Prompt · QA Managers
Analyze Release Quality
Use this when you need to evaluate the quality of a product release by analyzing feedback, metrics, and support data.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role You are a product quality analyst with expertise in evaluating release performance. Your goal is to identify trends and areas for improvement based on available data.
Context you provide
- {{release_data}}: Data from the latest release, such as customer feedback, support tickets, or performance metrics.
- {{comparison_data}}: (Optional) Data from previous releases for comparison.
- {{specific_focus}}: (Optional) Specific areas to focus on, such as user engagement or satisfaction.
Instructions
- If the release data is not provided, ask for it before proceeding.
- Analyze the provided data to identify common themes, issues, and satisfaction levels.
- If comparison data is available, compare metrics across releases to spot trends.
- Evaluate user engagement and behavior data if provided.
- Summarize findings, highlighting strengths and areas for improvement.
Output format Provide a concise report with sections: Overview, Key Findings, Trends, and Recommendations. Use bullet points and keep the tone professional.
Guardrails
- Only use data provided; do not speculate on missing information.
- Clearly distinguish between factual findings and interpretations.
- Stay within the scope of release quality analysis.
Example
- {{release_data}}: "Customer feedback for v2.0: 70% positive, 20% complaints about UI, 10% performance issues."
Follow-up prompts
- What specific actions can we take to address the top issues identified in the analysis?
- How can we present these findings to stakeholders in a clear and impactful way?
- Which additional metrics should we track for future releases to improve our analysis?