# Convious Financial Model

Vertical SaaS + transaction-fee platform connecting out-of-home experience (OOHE) venues to visitors via e-commerce, dynamic pricing, marketing automation, and on-site operations.

- Canonical: https://finamodel.com/startups/convious
- Excel download: https://finamodel.com/startup-models/convious.xlsx
- Category: Marketplace
- Model type: Marketplace / GMV
- Funding round: Series A
- Funding: $12M
- Founded: 2021
- Geography: Europe-primary (NL/DE anchor), active in 16 countries, expanding globally. [DECK slide 7]
- Customer: B2C

## About the company

Convious is a vertical commerce platform for attractions and leisure venues, including theme parks, museums, ski resorts, and zoos. It combines ticketing, dynamic pricing, marketing automation, e-commerce, POS, loyalty, and operational tools to help venues sell directly to visitors.

The business had 120 venues in 16 countries, processed more than 30 million visitors and 8 million bookings in 2020, and reported less than 1% annual venue churn. It earns a percentage of transactions flowing through the platform, with a possible subscription component for the software layer.

The model builds venue growth, visitors, bookings, spend per booking, and resulting GMV. A transaction take rate and any platform fees become revenue, while venue onboarding, customer success, product development, and sales costs feed the P&L. Retention, expansion revenue, and recovery in visitor demand are the critical scenario variables.

## 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

- End-to-end vertical SaaS platform for leisure operators (theme parks, ski resorts, museums, zoos, water parks, FECs, etc.).
- Core modules: Marketing (CRM, email, push/SMS, paid campaigns), Commerce (dynamic pricing, web shop, upsells, vouchers, reseller/channel manager), POS & Hardware, Mobile App (e-wallet, in-app purchase, F&B ordering), Loyalty & Support, BI & Forecasting.
- Key differentiation: real-time AI dynamic pricing + crowd control; D2C model bypasses third-party resellers and their commissions; single platform replaces legacy fragmented stack.
- Customer case stat: +201% increase in revenue, +86% increase in conversion (unnamed customer).

## Market

- TAM: $8.8TN total global Out-of-Home Experience (OOHE) market.
- Market represents ~10.4% of world GDP; 500k+ venues globally; 319 million jobs.
- Only 17% of OOHE revenue was booked online in 2020 - "underpenetrated market."
- Online OOHE CAGR: 22.6% (2021–2027).

## Revenue model

- Primary: Percentage take-rate on every transaction processed through the platform (tickets, rides, reservations, F&B, ski passes, lockers, etc.). Exact % not disclosed - stated as "a %*" with asterisk.
- Secondary: Implied SaaS/platform subscription (vertical SaaS positioning, slide 5), but no explicit SaaS fee tier or pricing disclosed in deck.
- Channel: Direct sales to venue operators (B2B); then venues use the platform to sell D2C to end consumers (B2B2C).
- ARPA: Described as "$xxk" - specific value redacted in deck.
- GMV-driven revenue; Convious earns a take-rate on total transaction volume flowing through the platform.

## Traction & metrics

- Venues: 120 (with <1% annual venue churn).
- Countries: 16 active.
- Visitors processed: 30M+ in 2020.
- Bookings: 8M in 2020.
- NPS: 42.7 (April 2021, trending up).
- GMV growth: "Growing 7x YoY despite COVID." Specific GMV figures (2018–2021F bar chart) are redacted as "xx" / "$xxxM" in the deck image - no actual dollar values readable.
- Expansion revenue: +184% expansion revenue in 2020 (existing customers spending more).
- Profitability: "Profitable for the second year in a row" as of deck date (~2021).
- Capital efficiency: "$xxxM forecasted GMV in 2021 with only $xM capital raised" - both values redacted.
- 2022 pipeline: "$xxxM booked for 2022" - redacted.
- LTC:CAC ratio mentioned but value redacted ("xx LTC to CAC ratio").

## Unit economics

- ARPA: "$xxk" - redacted.
- LTV:CAC ratio: Mentioned, value redacted ("xx LTC to CAC").
- Venue churn: <1% annually.
- Expansion revenue: +184% in 2020 implies strong net revenue retention (NRR likely well above 100%).

