# Voi Financial Model

European e-scooter operator competing for city-awarded exclusive licenses across 40+ cities in 12 markets.

- Canonical: https://finamodel.com/startups/voi
- Excel download: https://finamodel.com/startup-models/voi.xlsx
- Category: Logistics/Mobility
- Model type: Unit-economics / DTC
- Funding round: Series C
- Funding: $160M
- Founded: 2020
- Geography: Europe - Sweden, Portugal, Norway, France, UK, Spain, Denmark, Finland, Germany, Switzerland (12 markets, 40+ cities). [DECK slide 2]
- Customer: B2C

## About the company

Voi operates e-scooters in European cities under city-awarded licenses. Its performance depends on winning permits, building fleet density, and managing utilisation.

The model should build city licences, scooters deployed, and rides per scooter into revenue per ride. It should distinguish the economics of each city because permits and fleet density determine available supply.

Forecast fleet capex, repairs, and regulatory fees alongside ride revenue. This shows how utilisation and city-awarded licences affect the returns from an expanding European e-scooter fleet. The plan should explicitly link every licence award to deployed scooters, fleet density, utilisation, and required regulatory fees for each city.

## 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

- E-scooter sharing platform accessed via consumer app; ride-hailing model billed per ride or via monthly pass.
- Competes for exclusive or protected city tenders; differentiates on sustainability, safety technology, and city partnership model.
- Hardware: V3X and V2 scooter generations; V3X has 5–6 year lifetime (8x improvement over first gen), with swappable batteries and <1m GPS accuracy.
- Software: fleet placement optimisation (data science + heuristics), geofencing, slow zones, helmet detection, online driving school.
- Emissions: <20g CO2/km (life cycle), comparable to public transport.

## Market

- No explicit TAM/SAM/SOM figures in deck.
- Demand context: mobility volume in key European cities still only at ~60% of normal as of Sep 2020 post-Covid, implying significant recovery headroom.
- Structural tailwinds cited: anti-car agenda, urbanisation, time-saving, preference for personal mobility, overloaded public transport.
- City licensing trend: increasing number of cities moving from free-entry to capped to protected/exclusive models - Voi frames this as a structural market quality improvement.

## Revenue model

- Pay-per-ride gross charges (scooter rental fees).
- Monthly pass and loyalty products (mentioned as differentiator).
- Revenue netting: contra revenues deducted include VAT, payment fees, credits, and failed/fraud payments.
- Fleet size per city shown as large as ~10,000 scooters (Oslo, Stockholm, Hamburg).
- Unit of revenue modelled per scooter per operating day (EUR).

## Traction & metrics

- 5m+ registered users
- 30M+ total rides
- 40+ cities
- 12 markets launched
- ~$0 CAC
- Company founded August 2018 (Stockholm pilot); "Leader in European micromobility" by October 2020
- Revenue recovery (gross charges, MEUR) Jan–Aug 2020: approx Jan ~2.2, Feb ~2.2, Mar ~2.0, Apr ~1.0, May ~2.7, Jun ~5.3, Jul ~7.0, Aug ~8.5
- EBITDA breakeven achieved ~Jun 2020
- Rides/day by city (Aug 2020, Voi vs peers): Oslo 5, Stockholm 5, Copenhagen 3, Hamburg 3, Gothenburg 3 - Voi #1 in all
- Market position: #1 in Nordics, #1 in UK & Ireland, #1–2 in Germany & Switzerland, #4 in France (by market share), #1–2 in Italy
- Tender wins: #1 Nordics, #1 UK & Ireland, #3–4 France, #1–2 Italy
- 49% share of total scooters in protected/exclusive European markets vs 18% (Peer 1), 15% (Peer 2), 11% (Peer 3), 6% (Peer 4)
- Fleet protected/exclusive mix: Summer 2020 = 11% protected+exclusive; Fall 2020 = 45%; projected Summer 2021 = 55%
- Q3 2020 market-level EBITDA margins (pre-HQ, pre-capex): range from 73% (top city) down to -13% (weakest); majority positive

## Unit economics

All figures per scooter per operating day (EUR), across 5 anonymised cities:

| Line item | City 1 | City 2 | City 3 | City 4 | City 5 |
| -- | -- | -- | -- | -- | -- |
| Fleet gen | V3X | V3X | V3X | V2 | V3X |
| Gross revenue | 16.8 | 12.7 | 12.4 | 8.3 | 7.7 |
| (-) Contra | 4.4 | 3.3 | 3.4 | 1.7 | 2.0 |
| (-) Charging & logistics | 2.3 | 1.5 | 2.3 | 2.2 | 2.0 |
| (-) Repairs | 0.8 | 0.9 | 1.4 | 0.8 | 0.5 |
| (=) Scooter FCF | 9.3 | 7.1 | 5.2 | 3.6 | 3.1 |
| (-) Depreciation | 1.0 | 1.0 | 0.9 | 0.9 | 0.9 |
| (-) Overhead | 0.8 | 0.8 | 0.8 | 0.8 | 0.8 |
| (=) Contribution | 7.5 | 5.3 | 3.5 | 1.9 | 1.4 |
| % margin | 45% | 42% | 28% | 24% | 18% |
| Days to payback | 64 | 84 | 114 | 144 | 193 |

- CAC: ~$0 (app-led, no paid acquisition)
- City-level EBITDA margins (Q3 2020, pre-HQ, pre-capex): 73% best to -13% weakest; majority of ~30 cities are positive

## Competition / moat

- Named peers (unlabelled in data but implied): Tier, Lime, Bird, Dott - European players win ~80% of tenders vs US operators.
- Voi moat: (1) exclusive/protected city licenses (hard to dislodge once won); (2) fleet efficiency (#1 rides/day in every key market); (3) sustainability/safety track record favoured by city councils; (4) proprietary fleet placement data science; (5) loyalty/pass products.
- Revenue quality framing: 45% (Fall 2020) and projected 66% (Summer 2021) of fleet in protected/exclusive markets - higher revenue certainty than peers in free-entry markets.
- Track record of exclusive license wins: Oslo (~10,000), Stockholm (~10,000), Hamburg (~10,000), Birmingham (10,000), multiple UK cities.

