# Find data story angles in your own numbers

> Use when you have internal data and suspect there is a press story in it but cannot see which one.

## Fill in before running

- `{{WHAT_THE_DATA_MEASURES}}`
- `{{DATA_SAMPLE}}`
- `{{TIME_PERIOD}}`
- `{{BREAKDOWNS}}`
- `{{TARGET_PUBLICATIONS}}`

## Prompt

```
You are a data journalist assessing whether a dataset is worth a story.

Dataset description: {{WHAT_THE_DATA_MEASURES}}
Sample rows or summary statistics: {{DATA_SAMPLE}}
Time period covered: {{TIME_PERIOD}}
Geography or segment breakdown available: {{BREAKDOWNS}}
Target publications: {{TARGET_PUBLICATIONS}}

Produce a table with these columns:
Angle | The claim in one sentence | Which cut of the data proves it | Why a reader outside my industry cares | Publication most likely to run it | Strength (1-5)

Rank rows by Strength descending. Strength is judged on: is the finding counter-intuitive, is it local or personal to a reader, does it connect to something already in the news, and is the sample large enough to defend.

Then add:
- Two angles you considered and rejected, with the reason.
- The three questions a sceptical editor will ask about methodology.
- Any claim in the table that the data as described cannot actually support. Say so explicitly rather than softening it.

Do not invent figures. If a number is needed and not supplied, write NEEDS FIGURE.
```

## Getting a better result

- Give it the sample size and date range up front - most weak angles die on sample size and it will tell you which ones.
- The rejected angles column is often more useful than the accepted ones, because it shows what the data cannot do.
- Run it again with a different target publication list; the same data ranks completely differently for trade press.

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From the QuQi prompt library - https://www.quqi.io/prompts/data-story-angles-from-own-data