Insights
Insights are saved queries over your events: pick an event, choose an aggregation, filter and group it, and save the result as a chart on your dashboard.
What an insight is
An insight is defined by:
- Event — a specific event name, or all events
- Aggregation — event count or unique users
- Filters — property conditions (e.g.
plan = "pro") - Group by — a time interval (day, week, month) or a property value
- Visualization — line, bar, pie, table, or a single number
Example: "Weekly signups on the pro plan" is user_signed_up, filtered to plan = "pro", grouped by week, drawn as a line chart.
Saved insights run on demand and can be pinned to your project dashboard as widgets.
How to instrument for insights
Insights are only as good as the events underneath them:
- One name per action. Use a single, consistent event name for each action (
purchase_completed, not sometimespurchaseand sometimesbuy_completed). Insights query by exact event name. - Put dimensions in properties. If you'll want to break a metric down by something — plan, screen, product category — send it as a property rather than encoding it in the event name.
feature_usedwith{ feature: "dark_mode" }can be grouped by feature;dark_mode_usedcannot. - Use consistent property values.
"pro"and"Pro"are different values in a breakdown.
// Good: one event, groupable by property
track('feature_used', { feature: 'export', plan: 'pro' });
// Hard to analyze: name explosion
track('export_feature_used_by_pro_user');
Ask AI
On paid plans you can also ask questions in plain English ("how many users exported data last week?") and get a chart back — useful for one-off questions that don't warrant a saved insight.
Next steps
- Funnels — multi-step conversion
- Retention — do users come back?
- Tracking Events — naming and property patterns