Most FemTech founders know they need "evidence" to build credibility. But does "evidence" mean user testimonials, a pilot study, or published research?

You need to know that evidence exists on a spectrum, and understanding which type of evidence you need at each stage of your company can be the difference between success and stalled growth.

Let’s break down the five types of evidence every FemTech startup should be working toward and when each one matters most.

Type 1: User Testimonials and Qualitative Feedback

Real stories from women describing their experience with your product.

Why it matters: This is your foundation. User testimonials prove that real women are using your product and finding value. They show you're solving a real problem, not just an imagined one. It could be app store reviews, social media mentions, or direct user feedback

When you need it: From your very first user, you should be collecting feedback.

How to collect it:

  • In-app surveys asking specific outcome questions

  • Follow-up emails at 30, 60, and 90 days post-signup

  • User interviews (record with permission)

Limitation: Testimonials show user satisfaction but aren't clinical evidence. Investors love reading them, but they won't replace hard data.

Action step: Create a system for collecting user feedback consistently. Make it easy for users to share their stories, and always ask permission before using testimonials publicly.

Type 2: User Engagement and Retention Metrics

Quantitative data showing how women actually use your product over time.

Why it matters: Engagement proves your product isn't just downloaded but used consistently. Retention shows women find long-term value, not just initial curiosity.

High retention signals trust, showing that users are making your product part of their routine. Low retention is a red flag that either the product isn't delivering value or the user experience is broken.

What it looks like:

  • Daily/monthly active users (DAU/MAU)

  • Session length and frequency

  • Feature adoption rates

  • 30-day, 60-day, and 90-day retention

  • Completion rates for onboarding or educational journeys

When you need it: From day one. Track this immediately and review monthly.

Action step: Set up analytics from the start, tools that track user behavior. 

Type 3: Clinical Validation Through Pilot Studies

Structured studies showing your product leads to measurable health outcomes.

Why it matters: This is where you move from "users like it" to "it actually works." Clinical validation shows your product changes behavior, improves symptoms, or supports better health outcomes.

What it looks like:

  • Pilot studies with 50-100 users measuring specific outcomes (reduced pain scores, improved cycle regularity, increased healthcare engagement)

  • Pre/post surveys showing changes in knowledge, confidence, or symptom management

  • Partnerships with clinics or health systems testing your product in real-world settings

When you need it: Once you plan to start scaling. Investors want to see you're not just building engagement but creating measurable health impact.

How to get started:

  • Partner with a university or research institution

  • Work with clinical advisors to design a small study

  • Define clear, measurable outcomes before starting 

  • Use validated scales where possible (pain scales, quality-of-life measures)

The limitation: Pilot studies are smaller and less rigorous than peer-reviewed research. They won't get you published, but they're enough to show investors you're serious about evidence.

Action step: Identify one measurable outcome your product should influence. Design a simple pre/post study with 50+ users. Even small-scale data with clear before-and-after results is valuable.

Type 4: Peer-Reviewed Published Research

Studies published in medical or scientific journals showing your product works.

Why it matters: Peer-reviewed research gives you credibility with healthcare providers, health systems, payers, and sophisticated investors. It signals independent validation by the scientific community and strengthens your competitive position.

What it looks like:

  • Randomized controlled trials (RCTs) comparing your product to standard care or control groups

  • Observational studies published in reputable journals

  • Meta-analyses or systematic reviews including your product

When you need it: When you're scaling and need institutional partnerships or reimbursement pathways.

Limitations: Peer-reviewed research takes time, money, and expertise. You'll need academic partners, ethics board approvals, and a rigorous study design.

Action step: Find an academic collaborator specializing in your clinical area. Many researchers are interested in studying digital health interventions; you need the right fit.

Type 5: Real-World Evidence (RWE) at Scale

Large-scale data showing your product works across diverse populations in real-world settings, not just controlled studies.

Why it matters: Real-world evidence proves your product doesn't just work in research studies’ it works when thousands of women use it in everyday life.

What it looks like:

  • Aggregated, anonymized data from thousands of users showing health outcomes

  • Health system partnerships demonstrating improved care quality or reduced costs

  • Registry or claims data showing impact on diagnosis rates, treatment adherence, or hospitalizations

When you need it: When scaling nationally or internationally, or pursuing reimbursement from insurance companies or large health systems.

Why it's powerful: RWE is what payers and large healthcare organizations want. It proves your product works at a population scale, not just for early adopters.

Limitation: You need significant scale (typically 10,000+ users) and robust data infrastructure. You must also navigate privacy regulations carefully.

Action step: Build data infrastructure early so when you reach scale, you can analyze outcomes across your user base. Work with health economists or outcomes researchers to design impact studies.

The Path Forward

You don't need all five types of evidence on day one. But you should know which type you need next and actively work toward it.

Evidence isn't a checkbox. It's how you prove your product works and why women should trust it.

Start where you are and build systematically.

Are you building a FemTech startup and need help with clinical positioning? Better Woman Health delivers weekly insights on credibility, clinical claims, and evidence-based content.

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