WD
Well Dot Financial Model

Health-tech Startup Financials (Free Excel Download)

AI-powered, consumer-grade health engagement platform sold B2B to employers/health plans to improve member health and reduce healthcare costs.

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About this model

Well is an AI-powered health-engagement platform sold to employers and health plans. It uses consumer-grade experiences to improve member behaviour and reduce healthcare costs for institutional buyers, making sustained engagement central to its value proposition.

The commercial model depends on client wins, covered members, PMPM fees, adoption, and renewal. Outcomes incentives can create additional upside or risk, while implementation and integration influence how quickly an employer or plan can make the service available to eligible populations.

The model forecasts clients, covered members, PMPM fees, engagement, outcomes incentives, implementation, and renewal. It includes member-support and technology costs, enterprise sales, customer success, gross margin, operating cash flow, cash burn, and runway.

A turnkey financial model

Live formulas, no hardcoded values

Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.

All assumptions in one tab

Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.

Statements always balancing

For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.

Distinct schedules for clarity

Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.

No hidden macros or external links

There are no unexplained external workbook links or macros to undermine auditability or portability.

Changes flow through the model

Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.

About Well Dot

welldot.com
Read the pitch deck
Well Dot pitch deck cover
View on makeslides.com
Total raised
$40.0M
Funding round
Series A
Founded
2020
Category
Health-tech
Customer
B2B2C
Geography
Not explicitly stated

How to build a detailed financial model for Well Dot

A complete walkthrough of the business, drivers, and assumptions behind the downloadable Well Dot model - distilled from its pitch deck and publicly available information.

Product & value proposition

Well is a mobile-first health engagement platform that delivers personalized, AI-orchestrated health journeys, concierge support (Health Guides + nurses), virtual health services (telehealth, behavioral health, Rx savings), and incentives/rewards to drive member action.

Key differentiators:

  • Consumer-grade UX applying Netflix/Amazon/Spotify personalization principles to health
  • Clinically-robust content: 200+ distinct interventions across 50+ medical/behavioral health topics
  • AI Health Engine: ingests EHR + member data → scores health/cost opportunity → orchestrates personalized engagement → delivers incentives → closed feedback loop
  • Whole-health coverage: physical, mental, condition management, and wellness in one platform

ROI for buyers comes from four levers: preemptive engagement of high-risk members, driving utilization of proven programs, sustaining engagement in clinical programs, and "swimming upstream" on cost.

Revenue model

Not explicitly stated. Inferred from B2B model and standard digital health market norms:

  • Per-member-per-month (PMPM) fee paid by employer or health plan, covering all enrolled members - the dominant pricing model for wellness/engagement platforms in this space.
  • Buyers are self-insured employers and/or health plans (indicated by language around "employer benefits," member populations, and ROI framing directed at employers).
  • Potential upsell for add-on virtual health services (telehealth, BH, condition management) layered on top of base engagement platform.
  • No ACV, PMPM rate, or contract structure figures are shown.

Traction & metrics

  • Illustrative member cost savings opportunity cited: >$6K per member per year (Mia example, explicitly labeled "Illustrative")
  • App UI shows stats: 1,470 and 8,400 (context unclear - likely steps or points in the UI mockup, not company-level KPIs)
  • No revenue, ARR, customer count, member lives covered, growth rates, or NPS figures are disclosed in the deck.

Competition / moat

Not explicitly addressed as a competitive landscape slide. Moat articulated through differentiation:

  • Proprietary AI Health Engine with closed feedback loop
  • 200+ clinical interventions built in-house by physicians, psychologists, and public health experts
  • Consumer-grade personalization engine (behavioral economics + dynamic incentives)
  • Depth of integrated whole-health coverage vs. point solutions

Team & funding ask / use of funds

Recommended financial model

  • Archetype + why: B2B SaaS / health-tech PMPM model. Revenue scales with number of employer/health-plan customers × covered member lives × PMPM rate. This is the standard archetype for digital health engagement platforms sold to self-insured employers. A 3-statement model is appropriate if funding/capitalization context emerges; otherwise a revenue/margin build is sufficient for an early-stage operating forecast.
  • Forecast horizon & granularity: 5 years (Year 1–2 monthly, Year 3–5 annual). Monthly granularity needed in early years to track member ramp and churn within employer accounts.
  • Key drivers & assumptions:
DriverValue
PMPM rate (base platform)$3–$8 PMPM
Add-on virtual health PMPM$1–$3 PMPM
Average employer contract size (lives)2,000–10,000 members
Gross margin60–75%
Member churn / contract renewal rate80–90% annual renewal
S&M as % of revenue25–35%
R&D as % of revenue20–30%
G&A as % of revenue10–15%
  • Scenarios (Base / Bull / Bear - which variables flex):
  • Bear: Slow logo adds, low PMPM rate (competitive pricing pressure), 65% gross margin (more human concierge reliance)
  • Base: Moderate logo growth, $5 PMPM blended, 70% gross margin, 85% renewal
  • Bull: Faster logo adds, upsell to virtual health add-ons lifts blended PMPM to $8+, 75% gross margin, 90%+ renewal
  • Required sheets / outputs:
  1. Assumptions - PMPM rate, logo ramp, avg. lives/logo, gross margin, opex ratios
  2. Revenue Build - logos × lives × PMPM by month/year; separate base + add-on tiers
  3. P&L - Revenue → Gross Profit → EBITDA → Net Income
  4. Headcount & Opex - Health Guides/nurses (COGS), S&M, R&D, G&A
  5. Cash Flow & Runway - burn rate, cash balance, months of runway
  6. KPI Dashboard - ARR, net revenue retention, lives covered, PMPM, gross margin %, burn multiple

Frequently asked

Is the Well Dot financial model free?+

Yes. The Well Dot model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.

What's included in the model?+

A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.

How was this model built?+

It was built from Well Dot's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.

Can I change the assumptions?+

Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.

Have more financial modelling questions? Contact us

Alex Tapio, ex-Deloitte financial modelling expert

Created by ex-finance professionals

Hey, I’m Alex and I created Finamodel.

Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.

Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.

I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.

Having a template library on hand cuts a first build from hours to minutes.

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