Spotting PMS Patterns — Why a Symptom Heatmap Beats a List
Most symptom-tracking apps are list-shaped. You log "headache, day of cycle 22" and the app stores it as a row in a database. A month later you have 30 rows, organised by date. A year later you have 360 rows, and the question you'd actually want answered — do my headaches cluster the few days before my period? — is buried under all that linearity.
The fix is a calendar-style heatmap: each row is a symptom, each column is a day, and the colour of the cell is how severe it was. Empty cell means not logged. Pattern visible at a glance. The same data you've been entering all along, organised so the trend can't hide.
What you actually want to see
When you start tracking PMS symptoms across multiple cycles, three patterns are worth catching:
- Cyclical: cramps a day or two before your period starts, headaches the week before, low energy in the late luteal phase. These cluster predictably.
- Trigger-linked: acne after dairy, bloating after specific foods, headaches after poor sleep. These don't track the cycle — they track behavior.
- Drift: a baseline symptom that's slowly getting worse over months. Worth showing your clinician before it gets serious.
A list of dates makes these all look the same. A heatmap separates them — cyclical ones show as vertical bands tied to cycle position, trigger-linked ones look random, and drift shows as a row that gets darker over time.
Why fixed categories
A symptom tracker that lets you type free-text "what hurt today" is friendly to fill out and impossible to chart. The pattern only emerges when you've used the same labels consistently. Flo and Clue both figured this out — their fixed-category models look limiting at first but are the reason their pattern detection works.
A useful set covers the most common PMS symptoms with a 0–3 intensity scale (anything finer is hard to remember consistently a week later):
- Cramps — pelvic / lower abdomen
- Headache
- Bloating
- Fatigue
- Acne / skin
- Breast tenderness
Plus a few day-level vitals: mood (great / good / ok / low / rough), energy (low / med / high), sleep hours, and a free-text notes field for the things that don't fit the categories.
The 0–3 scale
Why three levels of severity instead of five or ten? Because you're going to fill this in once a day, in 30 seconds, while half-asleep. "Was it mild, moderate, or severe?" maps to memory cleanly. "Was it a 4 or a 5 out of 10?" doesn't. A coarser scale that gets filled in consistently beats a finer one that gets filled in inconsistently.
Reading the heatmap
Once you have 60 days of data, look for:
- Vertical clusters — a column that's dark across multiple symptom rows means a rough day. Multiple rough days in a row, all 4-7 days before your period, are the classic late-luteal pattern.
- Horizontal clusters — a row that's dark for several days running means that one symptom is having an episode. Combined with notes, you can usually correlate it to a trigger.
- Quiet weeks — empty stretches matter. The follicular phase (after your period, before ovulation) is typically the lightest. If it's NOT in your data, that's worth noticing.
Patterns get clearer the longer you log. After three full cycles you can usually see the cycle-tied clusters. After six, drift becomes visible.
Our take
The Symptom Tracker renders exactly this: a 60-day heatmap with one row per symptom, plus mood and energy. Click any cell and the editor jumps to that day so you can fix or add a note retroactively. Everything stays in localStorage on this device — same privacy story as the Period Tracker. CSV export when you want to move it.
Clear-all in one click. No account, no upload.
What it isn't
A symptom tracker is a journaling tool, not a diagnostic one. Persistent severe symptoms, sudden changes, or anything that interferes with daily life is a clinician conversation — and a tracker is genuinely useful when you walk into that appointment with three months of data instead of "ummm yeah it's been pretty bad lately." Pattern recognition is what the tracker does. Diagnosis is what your provider does.
The short version
A list of dated symptoms is data nobody can read. The same data laid out as a heatmap surfaces clusters in seconds. Fixed categories on a coarse intensity scale make the heatmap actually fill up consistently. Then patterns become obvious — and you have something specific to talk about at your next visit.