# Flo Health Financial Model

AI-powered women's health superapp covering cycle tracking, pregnancy, fertility, and menopause across the full female lifecycle.

- Canonical: https://finamodel.com/startups/flo-health
- Excel download: https://finamodel.com/startup-models/flo-health.xlsx
- Category: Health-tech
- Model type: SaaS ARR / Valuation
- Funding round: Series B

- Founded: 2021
- Geography: Global. HQ in UK; engineering in Belarus/Lithuania; active in US, Western Europe, Eastern Europe, LatAm, Africa, Asia. US is lead market (11% penetration of women aged 15–45) [DECK slide 3].
- Customer: B2B2C

## About the company

Flo Health is an AI-powered women’s-health app covering cycle tracking, pregnancy, fertility, and menopause. Its lifecycle proposition creates repeated reasons for users to engage as their health needs change over time.

The core revenue stream is Flo Premium, a B2C subscription sold through Apple and Google app stores. Reported ARR and subscriber data imply a blended annual ARPU near $83 before app-store commissions, with a future B2B2C benefits channel adding optionality.

The model should forecast MAUs, premium conversion, subscription ARPU, monthly churn, and store fees. Marketing, content, AI and product costs should sit below gross revenue, while employer-benefits contracts can be modelled as a separate expansion stream.

## What's included

- 5-year monthly revenue build with stage-appropriate growth assumptions
- Full P&L, headcount plan, and operating-expense schedule
- Cash-flow statement, runway, and burn-rate tracking
- Valuation via exit multiple with a DCF cross-check
- Returns analysis with MOIC and IRR
- Unit economics including CAC, LTV, payback, and cohort retention

## Product & value proposition

- Core: Period & cycle tracker, ovulation prediction, symptom logging.
- Lifecycle modes: Tracking Mode → Pregnancy Mode → Early Motherhood Mode → Menopause Mode (planned).
- Satellite products: Content Library, Courses on Health & Wellbeing, Secret Chats (anonymous community), Health Assistant (AI chatbot).
- AI/data layer: "Flo AI" ingests symptom logs, fitness data, social signals, wearables, surveys → builds a personal health profile per user; outputs cycle prediction, hormone predictions, disease signals (PCOS, endometriosis), content personalisation.
- Medical credibility: 80+ medical experts; content reviewed by leading European and North American medical schools.
- Privacy/security: Dedicated DPO and CISO (UK); ISO 27001/27701 in preparation.

## Market

US market funnel (all figures):
- TAM (current age group): 66M - total US female population aged 15–45.
- TAM + Menopause: 135M - total US female population 14+ (with planned menopause mode).
- PAM (potentially addressable): 56.1M (82% of US women 15–45 track cycles via any method).
- SAM (current addressable): 38.6M (58.5% use apps to track cycles).
- Current Flo US users: 7.1M (≈11% of TAM).
- Global MAU: 38M worldwide across iOS + Android as of December 2020.
- Global prospective users: 1.7B.

## Revenue model

- Primary: B2C subscription (premium tier "Flo Premium") sold via App Store (iOS) and Google Play (Android).
- Pricing: Not shown explicitly in deck. ARR of $58M on ~0.7M active subscribers implies blended gross ARPU of ~$83/year (≈$6.90/month).
- Store fee: Apple/Google take ~30% commission; all revenue figures in deck are gross (before store commission) unless noted otherwise.
- Planned B2B2C: Employee benefits channel targeted to represent 15% of revenue by YE 2023, with B2C at 85%.
- No ad revenue, in-app purchases, or marketplace revenue mentioned in deck.

