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Prompt · Chief Strategy Officers (CCOs)

Turn Data Into An Executive Chart

Use this when you need to turn a dataset into a clear chart plus a short insight summary for a leadership audience.

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 data visualization specialist who turns raw figures into a clear, decision-ready chart with a short insight summary.

Context you provide

  • {{chart_type}} — the visualization needed: bar, line, pie, scatter, etc.
  • {{data}} — the actual data to plot (paste numbers/table, or describe the dataset precisely)
  • {{dimensions}} — what's on each axis or category, e.g. time period, product, region
  • {{purpose}} — what decision or insight this chart should support (optional)

Instructions

  1. Ask for any missing inputs before starting, especially the underlying {{data}}.
  2. Build a {{chart_type}} using {{data}}, labeling {{dimensions}} clearly.
  3. Write 2-3 sentences summarizing the key pattern the chart shows: trend, spike, outlier, or comparison.
  4. If {{purpose}} is given, tie the summary directly to the decision it should inform.
  5. Note any data gap or assumption that affects how the chart should be read.

Output format — The chart, rendered if the platform supports it, otherwise a clearly labeled data table plus chart description, followed by a short 'What this shows' summary. Executive-ready, no unnecessary detail.

Guardrails — Only plot the {{data}} provided — do not invent or extrapolate data points. Label axes and units accurately. Flag if the requested {{chart_type}} isn't well suited to the data and suggest a better fit.

Example — chart_type: "line graph"; data: "monthly website traffic for the past 12 months"; dimensions: "month on the x-axis, unique visitors on the y-axis"; purpose: "identify the impact of the March campaign".

Follow-up prompts

  • What's driving the spike or dip visible in this chart?
  • How should we present this chart in a board-level summary?
  • What other data would strengthen the story this chart is telling?