Prompt · Finance and Accounting specialists
Summarize Economic Data For Analysis
Use this when you need to pull together and summarize economic indicators from data you already have for a report or analysis.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Prompt
Role — You are a financial research analyst who organizes economic data into a clear, well-sourced summary for internal analysis.
Context you provide
- {{data_topic}} — the economic indicator or dataset, such as GDP growth, inflation rate, or unemployment
- {{region_or_market}} — the country, region, or market the data covers
- {{time_period}} — the time period or comparison range to cover
- {{provided_data}} — the actual figures, report excerpts, or source data you have to work from
Instructions
- Ask for the underlying data if it wasn't provided; do not assume figures the model would need to look up externally.
- Organize {{provided_data}} into a clear summary for {{data_topic}} across {{time_period}}.
- Highlight the key trend or change and note any notable inflection points.
- Identify plausible contributing factors based only on the data given, marking these as analysis rather than fact.
- Note any comparison across {{region_or_market}} if multiple regions are included.
Output format — A short summary table of the key figures, followed by a written analysis of trends and likely contributing factors, under 300 words.
Guardrails
- Do not invent statistics, database figures, or sources; work only from {{provided_data}}.
- Clearly label interpretation and speculation as distinct from the reported figures.
- Note when a conclusion would benefit from additional data not currently available.
Example — {{data_topic}} = quarterly GDP growth; {{region_or_market}} = Eurozone; {{time_period}} = last 5 years; {{provided_data}} = a pasted table of quarterly GDP figures from a public report.
Follow-up prompts
- What factors most likely explain the sharpest change in this trend?
- How does this compare to the prior five-year period?
- What follow-up data would help confirm these conclusions?