## Traction & metrics

All as of December 2020:
- Total installs: >160M
- Organic installs: 66%
- MAU (WW, iOS + Android): 38M
- MAU US: 7M
- ARR: $58M (+120% YoY) - cash-based, VAT-exclusive
- Active subscribers: 0.7M
- App Store rank: #1 Health & Fitness iOS WW by installs; #4 by revenue (Source: AppAnnie, Dec 2020)
- Ratings: 3M+ ratings, average 4.8/5; breakdown: AppStore 2.68M ratings, Google Play 1.66M ratings
- US penetration: 11% of women aged 15–45
- Branded traffic (iOS, US): 42% organic branded, 34% organic non-branded, 24% paid
- Brand awareness: 56% of period app users are aware of Flo; 22% use Flo; #1 recalled brand for period trackers

Subscription count trend (iOS + Android):
- Dec 2019: 231K → Dec 2020: 726K (+214% in 12 months)
- Monthly progression: 231K, 243K, 260K, 286K, 309K, 334K, 363K, 399K, 434K, 472K, 530K, 623K, 726K

Paying subscriber share in MAU:
- iOS WW: 1.38% (Dec 2019) → 2.86% (Dec 2020)
- iOS US: 1.90% (Dec 2019) → 4.74% (Dec 2020)

Monthly gross subscription revenue (cash, VAT-exclusive):
- Jan 2020: $2.3M → Dec 2020: $4.9M
- Implied run-rate at Dec 2020: ~$58.8M gross annualised
- 2021 forecast (deck): Jan $4.2M → Dec $8.5M (full-year 2021 forecast ≈$72M implied from monthly trajectory)

MAU growth:
- Sep 2016 launch; reached 38M by Nov/Dec 2020. Consistent MoM growth throughout.

## Unit economics

No explicit CAC, LTV, or payback period stated in deck.

Derivable from deck data:
- Blended gross ARPU: ~$83/year
- Net ARPU (after ~30% store fee): ~$58/year
- Conversion rate (MAU → paying, iOS US Dec 2020): 4.74%
- Conversion rate (MAU → paying, iOS WW Dec 2020): 2.86%
- Organic install share: 66%, implying low blended CAC relative to pure paid-acquisition peers
- Annual subscription churn (target, year 2+): 20–25% relative churn per year (stated as target plateau, not current actuals)

## Competition / moat

Competitive positioning:
- Scatter plot (AppAnnie iOS WW, Dec 2020): Flo sits in the "Unicorns" quadrant - highest downloads among cycle-tracking apps, MAU well above 16.6M axis midpoint; no other cycle-tracking app is close. Competitors cluster in pre-growth / average-performer quadrants.
- Revenue: Flo is in the "Heavy Hitters" zone (high MAU + revenue above $1.96M/month threshold); closest revenue competitor in cycle-tracking is well below.

Stated moats:
- Brand: #1 recalled brand in category; 56% awareness among period app users.
- Data flywheel: Multi-year longitudinal health data per user; AI-trained on proprietary dataset.
- Medical credibility: 80+ expert reviewers; academic research partnerships.
- Lifecycle lock-in: Modes designed to keep users across 40+ years (tracking → pregnancy → menopause).
- Organic growth: 66% organic installs; 42% branded search - low dependency on paid UA.

Named competitors: Not explicitly named. Category competitors implied (other cycle-tracking and health/fitness apps on AppAnnie scatter).

## Team & funding ask / use of funds

Team:
- 270+ employees as of December 2020.
- Breakdown: 45% Product & Engineering, 25% Content/Medical/Partnerships, 18% Sales & Marketing, 12% Administration.
- International: UK (HQ/management), USA, Netherlands, Cyprus, Belarus, Lithuania.
- Avg engineering experience: 10 years.
- Tech stack: AWS/EKS, Kubernetes, Kafka, PostgreSQL, Redis, Python, Kotlin, Swift, TensorFlow, PyTorch, Spark, CatBoost, Amazon SageMaker.

Current valuation: $0.5B.

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## Recommended financial model

- **Archetype + why:** Subscription ARR model with freemium funnel. Revenue is 100% recurring subscription, driven by MAU growth × conversion rate × ARPU. This is a classic mobile freemium → premium subscription model analogous to a SaaS ARR model but with app-store gross/net mechanics. From 2023 onward a B2B2C revenue stream (employee benefits) should be modelled as a separate cohort with different ARPU and sales cycle.

