# Incredible Health Financial Model

B2B marketplace that flips the nurse-hiring funnel - hospitals apply to pre-screened RN candidates instead of the other way around.

- Canonical: https://finamodel.com/startups/incredible-health
- Excel download: https://finamodel.com/startup-models/incredible-health.xlsx
- Category: Health-tech
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $15M
- Founded: 2020
- Geography: California (150+ hospitals) [DECK slide 7]; nationwide expansion stated as next phase [DECK slide 7]. Headquartered San Francisco, CA [DECK slide 2].
- Customer: B2B2C

## About the company

Incredible Health is a nurse-hiring marketplace where hospitals apply to pre-screened registered-nurse candidates. It reverses the usual hiring funnel, helping clinical employers access scarce talent while giving nurses more control over opportunities.

The platform monetises hospital access to candidates, so success depends on both employer demand and reliable nurse supply. Repeat hiring, specialty mix, time to placement, employer retention, and candidate engagement determine marketplace liquidity and revenue durability.

The model forecasts hospital customers, candidate supply, nurse placements, fee per placement, repeat hiring, and marketplace operations. It includes employer sales, candidate acquisition, placement support, take rate, operating headcount, gross margin, cash burn, and runway.

## 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

- Candidate-first marketplace: nurses create profiles, hospitals browse and send interview requests - inverting the traditional job-board model.
- Platform delivers hire in <30 days vs 82-day national average; claims 25× efficiency vs traditional job boards.
- Rich hospital profiles with staffing quality signals, specialty rankings, patient-experience ratings, and employer branding - designed to help nurses evaluate fit before accepting.
- NPS from both talent and employers: 86+.
- Key insight driving moat: 68% of RN candidates accept their first offer; 61% do so even when later offers carry higher pay - speed and match quality matter more than comp maximisation.
- Stanford Health Care CHRO testimonial: consistently hires in permanent roles in under three weeks.

## Market

- Projected US nursing shortage: 1 million nurses short by 2024.
- Average time to hire a nurse nationally: 82 days.
- No explicit TAM/SAM/SOM dollar figures in deck.
- Implied addressable market: ~6,000+ hospitals in the US; deck focuses on IDNs, academic medical centres, community hospitals.

## Revenue model

- Not explicitly stated in deck; no pricing slide.
- Business model described as "Marketplace Technology" - standard marketplace models in this category charge hospitals a placement fee (percentage of first-year salary or flat per-hire fee) and/or a subscription/seat licence for access to the candidate pool.
- Revenue model is likely per-placement fee from hospitals (common for permanent healthcare staffing marketplaces) possibly layered with a SaaS subscription for platform access. Rationale: deck emphasises "permanent nurses," speed-to-hire, and hospital-side UX - all consistent with per-hire monetisation.

## Traction & metrics

- Customers: 150+ hospitals in California, including named enterprise accounts: Stanford Health Care, UCSF Medical Center, UC Davis, Cedars-Sinai, HCA, Providence, Dignity Health/CommonSpirit, Rady Children's, Cook Children's, Baylor Scott & White, and others.
- Time to hire: <30 days vs 82-day national average
- Efficiency vs job boards: 25×
- NPS (talent + employers): 86+
- Candidate acceptance rate (1st offer): 68%
- Candidate acceptance rate (1st offer even when later offers pay more): 61%
- No revenue figures, ARR, GMV, or growth rate disclosed in deck.
- Founded: 2017

## Competition / moat

- Competitive framing: 25× more efficient than "traditional job boards" - implies primary displacement target is legacy boards (Indeed, LinkedIn, niche nursing boards).
- Moat sources (from deck): proprietary matching technology, candidate-centric UX (employer applies to nurse rather than reverse), rich nurse preference data, first-mover hospital relationships in California, NPS/brand reputation among RN community.
- No direct competitor named; no comp grid shown.

## Team & funding ask / use of funds

- Team described as MDs, RNs, software engineers, marketers, designers; healthcare and matching-technology experts.
- Backed by "top tier Silicon Valley investors" - marketplace and matching technology experts.
- No named investors, no funding history, no ask amount, no use-of-funds breakdown in deck.

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## Recommended financial model

**Archetype + why:**
Marketplace per-placement revenue model with optional SaaS subscription layer. This is closest to a "staffing marketplace" archetype - revenue driven by volume of nurse placements × average fee per placement, plus potentially a recurring platform access fee per hospital. The candidate-side is free. Model should capture both placement GMV and net revenue (take rate).

**Forecast horizon & granularity:**
- 3–5 year annual model (suitable for Series A/B fundraise context).
- Year 1–2 quarterly, Years 3–5 annual.
- Monthly granularity not warranted without unit-level pipeline data.

**Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Active hospital customers (start) | 150 |
| Avg nurses hired per hospital per year | 20–40 hires/year |
| Avg placement fee per hire | $5,000–$8,000 |
| Platform/SaaS fee per hospital per month | $0–$2,000 |
| Candidate take rate | 0% |
| Time to hire | <30 days |
| NPS (demand-side proxy for churn) | 86+ |
| Hospital customer growth rate (CA) | 20–40% YoY |
| National expansion ramp | Year 2 |
| Gross margin | 60–75% |
| S&M spend as % of revenue | 25–35% |
| R&D spend as % of revenue | 15–20% |
| G&A spend as % of revenue | 8–12% |

**Scenarios (Base / Bull / Bear - which variables flex):**
- **Base:** 150 hospital clients growing 30% YoY; 25 hires/hospital/year; $6,500 placement fee; national expansion begins Y2.
- **Bull:** Hospital growth 50% YoY; 35 hires/hospital; layered SaaS fee of $1,000/month; faster national ramp.
- **Bear:** Growth slows to 15% YoY; hires/hospital drops to 15 (hospitals cautious, budget cuts); placement fee compresses to $4,500 under competition.
- **Key flex variables:** hires-per-hospital, placement fee, and hospital customer count are the three levers with the most P&L sensitivity.

**Required sheets / outputs:**
1. Assumptions dashboard (all inputs in one place; colour-coded)
2. Hospital customer build (cohort by entry year, churn rate, active count)
3. Revenue build (placements × fee + optional SaaS)
4. P&L (gross profit, EBITDA)
5. Headcount model (sales, engineering, ops)
6. Cash flow / runway (given no funding ask disclosed, model to show breakeven path)
7. Scenario toggle (Base / Bull / Bear)
8. KPI summary: hospitals, nurses placed, GMV, revenue, take rate, NPS proxy

## Frequently asked questions

### Is the Incredible Health financial model free?

Yes. The Incredible 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.