Customer retention · AI-driven decisions
Recommend the next best customer action
Customers are often given generic guidance even though their product history and current behavior indicate a specific next action that would improve adoption.
The record
Telemetry these decisions draw on
- Feature-use sequences
- Completed and abandoned workflows
- Configuration state
- Training activity
- Support history
- Integration status
- Usage patterns of successful customers
The questions
What an agent answers
- What should this customer do next?
- Which feature or workflow is most relevant now?
- Which missing action is preventing deeper adoption?
- Should the next step be automated guidance or human outreach?
- What similar behavior led other customers to success?
"Users who created their first dashboard but have not configured alerts typically abandon the product. Prompt this user to activate the alerting workflow."
Related use cases
Browse the full library →Customer retention
Detect customers becoming disengaged
Customer disengagement is often recognized only after usage has materially declined or a renewal is already at risk.
Root cause analysis · Chief Information Officer / Chief Customer Officer
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Provide proactive customer support
Customers frequently experience repeated errors or failed workflows before they open a support case, creating avoidable frustration and support cost.
Root cause analysis · Chief Information Officer / Chief Customer Officer
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Explain customer-impacting failures
A customer journey can fail even when individual systems appear healthy, making it difficult to determine why customers abandon applications, purchases, or digital workflows.
Root cause analysis · Chief Information Officer / Chief Customer Officer
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