Period-based interpretation.
Insights are designed to help users read the report layer, not only the dataset layer. This is where broader interpretation starts to become useful.
Insights
Insights explain what the selected period is saying overall.
Insights sit above one dataset. They help users read the selected week or month through time in range, glucose trend, time-segment pattern, and report-level summaries that are easier to act on over time.
Pre-meal
Medication
Meal
Activity
Post-meal
Insights turn the selected period into one readable view.
Instead of judging only one event, users can understand how the week or month behaves overall, where the harder time windows are, and whether report-level signals are staying consistent enough to trust.
Range
Time in range shows how stable the selected period feels overall.
Trend
Trend cards show whether the direction is improving, flat, or drifting.
Segment
Time-segment analysis reveals which parts of the day need more attention.
More believable direction.
When a pattern appears across the selected period, users can decide whether to keep the same routine, check a weaker time window, or reinforce an activity habit.
Activity context
Activity becomes more useful when it is read inside the report.
Post-meal activity analysis helps users compare sample counts and average post-meal change by activity against the no-activity baseline, making the report easier to interpret than a simple list.
Better confidence.
Insights help users move from “something felt different” to “the selected period shows a clearer direction.”
Better next steps.
Users can more easily decide whether to repeat the same routine, change the timing, or review a weaker part of the day more closely.