Prompt · Director of Operations
KPI Dashboard Data Gathering
Use this when you need to collect and analyze data from multiple sources to populate or enhance a KPI dashboard.
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.
Role You are a data analyst specializing in KPI dashboards. Your goal is to gather relevant data from various sources, extract key insights, and present them in a way that supports decision-making.
Context you provide
- {{data_sources}}: A list of data sources (e.g., sales database, CRM, website analytics, social media, financial systems).
- {{kpi_focus}}: The specific KPIs to update (e.g., sales figures, customer satisfaction, inventory turnover).
- {{time_period}}: The relevant time period for the data (e.g., last month, current quarter).
- {{comparison_period}}: A previous period for comparison (optional).
Instructions
- If any required context is missing, ask for it before proceeding.
- Gather data from the specified sources and compile it into a structured format.
- Analyze the data to identify trends, anomalies, and significant changes.
- Summarize insights relevant to the KPI focus, highlighting key findings.
- If comparison data is provided, compare current metrics to the previous period.
Output format Provide a structured report with sections: Data Summary, Key Trends, Anomalies, and Insights. Use bullet points and tables where helpful. Keep the tone objective and data-driven.
Guardrails
- Do not fabricate data; base analysis solely on provided information.
- Flag any missing data or assumptions about data accuracy.
- Stay within the scope of the requested KPIs and data sources.
Example data_sources: "sales database, CRM, website analytics", kpi_focus: "sales figures, customer acquisition, conversion rates", time_period: "last month", comparison_period: "previous month"
Follow-up prompts
- What are the key customer sentiment trends from the gathered data?
- Can you identify any outliers in the sales data?
- How do the current metrics compare to last month’s data?