How Flo grows

Flo's user acquisition team noticed Meta ads with a narrative about enhancing your sex life gaining traction, performing well even into the existing generic funnel. Product dissected it as an unexplored user need: added a separate user goal 'enhance sex life' and enriched the web onboarding with questions tailored to it, so users clicking that ad land in a funnel that acknowledges the ad they came from and continues the narrative seamlessly.

In Flo's perimenopause web onboarding funnel (users arriving from ads promising to explain their phase), added a step to determine the user's perimenopause phase. Test 1: almost 10% drop in conversion. Test 2, after design guesses: same drop. A post-mortem segmenting the audience found the questions were hard to answer and almost 75% of users got no phase, seeing an 'Oops, sorry, we were not able to pinpoint your perimenopause phase' screen. Test 3: question rewritten with the medical team, logic slightly changed, and users who still can't be classified just go to the next section with no failure message.

With 200K+ installs a day and ~70M MAU, Flo uses a 'brute-force' approach: create large enough test groups, put many price points into test against the initial price, and decide separately for each region. The success metric is the effect on average revenue per user, not conversion, because price moves trial conversion, trial activation and subscription retention together. Example: a price half as high can triple retention and give much higher overall ARPU.

Weekly syncs between Flo's marketing and product teams. Practice: every change product introduces and every change marketing makes to ad campaigns is shared, even if it seems not to matter, because you never know which insight the other team will value. Mike frames it as the fix for the usual tension (marketing says the funnel doesn't convert, product says marketing brings the wrong audience).

Flo re-analyzes shipped experiments 3, 6 and 12 months after rollout to see whether a reported win was a business win. Year-end exercise: add up the relative uplifts reported from tens of winning experiments (5-10% each) and ask whether the business grew by that much, i.e. whether the effects compounded.

Flo positions itself as a lifelong partner: core needs such as cycle tracking are free, and the team avoids intrusive paywalls and doesn't push to monetize on day one or day seven. It tracks how needs evolve across life stages (understanding periods, trying to get pregnant, following pregnancy, perimenopause) and, when it sees something of value beyond the core offering, approaches users with a tailored product offering at that time, converting free users 3, 6 or 12 months later.

Common practice at Flo: after a win, run a blackout test that removes the new element. For the perimenopause phase step (a 23% win that seemed too good to be true), a fourth iteration removed the new section; it lost, proving the uplift. Blackouts are also used to test removing existing onboarding steps, since funnels tend to keep accumulating steps.

Do not derive regional prices from the Big Mac Index or from Netflix/Spotify local prices: your app's buyers in a country are not the average person there. In emerging markets like Brazil, iOS users are the richer part of society, so iOS prices can sit well above what an index predicts, while Android prices must be much lower. Flo finds optimal prices per country and per platform; regional prices are almost always below the US, and in rich countries (US, UK) the optimal Android price is only ~15-20% below iOS, while in countries like Brazil the iOS/Android gap is very large. Prices are set by testing rather than any benchmark, since age mix, platform mix, product type and culture all shift the optimum.

At the higher Brazil price there were too few conversions to feed ad networks' optimization and compete in auctions. After the price cut, conversions became frequent enough to send sufficient signal to the networks; Flo found a 'hot spot' for paid acquisition and significantly increased paid UA volume in Brazil, profitably. Networks and spend not given.

In countries where women mostly cannot pay (no credit cards, no money), where 99%+ of users would never convert, Flo opens the premium features for free instead of keeping them behind a paywall. Done for mission reasons, not business ones; Flo communicates it as a pro-social campaign. Now free in more than 50 countries, with 20M+ subscriptions gifted (vs ~10M sold).

Offer a free period-tracking product to users from their mid-teens and keep serving them free for as long as they need, building a data layer over their whole life (18 to 35-50, into perimenopause and menopause). Add paid modules (e.g. perimenopause, menopause, partner features) inside Flo Premium that users subscribe to when a life stage makes them relevant. Investor thesis: each new module widens the surface where the 60M MAU find a reason to subscribe; capturing 1-3% per module means hundreds of millions in revenue.

Flo's web onboardings still offer free trials instead of asking users to pay upfront, which delays the real conversion event. To call experiments early, the team picks proxy events that correlate with future user value and are informative about outcomes 30-40 days out. Mike notes this needs lots of historical data; early-stage startups have to rely on gut feeling.

Product leaders from several companies told Flo a paywall pattern had given them a 10% conversion uplift. Flo implemented exactly the same thing, pixel to pixel. Mike's takeaway: borrow the idea, not the solution, and understand the underlying problem first.

Tested the Blinkist-style paywall (reassuring users they will be reminded before the trial ends, to make starting a free trial feel safe) at both Loóna and Flo.

Partner Mode is one of Flo's most requested features, used by more than 2 million pairs. Flo added it into the onboarding funnel expecting a conversion boost.

Rather than competing as a general health app, narrowed its category to women's health / menstrual cycle tracking so it could confidently claim to be #1 in that niche. Paired with strong metrics, funnels and testing.

Flo's team ran over 100 experiments a month. Guest advises small apps to start testing pricing, paywall UI/UX, color schemes and fonts early and often, pushing experiment count up.

Reduced the Brazil subscription price 'really significantly' (exact level not given), chosen through the regional price-testing process. The lower price raised conversions and improved retention.

Existing subscribers upgrade to a more premium tier and buy features not included in their first purchase, so each cohort's revenue grows after year one.

Flo worked with GP Bullhound to raise a growth round, going out for $100M. Multiple investors competed and the round was doubled to $200M, led by General Atlantic. Pitch centered on the freemium data layer and module expansion thesis.

Mentioned right after the Blinkist paywall failures at Loóna and Flo: 'the same thing with the trial toggle, it worked for some teams'. No details on the test.