Where Do I Fit In? The Missing Middle in Women’s Health Tech

Women’s health data seems to be caught in a fascinating tension:

🔹 Personalization vs. Context

1️⃣ Some companies are capturing personalized data for the first time — which is amazing. But users often ask: “Cool… but how do I compare to others?” The broader dataset doesn’t exist yet.

2️⃣ Others are using population-level insights (fertility, menopause trends, etc.), but users ask: “Where do I fit into this?” The insights aren’t personal enough to feel actionable.

3️⃣ And a few are reaching scale — combining personal data and large cohorts to offer both insight and context. That’s the sweet spot.

Here’s how I’m seeing the space shake out:

(1) Context-first, with early-stage personalization:
These companies — @Pomelo, @Maven, @Modern Fertility, @Tia Health — lead with rich data and trend insights, often using segmentation models. The next frontier might be moving from archetypes to true individual-level insights.

(2) Personalized-first, but still building broader context:
@Evvy, @Reya — focusing on individual data through software or hardware, but still in early stages of building scalable benchmarks and cohorts.

(3) Bridging both — large personalized datasets with ecosystem context:
@Oura, @WHOOP, @Garmin, @BloomLife, @Natural Cycles, @Clue, @FloHealth — companies that have scaled personalized tracking and can offer broader insights across their user base.

🙋🏽‍♀️ If you're at a start up building in category (1) or (2), how are you thinking about scaling personalization + context? Are you down for a quick chat, I’d love to jam on this with you.

🌶️ And in a world where data is the strongest moat, how are we balancing the need to build and share large datasets while noting the power of data ownership to a startup?

#WomensHealth #FemTech #HealthData #PersonalizedHealth #ProductThinking