What follows is not a pitch: verifiable numbers, an open list of what we do not know, each risk priced by what it costs to test, and a model where you can move any parameter and watch it break.
Women's femtech is a mature market with billion-dollar valuations. The male side of the same subject belongs to no one: around 25 products, almost all under six months old, almost all with no reviews. Collected by hand through App Store and Google Play search in August 2026, with every row checked by opening the listing.
| App | Positioning | Ratings | Status |
|---|---|---|---|
| Selin | Cycle tracker with a partner mode | 1160 | 100,000 installs on Android, the only visible player |
| HerMood | Mood calendar for men | 0 | updates stopped the day after release |
| Phases | Period tracker for men | 5 | active |
| Attune | Period tracker for men | 1 | active |
| Wing Man | Understanding her cycle | 0 | no reviews since launch |
| HerPhase | Cycle tracker | 12 | active, plus a third party is holding a domain for launch |
These rows take ten minutes to check: search either store for period tracker for men and look at the last update dates.
Every abandoned competitor is built the same way: a reference guide describing the phases, plus a joke about dangerous days. People read that on install day and never come back, and with no return there is no habit and no revenue. We think this is a failure of the format, not of the subject.
Not a description of the phase, but three actions and three things to say, dated to today. The value is tied to the date, so tomorrow it refreshes.
The warning goes into the phone calendar a day ahead. The app reminds you it exists even when nobody opens it.
After six logs it shows her own hard days. The longer you use it, the more the history costs to lose.
One metric tests the hypothesis: day thirty retention. If it lands at the level of the abandoned competitors, then the problem is the subject and not the format, and that has to be admitted fast rather than covered up with a year of marketing.
This is not a forecast, it is a build-your-own: our assumptions are loaded as defaults, but you can swap any of them for yours and watch what happens to the economics. The model warns you when a value moves past what we can defend.
The model rests on four untested assumptions and one reputational condition. Each one costs less to test than being wrong would cost.
A man sees a word about periods on the store page and does not install, because it embarrasses him. The funnel then breaks at the first step, and nothing inside the app can make up for it.
If people open the app twice and forget it, the value is zero no matter how good the writing is. This is exactly what killed everyone before us, and we have no grounds to think we are smarter until the first data arrives.
One wave of discussion framed around control is enough to give the product a reputation it will not escape. The female audience decides the fate of a product built for men.
With a generous limit on AI breakdowns, one active user can cost more than he pays. This is exactly the case where growth kills the economics.
Apps about women's health go through extra review, and wording about how a person feels reads easily as a medical claim.
Flo and Clue already have a mode like this as a secondary feature. They could double down on it at any time and get the audience for free.
The product launched a few days ago, so there are more empty rows here than filled ones. The filled ones can be checked in public sources, and the empty ones are not padded with invented numbers.
| Metric | Value | How we'll get it, or where it came from |
|---|---|---|
| Apps in the niche | about 25 | manual search across both stores, August 2026 |
| Notable players | 1 | Selin, 100K installs on Android |
| Abandoned direct competitors | 4 | last update dates on their store listings |
| Languages in the product | 2 | Russian and English, full feature parity |
| Cost of an AI breakdown | capped | model and token limit are set on the server, not by the client |
| Installs and active users | no data | App Store Connect and Play Console, after the first release |
| Retention on day 7 and day 30 | no data | activation events are recorded from day one, we need the first hundred installs |
| Share of users who reach six logs | no data | event is already logged, waiting for volume |
| Price and payment model | not decided | subscription or one-time purchase, it affects the whole model above |
| Cost per install from ads | no data | first creative test, about a hundred dollars to find out |
| Reaction from women | no data | twenty interviews before scaling |
| Audience size in Russia and the US | no data | public data on men aged 25-45 in relationships |
The app in two languages, four screens, a cycle engine with five phases, warnings, export to the phone calendar, offline mode, install to the home screen.
Data sync with the server, AI breakdown through a closed proxy with caps on model, tokens and rate, funnel analytics, a log mode for the partner.
Our own domain and an app subdomain, a landing page in two languages, a referral link inside the product. App store publishing is the next step.
The most honest thing we can say at this stage: the hypothesis is framed so that a month and a hundred dollars can disprove it. If you want a closer look, write to us.