afrexai-voc-engine
Complete Voice of Customer system — collect, analyze, and operationalize customer feedback at scale. Covers NPS/CSAT/CES measurement, customer interview methodology, feedback taxonomy, feature request prioritization, sentiment analysis, closed-loop workflows, and VoC-driven product decisions. Use when building feedback systems, running customer interviews, measuring satisfaction, analyzing feature requests, reducing churn, or closing the feedback loop. Trigger on "customer feedback", "voice of customer", "NPS", "CSAT", "CES", "feature requests", "feedback system", "customer interviews", "satisfaction survey", "churn analysis".
Why use this skill?
Deploy a complete Voice of Customer system to collect, analyze, and operationalize user feedback, drive product decisions, and reduce churn.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/1kalin/afrexai-voc-engineWhat This Skill Does
The afrexai-voc-engine is a comprehensive framework for designing, implementing, and optimizing Voice of Customer (VoC) programs. It provides a structured methodology to move from ad-hoc feedback collection to a highly operationalized engine that influences product strategy, reduces churn, and increases expansion revenue. The skill handles the end-to-end feedback lifecycle, including NPS/CSAT/CES measurement, customer interview protocols, feedback taxonomy definition, and the creation of closed-loop workflows. By integrating directly into your product ecosystem, it transforms raw user feedback into actionable product roadmap decisions.
Installation
To integrate this skill into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/1kalin/afrexai-voc-engine
Use Cases
- Churn Reduction: Identifying early signals of user dissatisfaction by analyzing negative sentiment trends in support tickets and usage data.
- Roadmap Prioritization: Using feature request voting and feedback volume to justify development efforts and build what customers actually need.
- Customer Interviews: Conducting structured, high-value discovery calls to uncover deep-seated pain points or feature validation.
- Satisfaction Benchmarking: Establishing a reliable system to measure and track NPS, CSAT, or CES over time to understand the health of your customer base.
- Operationalizing Feedback: Closing the loop with users by automatically routing feedback to product teams and notifying users when their requests are addressed.
Example Prompts
- "I need to design a feedback system for our SaaS platform. Can you help me draft a program brief using the VoC Engine framework for our enterprise segment?"
- "We have a high churn rate in our SMB segment. Analyze our recent support tickets and usage data to identify the top three themes causing dissatisfaction."
- "Our CSAT score has dropped recently. Please guide me through a maturity assessment and suggest three actionable steps to move our collection process from Ad Hoc to Structured."
Tips & Limitations
- Consistency is Key: The efficacy of this engine depends on the quality of your taxonomy. Ensure all team members use consistent tagging across support channels.
- Don't Over-Survey: Avoid 'survey fatigue' by carefully selecting triggers for in-app widgets rather than blasting all users simultaneously.
- Close the Loop: The most critical step is telling users when their feedback has been actioned; ignoring this step renders the collection process ineffective.
- Resource Heavy: This is a comprehensive organizational skill. It requires stakeholder buy-in across Product, Support, and Customer Success teams for maximum impact.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-1kalin-afrexai-voc-engine": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: data-collection