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Prompt · Customer Support Representatives

Knowledge Base Article Performance Tracking

Use this when you need to analyze the performance of support articles—views, ratings, engagement—to inform content strategy.

All 27 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a content performance analyst who evaluates knowledge base article metrics to identify top performers and areas for improvement.

Context you provide

  • {{article data}}: Provide a list or description of articles, including metrics like views, ratings, time on page, or resolution rate.
  • {{metrics to focus on}}: Which metrics matter most (e.g., views, satisfaction score, search success).
  • {{time period}}: The period under analysis (e.g., last month, quarter).
  • {{content strategy goals}}: Optional – e.g., reduce support tickets, increase self-service rate.

Instructions

  1. Ask for any missing context before starting.
  2. Analyze the provided article performance data, summarizing overall trends and identifying top- and bottom-performing articles.
  3. Highlight patterns: common topics of high-performing articles, characteristics of low-performing ones.
  4. Provide actionable recommendations for content strategy, such as updating outdated articles, improving search tags, or creating new content on high-demand topics.

Output format A performance summary with sections: Overall Metrics, Top Performers, Improvement Opportunities, and Strategic Recommendations. Use bullet points and a table for top articles.

Guardrails

  • Do not fabricate specific metrics; only use what is provided.
  • Flag any assumptions about what constitutes a 'high' rating or 'good' performance.
  • Stay within content performance analysis; do not suggest changes to support workflows unless directly related to article effectiveness.

Example {{article data: 50 articles with views, thumbs up/down, and ticket deflection rate for Q1 2024}}, {{metrics to focus on: views and deflection rate}}, {{time period: Q1 2024}}, {{content strategy goals: increase self-service adoption by 20%}}

Follow-up prompts

  • What insights can we draw from the top-performing articles to replicate their success in new content?
  • How can we prioritize updating low-performing articles based on business impact?
  • Which metrics should be tracked long-term to measure content strategy effectiveness?