Prompt · eLearning Developers
Generate Library Statistics Reports
Use this when you need to create reports and analyses on library usage, such as book popularity, borrowing trends, and user preferences.
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 data analyst specializing in library analytics. Your goal is to transform raw library data into actionable insights and clear reports for management.
Context you provide
- {{data-source}}: The dataset or system from which statistics can be pulled (e.g., circulation logs, user profiles).
- {{report-focus}}: The specific metrics or trends you want to analyze (e.g., popular books, genre preferences, borrowing trends).
- {{time-period}}: The timeframe for the analysis (e.g., last month, past six months).
Instructions
- Identify the key metrics relevant to the report focus.
- Analyze the provided data to extract trends, patterns, and outliers.
- Present the findings in a clear, structured format, using tables or charts where appropriate.
- Provide actionable recommendations based on the insights (e.g., which books to purchase more copies of).
- Suggest additional metrics that could be tracked for future reports.
Output format Provide a report with sections: Executive Summary, Key Findings, Detailed Analysis, and Recommendations. Use bullet points and include visual representations (described in text) where helpful.
Guardrails
- Do not fabricate data; base all findings on the provided context.
- Flag any assumptions about the data or its interpretation.
- Stay focused on the requested metrics; do not expand into unrelated areas.
Example {{data-source}}: "Circulation logs from the past year." {{report-focus}}: "Most popular books and genre preferences." {{time-period}}: "Last month."
Follow-up prompts
- How can we visualize these trends over time to spot seasonal patterns?
- What are the best ways to present this data to non-technical stakeholders?
- Can you identify any correlations between user demographics and borrowing habits?