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How do fertility trackers interact with advertising services?

The Pregnancy and Health Apps Still Leaking Data in 2026

Posted on June 30, 2026June 30, 2026 by James O'Claire

When Yeeun Jo, a student at University of Illinois at Urbana-Champaign (UIUC) contacted me in 2025 to ask about data tracking in app advertisements related to women’s health and pregnancy I was a bit skeptical. I think I first told her along the lines that while such data collection was broad it was rarely so specific as the advertisers were unlikely to act on specific information like which week of pregnancy a woman was currently in.

Not to mention, Facebook’s historic $5 billion FTC fine for deceptive third-party data tracking, and the FTC’s subsequent 2021 crack-down specifically targeting Flo Health for passing intimate logging metrics to Facebook’s SDK. I thought it was unlikely they’d find much.

10 years of ad experience, and I’m still wrong on what ends up tracked

Well, it’s a year later and Yeeun was 100% correct in her guess that mobile apps and mobile ad networks were still tracking more data than I expected. She and Brad Reaves released their paper “Expecting (Targeted Ads)? Network Analysis of User Health Data Leakage in Fertility Tracking Apps” showing the high specificity which these events are tracked.

What did Yeeun find?


Interaction
Example Health Leakage Parameters
Registrationus=precon, us=preg02,tri1
Menstruationappmode=ttc, csw=preg02,tri1, sid=pregnancy-prep-for-moms-to-be, subcat=ovulation
Fertilitycat=gettingpregnant, subcat=preppingforpregnancy, contentidentifiers=conceptionbasics, preconceptiontests, naturalfamilyplanning symptomsallkinds, vaginalbleedingdischarge
SleepNo unique values, repeats other leakage parameters
Contraceptiontopic=baby-products-health-and-safety
Pregnancybage=33, cat=pregnancy, csw=preg02,tri1, sid=checklist-packing-a-hospital-bag, registry, spot=child-growth, isitsafe, birthprefs, subtopic=pregnancy-weight-gain, tid=weight-gain
Postpartumappmode=baby, cat=firstyear, csw=post7m,child0yr, phase= baby, sid=your-baby-week-1, subcat=monthbymonth
Pregnancy Losssubcat=pregnancyloss, wknum=17, us=null
Examples from table 3:
https://arxiv.org/html/2606.26276v1#S4.T3

I think what was surprising here is the accuracy of the X weeks and X months pre and post birth that were surprising here. While I of course would have expected the categories themselves like pregnancy / ovulation etc to be passed as those would be the easy high value adds for a pregnancy app to increase their monetization, the specificity of the time was much deeper than I expected.

If you didn’t catch them in the lists there are plenty of things that stand out like apps sharing: ‘vaginalbleedingdischarge’ Then there is the ‘subcat=pregnancyloss,wknum=17’ which crosses a morality line.

How was the data collected?

The data was collected similar to how I collect advertising data on AppGoblin by collecting all network traffic in and out of apps. Jo & Reaves went the additional step of “systematizing app features [and] conduct a series of standardized user interactions across all apps” which enabled them to capture the specific categories and times above like weeks, trimesters and category of pregnancy.

Wasn’t FB & Google investigated and paid millions for doing this?

This joins the massive stories from the past 7 years that started with Facebook in 2019 when it was reported that Flo had set their conversion metrics up based on health sensitive data. Thus Facebook was collecting and targeting their ads based on private data, which they were later fined and found guilty of. In the end Google and Flo Health had multiple settlements and paid $58 million in a class action settlement.

You’d think in 2026 there wouldn’t have been so many apps still sending this data.

Apps in the Paper

Here are the apps called out in the paper. I added URL links to the data I’ve collected about the apps with AppGoblin. AppGoblin only collects data in the first app open and without any interaction, so I was unable to verify the specifics like ‘3rd trimester’ or other data being sent deeper in the user journey as collected by Reaves and Jo.

What you can see on AppGoblin is each of the Ad Networks and data trackers currently integrated with each of the apps.

AppNameApp Store IDHeadquarters
Clovercom.wachanga.womancalendarLimassol, Cyprus
Stardustcom.stardust.appNew York, NY, USA
My Calendarcom.popularapp.periodcalendarTortola, United Kingdom
My Period Calendarcom.lbrc.PeriodCalendarRedmond, WA, USA
Lily Trackercom.smsrobot.periodDublin, Ireland
GP Trackercom.period.tracker.liteLos Angeles, CA, USA
MIAcom.azarou.aventure.spoonge.run
BabyCentercom.babycenter.pregnancytrackerNew York New York, USA
Pregnancy +com.hp.pregnancy.liteNoord-Holland-Amsterdam, Netherlands
Amila Pregnancycom.easymobs.pregnancyPaphos, Cyprus
What to Expectcom.wte.viewNew York, NY, USA
Pregnancy (duff hl studio)com.women.pregnancytrackerapp22
Preglifecom.gravid.gravid
The Bumpcom.xogrp.thebumpChevy Chase, MD, USA
Timskiy Pregnancycom.timskiy.pregnancy
Ovyucom.ishitechnolabs.ovyuGujarat Surat, India
Radhu Pregnancycom.radhu.pregnancytracker
Evelinecom.ixensor.lhTaipei City, Taiwan
Kindaracom.kindara.pgapBoulder, Colorado , USA
Miramira.fertilitytracker.android_us

What’s Next?

The paper didn’t share the specifics of which apps sent which private data to which Ad Networks. I think this would be highly worth checking. It would require the specific walking through the app on boardings to trigger the various ad calls containing the relevant data.

If anyone is interested in this as a project I’m happy to help. Please DM or email me.

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