Editorial · Weekly
Data-Driven Newsletter Template
Original analysis of fresh data, every issue. Each issue is built around one piece of original analysis — a chart, a model, a survey result — with commentary. The data is the differentiator and the moat.
Who this template is for
Analysts, researchers, and anyone with privileged data access.
Issue structure
- The headline finding. One chart and one sentence summarising what's new
- The data. Where it came from, methodology, sample size
- What it shows. 3–5 follow-up charts or breakdowns
- What it means. Your interpretation and what you'd watch next
- Get the data. Link to the spreadsheet, dashboard, or methodology
When to use this template
- ✓ You have access to interesting data nobody else has
- ✓ You can credibly run analysis (or commission it)
- ✓ You want to be cited by journalists, analysts, and other operators
Examples that work
Newsletters using a version of this template successfully:
- Chartr
- Sherwood News
- Marketing Brew's data drops
Use this template in Aldus
Aldus's AI editor uses this template as a starting prompt — paste your sources and the editor produces the first draft in your voice. Suggested prompt:
Topic: Original data-driven analysis on [question]. Voice: Analyst — specific, restrained, willing to say what we don't know. Sources: [the dataset, methodology notes, prior research]. Lead with the headline finding and one chart. Explain methodology honestly. Add 3 follow-up charts. End with what you'd watch next. Don't oversell.
Frequently asked questions
What if I don't have proprietary data?
Public data sets are abundant — Census, FRED, Crunchbase, Stack Overflow Survey, public APIs from Reddit, GitHub, GitHub Trending. The differentiator is the question and the analysis, not the data source.
How original does the analysis need to be?
Original enough that a journalist or operator would cite you rather than the underlying source. A new framing of public data still counts as original work.