcome tracking after approval and launch

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How the recommendation flow works

  1. Detect: risk signals are identified from customer health and behavior data.
  2. Recommend: AI advisor suggests a fix package.
  3. Review: your team edits or approves the recommendation.
  4. Execute: approved actions are launched through workflows.
  5. Measure: results are tracked in recovery and impact metrics.

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Brand and personalization inputs

AI advisor recommendations align to client settings, including:
  • Brand identity and tone of voice
  • Sender configuration
  • Template and variable availability
  • Segment and lifecycle state data
For template variables and custom vars guidance, see:

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Enabling AI advisor

AI advisor is controlled by feature flags in account settings. Recommended rollout:
  1. Enable AI advisor for a controlled set of interventions.
  2. Require manual approval for early runs.
  3. Review recommendation quality and outcome lift.
  4. Expand usage once quality is stable.

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Safety and governance

  • Keep approval checkpoints for customer-facing sends
  • Document why recommendations were accepted or rejected
  • Validate segment targeting before execution
  • Review outcomes and adjust strategy regularly

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Success signals

Track these indicators to measure AI advisor effectiveness:
  • Recommendation approval rate
  • Time from detection to approved action
  • User recovery rate after AI-advised interventions
  • Revenue protected or recovered