You've been tracking your cycle for six months. You have data on sleep, mood, symptoms, flow intensity, and even basal body temperature. You bring it to your doctor, hoping it will help explain why your periods have become unbearable.

Your doctor glances at your phone screen, nods politely, and asks you to describe your symptoms verbally instead.

You leave frustrated, wondering why the data you collected wasn’t useful.

The reality is more complex

Most women's health data isn't designed to be clinically useful. It's designed to be personally empowering, engagement-driving, and easy to collect. Those aren't the same thing.

Women are tracking their health more than ever. Periods. Ovulation. Pain. Mood. Hot flashes. Fertility. There are thousands of apps promising insight, empowerment, and clarity.

But from a medical perspective, data is only useful if it answers questions that matter to care.

Doctors ask, "Can I trust it?" ”Is it accurate?” “Is it consistent?” “Does it change what I do next?”

A lot of women's health data fails this test, not because women aren't reporting honestly, but because the systems collecting that data were never designed with clinical decision-making in mind.

Period tracking apps excel at telling you when your period might arrive. But clinically, that’s basic.

Most apps track start and end dates, subjective flow intensity (light, medium, heavy), self-reported symptoms, mood emojis, and sexual activity. Now imagine you're a gynecologist trying to diagnose endometriosis, PCOS, or abnormal uterine bleeding.

You need quantified blood loss in milliliters, not "heavy." Pain scales with context: location, duration, severity, and what relieved it. Symptom patterns over multiple cycles, not scattered entries. Hormonal markers or lab results. Correlation with other health factors like medication changes or stress events.

Most period apps give you the first list. Doctors need the second.

"How heavy was your flow today?"

You select "heavy" because it felt heavy compared to yesterday. But what's heavy to you might be moderate to someone else. Or heavy compared to your normal might still be within clinical norms.

Without standardization, two women reporting the same symptom may mean entirely different things clinically. One app's "heavy flow" is another app's "moderate flow." One tracks "fatigue," another tracks "low energy." These sound similar, but they're not the same clinically.

Medical records use standardized terminologies like SNOMED CT or ICD codes. Period apps use whatever language seems easier.

This isn't a small problem. It's the difference between data and evidence.

Many women's health products were designed first to increase daily engagement, reduce user drop-off, feel supportive, and avoid regulatory complexity. Clinical usefulness was an afterthought.

That shows up in how data is captured. Inconsistent inputs. Optional fields. Gamified logging. Data that looks good in dashboards but collapses under clinical scrutiny.

Apps are designed for engagement, not clinical rigor. They prioritize features that keep you opening the app, like notifications, community forums, and articles, over features that ensure data quality, like mandatory daily logging, validated symptom scales, and structured data entry.

From a healthcare perspective, data might have to be boring to be useful. Precise. Repetitive. Standardized. Bounded. That doesn't always make for a delightful user experience, but it's what turns data into evidence.

Women's physiology is dynamic in ways medicine still struggles to fully model. Hormones fluctuate daily, monthly, and across life stages. The same symptom can mean very different things depending on cycle phase, age, pregnancy status, or menopause transition.

Yet many platforms treat symptoms as static events. A headache on day 5 of the cycle is not the same as one on day 25. Anxiety in early postpartum is not the same as anxiety five years later. Heavy bleeding at 14 is not the same as at 44.

Without hormonal context, most data loses clinical precision.

Clinical utility requires consistency. Patterns don't emerge from scattered data points. Diagnosis requires observing trends over time; ideally, 3-6 cycles minimum for menstrual conditions.

But app engagement drops sharply after the first month. Many users don't track long enough or consistently enough for the data to reveal meaningful patterns.

And even when women do collect clinically useful data, they're often reluctant to share it. Privacy concerns are valid. Period tracking apps have been sold, subpoenaed, and scrutinized, and women worry about employers, insurance companies, or legal systems accessing their reproductive health data.

Clinically useful data requires clinical integration. But integration requires trust. And trust has been broken repeatedly.

The gap isn't insurmountable. Closing it requires intentional design choices:

Clinician involvement from day zero. Doctors, researchers, and women’s health specialists should be embedded in the product development process from the very beginning—not brought in later to “validate” what already exists. Early clinical input helps define what data actually matters, how symptoms should be captured, which metrics are meaningful, and where safety boundaries lie.

Quantification over estimation. Tools that measure rather than ask. Blood loss in milliliters. Pain assessed with validated clinical scales. Symptoms defined using medical terminology.

Standardization across platforms. Industry-wide agreements on how to define, collect, and structure menstrual health data so it's comparable and interpretable.

Consistent, long-term tracking. Design that prioritizes data completeness over daily engagement. Features that make it easy to track accurately even when motivation wanes.

Clinical integration pathways. Secure, ethical ways to share data with healthcare providers. Export functions that generate clinically formatted reports doctors can actually use.

Validation against clinical outcomes. Studies that prove app-tracked data correlates with diagnosed conditions. Without this, it's just information, not evidence.

The FemTech companies that figure this out won't just empower users. They'll transform women's healthcare.

Imagine walking into your doctor's office with six months of quantified, standardized, clinically validated menstrual data. Not estimates. Not emojis. Actual evidence of what's happening in your body.

Imagine your doctor being able to diagnose endometriosis faster because your app flagged patterns consistent with the condition. Or adjusting your PCOS treatment based on objective cycle data rather than vague recollections of "irregular periods."

That's the promise. But we're not there yet.

Most women's health data today sits in the gap between personal insight and clinical utility. It helps you understand your body better. It gives you language to describe what you're experiencing. Those things matter.

But they're not enough to change how doctors diagnose, treat, and support women's health conditions.

The next evolution of FemTech isn't more features, prettier interfaces, or better engagement metrics. It's building tools that generate data doctors can actually use.

Because women deserve more than empowerment. They deserve evidence.

I’m Dr. Ayomide O, a FemTech Credibility Advisor helping FemTech brands build credibility with users & investors through evidence-based content.