Source Groups: Organize Your Data Into a Unified Story
Source Groups let you bundle related data sources together so your team gets cohesive, cross-source AI analysis instead of isolated chart updates.
Source Groups: Organize Your Data Into a Unified Story
If you're sending more than a handful of pulses, you've probably noticed something: individually, each chart tells part of the story. But nobody on your team is paid to mentally stitch five separate Slack messages into a coherent picture.
That's the problem Source Groups solve.
What Are Source Groups?
A Source Group is a logical bucket for related data sources. Instead of treating each Google Sheet tab or BigQuery query as an island, you group them by theme — a product line, a department, a campaign — and Chartcastr treats them as one unit for analysis.
When AI analysis runs across a Source Group, it doesn't just summarize each chart independently. It looks at the group as a whole: correlations across sources, trends that span multiple datasets, and context that only makes sense when you see the full picture.
Why This Matters
Consider a marketing team tracking three things: ad spend (Google Sheet), conversion rates (BigQuery), and landing page engagement (another Sheet). Without grouping, you get three separate AI summaries. With a Source Group:
- Cross-source insights — The AI can flag that conversions dropped while spend increased, and tie it to the landing page bounce rate climbing.
- Shared context — Attach external context (like a Notion strategy doc) once, and it applies to every source in the group. No need to duplicate context across individual sources.
- Group-level summaries — In addition to per-chart analysis, you get a summary that spans the whole group. One message, one story.
Setting It Up
- Head to your Source Group settings in the admin panel.
- Create a new group and give it a name that reflects the theme (e.g., "Q1 Marketing Performance").
- Add the relevant sources to the group.
- Optionally, attach external context — documents, notes, or pages that give the AI background on what these sources represent.
That's it. The next time pulses run for any source in that group, the AI analysis will factor in the full group context.
When to Use Groups vs. Individual Sources
Not everything needs to be grouped. Here's a quick framework:
| Scenario | Approach |
|---|---|
| Standalone KPI (e.g., daily active users) | Individual source |
| Related metrics that tell one story (e.g., spend + conversions + engagement) | Source Group |
| Cross-department reporting (e.g., sales + support + product) | Source Group per department, or one combined group |
| Experimental or one-off analyses | Individual source |
Tip
Source Groups work especially well with external context. A single strategy document attached to the group means every source in it benefits from the same background — no repetition needed.
The Bigger Picture
Source Groups are part of a broader pattern in Chartcastr: making your data delivery smarter without making your workflow more complicated. You're already sending pulses. Grouping them just means the AI has more to work with — and your team has less to piece together on their own.
Check out the full Source Groups documentation for details on setup, management, and best practices.