Insight Communication AI Prompts

Write a clear, insightful caption for this data visualization that tells the audience what to notice and what it means. Chart description: {{chart_description}} Audience: {{audience}} Key finding in the chart: {{key_finding}} Most chart captions are bad because they describe what the chart shows rather than what it means. A good caption answers: 'So what?' 1. The headline caption (1 sentence, bold): - State the insight, not a description of the chart - Wrong: 'Monthly revenue from January to December 2024' - Right: 'Revenue peaked in March before falling steadily — Q4 is 23% below Q1' - The headline should be a complete sentence with a verb, not a label 2. The supporting caption (1–2 sentences): - Add the most important context or implication that the headline did not capture - Point the reader to something specific: 'Note the sharp drop in August, which coincides with the system outage' - If the finding is surprising: explain briefly why that matters 3. Data note (optional, smaller text): - Source of the data - Any important caveat about how to read the chart (e.g. 'revenue excludes refunds') 4. Write 3 alternative headline options: - Option A: factual and neutral - Option B: action-oriented (implies what should happen) - Option C: question-framing (poses the key question the chart raises) For each option, explain in one sentence who it would be most appropriate for (analyst audience, executive audience, public-facing report).

Help me build a data story that takes my audience from the current situation to a clear recommendation. My data findings: {{findings}} My audience: {{audience}} The decision I want them to make: {{desired_decision}} A data story is not a data dump. It is a narrative that uses data as evidence to make a persuasive case. 1. The opening hook (1–2 sentences): - Start with something that makes the audience care: a surprising number, a relatable scenario, or the cost of inaction - Do not start with 'The purpose of this analysis is...' 2. The context (2–3 sentences): - What is the situation? Why are we looking at this now? - What were we expecting or hoping for? 3. The finding (the heart of the story): - What does the data actually show? - Present the key insight with supporting evidence — not a list of all findings, just the most important one - Acknowledge any counterintuitive or surprising element — it builds credibility 4. The implication (so what?): - What does this finding mean for the business? - What happens if we ignore it? - Quantify the impact if possible: revenue at risk, cost savings available, customers affected 5. The recommendation (the ask): - State one clear, specific action - Say who should do it, by when, and what the expected outcome is - Acknowledge the main objection your audience might have and address it briefly 6. The narrative structure check: - Does each section naturally lead to the next? - Could someone who did not see the data repeat your key point accurately to a colleague? Write the complete data story following this structure.

Turn my data findings into a clear executive summary that a non-technical leader can understand and act on. My findings: {{findings}} Audience: {{audience}} (e.g. VP of Sales, CFO, Operations Director) Decision needed: {{decision_needed}} 1. Lead with the so-what — not the analysis: - The first sentence must state the business implication, not the data finding - Wrong: 'Revenue declined 14% in Q3 compared to Q2' - Right: 'We are at risk of missing the annual target by $2.3M if Q4 revenue does not recover — here is what drove Q3's decline' 2. Use the SCR structure (Situation, Complication, Resolution): - Situation (1–2 sentences): what is the context? What were we expecting or hoping for? - Complication (2–3 sentences): what did the data reveal that is different from expectations? Include the key numbers. - Resolution (2–3 sentences): what does this mean for the decision at hand? What do you recommend? 3. Make every number meaningful: - Every statistic must have context: '14% decline' should be '14% decline — the largest quarter-over-quarter drop in 3 years' - Translate percentages to absolute impact where possible: '14% decline = $1.8M less than the same period last year' - Replace 'significant' with the actual number 4. One clear ask: - End with a single, specific request: a decision, an action, or a resource - Do not list 5 options — give one recommendation with a brief rationale 5. Length and format: - Maximum 200 words for the summary - One supporting table or chart description if needed - No bullet lists of raw statistics — write in paragraphs Write the executive summary now, following these principles.

A business stakeholder is pushing back on my data findings. Help me respond thoughtfully and maintain credibility. My finding: {{my_finding}} Stakeholder's objection: {{objection}} 1. First, take the objection seriously: Before preparing a rebuttal, ask: is the stakeholder raising a legitimate concern? - 'The data might be wrong' → Check: is there a reason the data quality could be an issue here? - 'This does not match what I see on the ground' → Check: is there a segment or time period the data is missing? - 'That cannot be right' → Check: have you double-checked the calculation? - 'The analysis method is wrong' → Check: is there a better method you should consider? 2. Classify the objection: - Factual objection (they dispute the data itself) → Respond with evidence and methodology - Interpretation objection (they agree on the data but disagree on the conclusion) → Explore the alternative interpretation together - Emotional objection (the finding is inconvenient or threatening) → Acknowledge the difficulty while holding the finding - Expertise objection (they know the domain better) → Listen carefully — they may be right 3. Prepare your response: For each objection type, draft a response that: - Acknowledges their perspective genuinely: 'That is a fair challenge to raise' - Addresses the substance of the concern with evidence - Does not become defensive or dismissive - Leaves the conversation open rather than closing it: 'What data would change your view?' 4. When to concede: - If the stakeholder raises a point that genuinely undermines the finding: concede it clearly and update your conclusion - Conceding when warranted builds far more credibility than defending a flawed finding 5. Draft the actual response: Write a 3–5 sentence response to the specific objection above that is confident but not combative.

I have technical analysis results that I need to explain to a non-technical business audience. Help me translate them into plain language without losing the key insights. Technical findings: {{technical_findings}} Audience: {{audience}} (their background: {{audience_background}}) 1. Jargon replacement guide: For each technical term in my findings, provide the plain English replacement: - 'Statistically significant' → 'We can be confident this difference is real, not just random' - 'Correlation of 0.73' → 'When X goes up, Y tends to go up about 73% of the time' - 'Regression model' → 'A mathematical formula that calculates the predicted value based on other factors' - 'Confidence interval' → 'The range within which the true answer almost certainly falls' - 'Null hypothesis rejected' → 'The data shows a clear difference — it is not just chance' Apply this principle to every technical term in my specific findings. 2. Translate each finding: For each technical finding, write: - The plain English version (1–2 sentences, no jargon) - A concrete analogy or example that makes it tangible - The business implication in one sentence 3. What to leave out: - Methodological details your audience does not need to evaluate the conclusion - Intermediate results that do not change the recommendation - Caveats that are technically important but would not change the action taken (note separately: caveats that ARE important enough to share, and how to phrase them without undermining your findings) 4. The 'can they repeat it?' test: After writing the simplified version, check: could your audience repeat the key finding accurately in a conversation with their own colleagues? If no: simplify further. If yes: you are done. Return: the translated findings, the jargon glossary, and a 3-bullet 'take-away' summary for the audience.