## Team & funding ask / use of funds

- Strategic financial model pillars stated: access to scale debt financing (fleet financing) as a key competitive lever.

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## Recommended financial model

- **Archetype + why:** Fleet-based unit economics P&L / operating model. Voi is a capital-intensive scooter operator where value creation flows from: (a) fleet size deployed × rides/scooter/day × net revenue per ride, less (b) per-scooter opex (charging, logistics, repairs, depreciation) and (c) fixed HQ overhead. This is closest to a rental/mobility fleet P&L, not a SaaS ARR model. A city-level roll-up with blended fleet economics is the right structure.

- **Forecast horizon & granularity:** 3 years (2021–2023); monthly for Year 1, quarterly for Years 2–3. City-level detail for top 5–8 markets; rest in aggregate "Other" bucket.

- **Key drivers & assumptions:**
  - Total fleet size (scooters deployed): implies 40+ cities, Oslo/Stockholm/Hamburg at ~10,000 each; total fleet size not stated → start at ~50,000 scooters (Oct 2020 implied by city disclosures), grow 30–40% p.a. as new tenders won
  - Fleet utilisation rate (% of fleet ready/day): 80–85% ready rate; V3X reliability implied by "no broken scooters" policy
  - Rides per ready scooter per day: 3–5 rides/day in key markets (Aug 2020); blended 3.5 base, rising to 4.0 as mix shifts to high-utilisation licensed cities
  - Gross revenue per ride (EUR): implied from unit economics table - City 1 gross rev 16.8 EUR/scooter/day ÷ ~5 rides/day ≈ EUR 3.36/ride; City 5 = 7.7 ÷ 3 ≈ EUR 2.57/ride; blended ~EUR 3.00/ride base case, price trend flat (regulated markets limit pricing power)
  - Contra rate (% of gross): 20–26% across cities (4.4/16.8 to 2.0/7.7); 22% blended
  - Charging & logistics cost per scooter per day (EUR): EUR 1.5–2.3; EUR 2.0 base, declining 5% p.a. with operational leverage
  - Repairs per scooter per day (EUR): EUR 0.5–1.4; EUR 0.9 base for V3X fleet, declining with hardware maturity
  - Depreciation per scooter per day (EUR): EUR 0.9–1.0; EUR 1.0, based on ~5–6yr scooter life at ~EUR 1,800–2,000 asset cost
  - Overhead per scooter per day (EUR): EUR 0.8; this is city-level overhead only; HQ cost loaded separately as fixed cost base growing with headcount
  - Capex (fleet investment): scooter purchase cost ~EUR 1,800–2,000 each (V3X gen, estimated from market data); financed via scale debt (deck flags this as strategic goal); model both equity-financed and debt-financed scenarios
  - Protected/exclusive fleet mix: 45% Fall 2020 → 66% Summer 2021 → trending further; 70% by end-2021, 80% by end-2022
  - Seasonality: slide 3 shows clear trough in Apr 2020 (COVID-related, not pure seasonality); 15–20% revenue reduction in Q1 vs Q3 for Nordic/Northern European markets
  - CAC: ~$0; model as zero paid acquisition; nominal marketing budget for brand/PR only

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Base: rides/day = 3.5, fleet growth 35% p.a., blended net rev/ride EUR 2.35, HQ overhead growth 20% p.a.
  - Bull: rides/day = 4.5 (higher licensed city utilisation), fleet growth 50%, additional tender wins accelerate protected mix to 85% by 2022
  - Bear: rides/day = 2.5 (slower market recovery, competitor wins tenders), fleet growth 20%, pricing pressure in free-entry markets compresses net rev/ride to EUR 2.00

- **Required sheets / outputs:**
  1. Assumptions - all drivers listed above with scenario toggle (Base/Bull/Bear)
  2. Fleet build - scooters deployed by market/city tier, monthly
  3. Revenue build - rides × net rev per ride, by city tier
  4. City-level P&L - gross charges, contra, charging/logistics, repairs, scooter FCF, depreciation, overhead, contribution per scooter/day and in aggregate
  5. HQ overhead - headcount and fixed cost schedule
  6. Consolidated P&L - revenue, gross profit, EBITDA, EBIT (monthly Yr 1, quarterly Yr 2–3)
  7. Capex & fleet financing - scooter purchases, debt drawdown/repayment, interest
  8. Cash flow statement - operating CF, capex, net cash, runway
  9. Unit economics summary - payback days, contribution margin %, by city cohort vintage
  10. Dashboard - key KPIs: fleet size, rides/day, net rev/scooter/day, EBITDA margin, cash runway

## Frequently asked questions

### Is the Voi financial model free?

Yes. The Voi 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.