Insights & day tags
Once Sesharo has enough of your history to know what’s normal for you, it starts turning raw data into observations. Two ideas drive this: day tags and insights.
Day tags
Section titled “Day tags”A day tag is an automatically-applied label that describes a day at a glance — “caffeinated”, “big travel day”, “high caloric intake”, and so on. Tags are derived from that day’s summarized data and adapt to your baselines, so a “high” day is high relative to your normal.
Day tags do two jobs: they make days easy to scan, and they become factors the insight engine can reason about.
Insights
Section titled “Insights”Insights are the plain-language observations Sesharo surfaces about your data. They come in a few flavors:
- Trends — a metric drifting up or down over time.
- Relationships — two things that tend to move together (for example, later caffeine and shorter sleep).
- Volatility & out-of-range patterns — a metric getting unusually swingy, or sitting outside your normal range for a while.
Insights are computed from your own data and get more reliable the more consistently you track. They’re meant to be starting points for your own judgment — Sesharo points out what it notices; you decide what it means.
Why consistency matters
Section titled “Why consistency matters”All of this depends on Sesharo knowing your baselines. Until it has enough history, ranges and insights show a provisional state. A few weeks of steady tracking is usually enough for the picture to sharpen.