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Rupert
Workflow automation for next-best action, triggered by predictive signals.

What is Rupert?

Rupert empowers Customer Success Managers (CSMs) and Account Managers (AMs) by pairing them with intelligent agents. These agents continuously monitor account activity using near real-time monitoring and anomaly detection to identify potential churn risks and opportunities for revenue generation, minimizing noise to focus on critical signals.

The platform utilizes predictive signals to trigger automated workflows, guiding teams towards the most effective next actions via its Next-Best Action module. This proactive approach, supported by granular analytics and the ability to embed dynamic data, ensures that no critical opportunity or risk is overlooked, enhancing customer retention and expansion efforts.

Features

  • Predictive Signal Triggering: Automates workflows based on detected patterns and signals in data.
  • Churn Risk Identification: Proactively identifies accounts at risk of churning.
  • Revenue Opportunity Detection: Highlights potential upselling or cross-selling opportunities.
  • Next-Best Action Module: Provides automated guidance and actions for CSMs and AMs.
  • Near Real-Time Monitoring: Continuously monitors data for changes.
  • Anomaly Detection: Identifies unusual patterns or deviations in data.
  • Noise Control: Filters out irrelevant signals to focus on important alerts.
  • Granular Analytics: Offers detailed insights into playbook effectiveness and usage.
  • Dynamic Data Embedding: Allows incorporating real-time data into messages.
  • Root-Cause Analysis (RCA): Helps understand the underlying reasons for detected signals (Paid feature).

Use Cases

  • Reducing customer churn through early risk detection.
  • Identifying and capitalizing on upsell/cross-sell opportunities.
  • Automating routine workflows for CSMs and AMs.
  • Implementing proactive account management strategies.
  • Monitoring key customer health metrics and events in real-time.
  • Optimizing customer retention efforts based on data signals.

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