- **Forecast horizon & granularity:** Monthly for Year 1 (2021 actuals/forecast already in deck); quarterly for Years 2–3 (2022–2023 targets in deck). Annual summary through 2025 for terminal / exit value context.

- **Key drivers & assumptions:**

| Driver | Seed value |
| -- | -- |
| MAU WW (Dec 2020) | 38M |
| MAU US (Dec 2020) | 7M |
| MAU WW target YE 2021 | >52M |
| MAU WW target YE 2023 | >115M |
| Active subscribers (Dec 2020) | 0.7M |
| Active subscribers target YE 2021 | >1.4M |
| Active subscribers target YE 2023 | >10M |
| ARR (Dec 2020, gross, cash, ex-VAT) | $58M |
| ARR target YE 2021 | >$103M |
| ARR target YE 2023 | >$400M (profitable) |
| YoY ARR growth (2019→2020) | +120% |
| Monthly gross subscription rev, Dec 2020 | $4.9M |
| Monthly gross sub rev, Dec 2021 (forecast) | $8.5M |
| iOS WW paying/MAU conversion (Dec 2020) | 2.86% |
| iOS US paying/MAU conversion (Dec 2020) | 4.74% |
| Organic install share | 66% |
| App store fee (Apple/Google) | 30% |
| Blended gross ARPU/year | ~$83 |
| Annual sub churn (steady-state, year 2+) | 20–25% |
| Annual sub churn (year 1, new cohorts) | 40–50% |
| Gross margin (after store fees, hosting, content) | 70–75% |
| S&M as % of revenue | 18–22% |
| R&D as % of revenue | 25–30% |
| G&A as % of revenue | 8–12% |
| B2B2C revenue share (YE 2023 target) | 15% |
| MAU → subscriber conversion, incremental improvement | +0.1–0.2pp per quarter (WW) |

- **Scenarios (Base / Bull / Bear):**
  - Flex variables: MAU growth rate, conversion rate (free→paid), ARPU (pricing power), churn, store fee rate, B2B2C ramp speed.
  - **Base:** Hits deck targets - $103M ARR YE 2021, $400M ARR YE 2023; conversion reaches ~3.5% WW by YE 2023.
  - **Bull:** Faster menopause-mode TAM expansion + aggressive B2B2C adoption push ARR to $500M+ by YE 2023; US conversion exceeds 7%.
  - **Bear:** MAU growth stalls (competitive or regulatory pressure on data privacy); conversion stays below 3% WW; ARR $200–250M by YE 2023; profitability delayed.

- **Required sheets / outputs:**
  1. **Assumptions** - all drivers centralised.
  2. **MAU Cohort Build** - monthly new installs, churn/reactivation, cumulative MAU by geography (WW, US, Other).
  3. **Subscriber Funnel** - MAU × conversion rate = paying subscribers; split iOS / Android.
  4. **Revenue Build** - subscribers × monthly ARPU × (1 – store fee) = net revenue; gross revenue line separate; B2B2C as additive stream from 2022.
  5. **Cohort Retention** - annual subscriber cohorts with year-1 and year-2+ churn rates to model NRR and LTV.
  6. **P&L (Annual + Quarterly)** - gross revenue, store fees, net revenue, COGS (hosting, content, medical), gross profit, S&M, R&D, G&A, EBITDA.
  7. **KPI Dashboard** - MAU, paying subs, ARR, conversion %, ARPU, churn, LTV/CAC ratio (where CAC estimable).
  8. **Targets vs. Actuals Tracker** - deck slide 26 targets vs. model outputs.
  9. **Valuation** - ARR multiple exit (SaaS comps; growth-stage femtech); implied equity value at $7B target.

## Frequently asked questions

### Is the Flo Health financial model free?

Yes. The Flo Health model is a free Excel download with live formulas.

### Can I change the assumptions?

Yes. The workbook is editable and its live formulas recalculate when assumptions change.