Data Detective Prompts: Analyse Anything With AI

NO CODING REQUIRED. JUST DATA AND THE RIGHT PROMPTS.

You don't need to know Python or SQL to analyse data with AI. You need to ask the right questions. This pack gives you 30 ready-to-use prompts for making sense of any dataset.

HOW TO SHARE DATA WITH AI

Option A: Copy-paste data as a table (works for small datasets under ~100 rows) Option B: Upload a CSV or Excel file to ChatGPT (requires Plus with Code Interpreter) Option C: Describe the data structure and paste summary statistics

DESCRIPTIVE ANALYSIS (1-10)

1. "Here's my data: [PASTE]. Give me a plain-English summary of what this data shows. No jargon."

2. "What are the 5 most important patterns or trends in this dataset?"

3. "Are there any obvious anomalies or outliers? Flag them with context."

4. "Summarise this data as if you were presenting it to a non-technical executive. Focus on business implications."

5. "What's the story this data is telling? Give me a 2-sentence headline."

6. "What does the distribution of [COLUMN] tell me? Is this what I'd expect?"

7. "Compare [GROUP A] vs [GROUP B] in this data. What are the key differences?"

8. "What time period shows the biggest change and what could explain it?"

9. "If I had to make one business decision based solely on this data, what should it be?"

10. "What questions does this data raise that it doesn't answer?"

DIAGNOSTIC ANALYSIS (11-20)

11. "My [METRIC] dropped in [PERIOD]. Based on this data, what are the 3 most likely causes?"

12. "Which [VARIABLE] has the strongest relationship with [OUTCOME] in this data?"

13. "Segment this data by [DIMENSION]. Which segment is performing best/worst and why might that be?"

14. "Is there a pattern in when [EVENT] happens? Day of week, time of day, seasonality?"

15. "Which customers/products/channels are driving most of the growth? Which are dragging it down?"

16. "If this trend continues, what does [METRIC] look like in 3 months?"

17. "What would I need to change to move [METRIC] by [X%]?"

18. "Find correlations between these metrics: [LIST]. Which ones move together?"

19. "Is there a leading indicator in this data — something that predicts [OUTCOME] before it happens?"

20. "What's the most counterintuitive finding in this data?"

SURVEY & QUALITATIVE DATA (21-25)

21. "Here are 50 open-ended survey responses: [PASTE]. What are the top 5 themes? Quote the most representative responses for each."

22. "Categorise these responses by sentiment (positive/neutral/negative) and identify the most common reason for each."

23. "What feature requests appear most frequently in this customer feedback?"

24. "What are customers NOT saying that they probably mean? Read between the lines."

25. "Turn these qualitative responses into 5 quantifiable insights I can track over time."

REPORTING PROMPTS (26-30)

26. "Write a 200-word data summary I can put in an email to my team about these results: [PASTE DATA]"

27. "Create an outline for a data presentation based on this analysis. What's the narrative arc?"

28. "What visualisations (chart types) would best communicate these findings? Describe what each chart should show."

29. "Write the key takeaways from this analysis in bullet points — one per insight, under 15 words each."

30. "If I could only share ONE number from this entire dataset with my leadership team, what should it be and why?"

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