# WhereIsMyTransport Financial Model

B2B mobility data platform mapping formal and informal public transport networks in emerging-market cities, licensing city data to governments, corporates, and NGOs.

- Canonical: https://finamodel.com/startups/whereismytransport
- Excel download: https://finamodel.com/startup-models/whereismytransport.xlsx
- Category: Logistics/Mobility
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $27.8M
- Founded: 2020
- Geography: Emerging markets - Africa, Latin America, Asia, Middle East; HQ presence in London, Cape Town, San Francisco, Mexico City [DECK, slide 10].
- Customer: B2C

## About the company

WhereIsMyTransport maps formal and informal public transport networks in emerging-market cities. It licenses mobility data to governments, corporates, and NGOs.

The model should translate city datasets and enterprise contracts into data-subscription ARR, while separating recurring licences from project services. Mapping cost should be tied to expansion into additional city networks.

Forecast expansion, churn, and project services alongside subscription revenue. This makes clear how coverage of formal and informal transport systems supports contracts across governments, corporates, and NGOs. Retain each city dataset as the basis for contracts and map the cost of expanding that coverage across emerging-market public transport networks efficiently.

## 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

- Collects, processes, and maintains mobility data for formal and informal public transport in cities where no usable map exists.
- Proprietary data production playbook: field collectors + Collector App + back-end production tooling; city fully mapped in 4–6 weeks.
- "Living Data" platform: ingests journey, movement, weather, and commuter-contributed data; outputs real-time journey plans and service alerts.
- Moat: incumbents (Google Maps, Citymapper, Moovit, Transit) lack informal-network data; 92% of the world's largest cities have no public transport map; WIMT claims more data than any other organisation.
- Product lines: (1) City Data Licences (B2B), (2) White-label consumer apps (B2B), (3) Collector App (data production tool), (4) Consumer commuter app in development (B2C).

## Market

- 2 billion people rely entirely on public transport in emerging-market cities.
- Commuters spend an average of 5 hours travelling per day.
- 80% of commuters rely on informal networks.
- 30% of minimum-wage household income spent on transport.
- Addressable commuter market: 300+ million daily commuters across target megacities.
- Target city expansion: 40 cities mapped to date across 27 countries, 4 continents; plan for 30 largest emerging-market megacities by 2023 at 3 new cities per quarter from 2021.

## Revenue model

- Primary: City Data Licences - recurring revenue stream sold to Location Based Services, Infrastructure Providers, Automotive & Equipment, Mobility-as-a-Service (MaaS), and development-finance clients.
- Secondary: White-label consumer products (B2B); 1 million+ users at time of deck.
- Client mix: originally public-sector, shifted toward large global corporates for broader use cases, better funding, and multi-city contracts.
- Named clients/partners: Shell Foundation, World Resources Institute, Facebook, Gautrain, IDB, Google, Toyota Tsusho, TUMI, UN-Habitat.
- Named investors: Google, Toyota Tsusho, Nedbank, Goodwell, Global Innovation Fund, iill Ventures, Omidyar Network.

## Traction & metrics

- 1,000,000+ km mapped.
- 40 cities mapped.
- 27 countries, 4 continents.
- 1 million+ users (white-label consumer apps).
- 100 million+ data transactions.
- 65+ in-office experts; 1,000+ in-field collectors.
- CDMX data example: 2,995 tracks (vs. 430 formal-only, 7x), 42,300 km (vs. 6,600, 6.5x), 1,390 routes (vs. 199, 7x), 31,400 stops (vs. 6,500, 4.8x).

## Unit economics

- "Multi-million dollar investment in design-led research" referenced as a cost item.
- City mapping cost: field team recruitment + 4–6 weeks of collection + ongoing local presence.

## Competition / moat

- Direct competitors named: Google Maps, Citymapper, Moovit, Transit - all developed-market focused, lack informal-network data.
- Competitive advantages stated: (1) proprietary data production playbook, (2) 1M+ km of mobility data no competitor holds, (3) adaptive AI platform for volatile environments, (4) multi-million dollar design-led consumer research investment, (5) embedded local teams for ongoing updates.
- 92% of the world's largest cities have no public transport map.
- Informal networks up to 10x larger than formal networks.

## Team & funding ask / use of funds

- Team: 65+ in-office staff across London, Cape Town, San Francisco, Mexico City; 1,000+ in-field data collectors.
- Investors listed: Google, Toyota Tsusho, Nedbank, Goodwell, Global Innovation Fund, iill Ventures, Omidyar Network.
- Founding date / year: Company operational from at least 2015 per product timeline.

## Recommended financial model

- **Archetype + why:** B2B Data Licence SaaS model (city-based ARR). Revenue is driven by recurring annual city data licence fees with expanding city coverage as the core growth lever. White-label consumer (B2B2C) is a secondary revenue stream. A 3-statement model underlies unit-level city economics.
- **Forecast horizon & granularity:** 5-year annual (2021–2025); quarterly build for Year 1–2 to capture the city-ramp cadence (3 new cities/quarter target). Monthly optionally for runway/cash planning given field-team cost structure.
- **Key drivers & assumptions:**
  - Cities mapped at period start: 40
  - New cities per quarter (2021+): 3; ramp to steady state
  - Average Annual Contract Value (ACV) per city data licence:
  - Clients per city (number of licensees):
  - Client mix split B2B corporate vs. NGO/public sector:
  - White-label consumer revenue per user or per contract:
  - Gross margin on data licences:
  - City data production cost (one-time capex per city):
  - Ongoing data maintenance cost per city per year:
  - Field collector headcount per new city:
  - In-office headcount growth: 65+ at deck date;
  - 1M+ users (consumer):; consumer monetisation path not shown - model as pass-through / cost centre for now
- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Base: 3 new cities/quarter, ACV at midpoint, 70% licence renewal rate
  - Bull: 4+ cities/quarter (additional funding), higher ACV from corporate mix shift, upsell of real-time data feeds
  - Bear: 1–2 cities/quarter (execution risk / COVID-type disruption), ACV discounting for public-sector clients, churn on NGO contracts
- **Required sheets / outputs:**
  1. Assumptions - city ramp schedule, ACV, headcount ratios, margins
  2. City Roll-up - cities mapped by quarter, cumulative ARR by cohort
  3. P&L - revenue by line (data licences, white-label), opex (field ops, tech, G&A), EBITDA
  4. Headcount - in-office + field; linked to city count
  5. Cash Flow - field capex per city, working capital, burn/runway
  6. Balance Sheet (light) - deferred revenue, capex, equity raised
  7. KPI Summary - cities live, ACV, ARR, ARR per city, gross margin %, burn multiple

## Frequently asked questions

### Is the WhereIsMyTransport financial model free?

Yes. The WhereIsMyTransport 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.