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.

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.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

• {{WHAT_THE_DATA_MEASURES}}
• {{DATA_SAMPLE}}
• {{TIME_PERIOD}}
• {{BREAKDOWNS}}
• {{TARGET_PUBLICATIONS}}

Getting a better result

1. 1 Give it the sample size and date range up front - most weak angles die on sample size and it will tell you which ones.
2. 2 The rejected angles column is often more useful than the accepted ones, because it shows what the data cannot do.
3. 3 Run it again with a different target publication list; the same data ranks completely differently for trade press.