App analytics vs sensitive health data
A practical guide to the difference between app analytics and sensitive health data, and why that distinction matters in cycle tracking apps.
Not all app data is the same.
There is a difference between basic analytics and sensitive health data. This difference matters.
Pattern Snapshot
The line to look for
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A strong privacy model makes this boundary clear in both product design and policy language.
What app analytics usually means
Analytics can include:
- app usage
- clicks and navigation
- performance data
This is often used to improve the product.
What sensitive health data includes
In a cycle tracking app, this can include:
- cycle dates
- symptoms
- mood
- personal notes
This is deeply personal.
Why the distinction matters
Some apps treat all data the same. Others separate them.
If sensitive data is handled like analytics, it can be:
- shared
- used for targeting
- exposed in ways you don't expect
What to look for
- clear separation between analytics and health data
- no data selling
- simple control over your data
If this isn't clear, it's a risk.
How this fits into privacy
This connects to how apps make money.
You can explore that here: do period apps sell your data
And how different models work: privacy-first vs ad-supported apps
Final thought
Privacy is not just about storage. It's about how data is treated.
If you want to understand what strong privacy should actually look like, start here. How private should a period tracker be
Luna separates analytics from sensitive health data and does not rely on selling it. Explore how it works →
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