How many past cycles do I need to seed a new tracker with?

Three to six cycle start dates give most prediction algorithms enough baseline data to generate useful forecasts. You do not need months or years of history. Recency matters more than volume. Enter your most recent cycles first. Most on-device trackers, including Floriva, generate initial predictions from as few as one cycle date and refine accuracy as you log new cycles.

What if I deleted my old period tracker before exporting?

Four recovery sources can help: healthcare provider records (LMP dates are recorded at most gynecology and primary care visits), your phone's native health app (Apple Health or Google Fit may have period data written by your old tracker), calendar or notes app entries, and pharmacy purchase records for corroborating dates. Enter whatever you recover and start logging new cycles right away. Your tracker will calibrate within 2 to 3 cycles.

Does period tracking history carry over automatically when switching apps?

No. There is no automatic data portability between period trackers. Each app uses its own data format, and direct import is rarely supported. The standard approach is to export from your old app (which produces a CSV or JSON), read the cycle start dates from that file, and enter them manually during your new tracker's onboarding. Most apps ask for historical cycle data as part of setup.

How long until my new tracker predictions are as accurate as my old app?

Typically 2 to 3 cycles. If you entered 3 to 6 historical cycle start dates during setup, your first prediction will be reasonable but may have a wider confidence window. After you record one new cycle in the app, accuracy improves. After 2 to 3 new cycles, predictions are generally comparable to a well-calibrated app. Historical seed data speeds this up. Without it, calibration takes longer.

alternatives

How to Rebuild Your Period History After Switching Apps

Switched period trackers and worried about losing your cycle history? Reconstruct it from exports, medical records, and secondary sources in under an hour.

The two scenarios: you have an export, or you don't Rebuilding your period history after switching apps is mostly a reading comprehension problem if you exported first, and a detective problem if you didn't. Both are solvable. The good news: modern cycle prediction algorithms are more capable than most users expect. You don't need three years of perfect data to get accurate predictions. You need 2 3 complete cycle records. If you can provide that from an export, healthcare records, or reconstruction, your new app will be useful within a month. Here's how to work through each scenario. If you have an export file This is the best case scenario, and the shortest path. Flo exports arrive as a ZIP file. Inside is typically a JSON or CSV with cycle dates, symptom logs, and account metadata. Open the cycle log file and look for cycle start entries or the equivalent. Sort by date descending and note the last 3 6 dates. Clue exports are a CSV with columns for date, category, and logged data. Filter or sort the spreadsheet to show rows where the period or cycle start category is logged. Note the dates. Glow, Stardust, Natural Cycles, and most other trackers export in similar CSV or JSON form