## Competition / moat

- Problem framing: incumbent/legacy ticketing vendors are described as having "no AI, no e-commerce, marketing or data play, no cloud APIs, no mobile."
- Moat claims: AI dynamic pricing + crowd control, full-stack D2C platform, deep integrations across the venue operations stack, high NPS, <1% churn.
- Direct competitors: Not named in deck.

## Team & funding ask / use of funds

- CEO/Founder: Camiel Kraan - former CCO Bwin, Founder Squla; 25+ years experience.
- COO: Adriaan van der Hek - former CEO ShoppingMinds; 25+ years experience.
- CTO: Juozapas Zabukas - former CTO Productors; 15+ years experience.
- VP Sales: Bernard Kochen - former VP Sales TravelBird; 15+ years experience.
- CMO: Koen Scholte - former VP Marketing Talpa/Emesa; 15+ years experience.
- Team size: 40+ members.
- Prior employer logos shown: Backbase, TietoEnator, ShoppingMinds, Adform, Infor, Booking.com, Bwin, Talpa, TravelBird.
- Capital raised to date: "$xM" - redacted.

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## Recommended financial model

- **Archetype + why:** GMV-driven marketplace / vertical SaaS take-rate model. Revenue = GMV × take-rate % (transaction layer) + optional SaaS platform fee per venue. This is the natural archetype because Convious's stated revenue mechanism is a % of every transaction; the SaaS subscription (if any) is secondary or bundled. A 3-statement wrapper (P&L, Balance Sheet, Cash Flow) should sit beneath it given the company claims profitability.

- **Forecast horizon & granularity:** 5-year annual model (2021–2026) with monthly granularity for Year 1–2 (useful for cash flow given COVID-recovery lumpiness). Deck is ~2021-vintage.

- **Key drivers & assumptions:**

| Driver | Value / Source |
| -- | -- |
| Starting venue count | 120 |
| Venue churn rate | <1% p.a. - model at 1% |
| Avg visitors per venue per year | 30M visitors ÷ 120 venues = ~250k/venue |
| GMV per venue per year | Visitors × booking rate × avg ticket value |
| GMV growth rate (online penetration tailwind) | OOHE online CAGR 22.6%; |
| Profitability | Already profitable for 2 years; maintain positive EBITDA in base case |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - **Base:** 22.6% OOHE online market CAGR; ~60 net new venues/yr; take-rate 3%; NRR 120%.
  - **Bull:** Faster global expansion; 100+ net new venues/yr; take-rate 4%; NRR 140%; COVID recovery accelerates revenue expansion.
  - **Bear:** Slower international rollout; 30 net new venues/yr; take-rate 2.5%; COVID resurgence delays recovery; NRR 110%.
  - Primary flex variables: net new venues, take-rate %, avg GMV per venue, NRR.

- **Required sheets / outputs:**
  1. **Assumptions** - all drivers in one input sheet (color-coded hardcodes vs. formulas)
  2. **Venue Roll-forward** - opening count, new adds, churn, closing count by period
  3. **GMV Build** - venues × visitors/venue × booking rate × AOV → total GMV
  4. **Revenue Build** - GMV × take-rate + SaaS fees × venue count; expansion revenue modelled via NRR
  5. **P&L** - Revenue, COGS (payment processing, hosting), Gross Profit, S&M, R&D, G&A, EBITDA, EBIT, Net Income
  6. **Cash Flow** - Operating / Investing / Financing; working capital light (SaaS + take-rate = mostly prepaid or near-real-time)
  7. **Balance Sheet** - simplified; flag deferred revenue if annual SaaS contracts
  8. **Unit Economics** - CAC, LTV, payback, ARPA, NRR per cohort
  9. **Scenarios** - toggle sheet linking Base/Bull/Bear assumptions
  10. **Dashboard** - GMV, revenue, venue count, NRR, EBITDA margin over time

## Frequently asked questions

### Is the Convious financial model free?

Yes. The Convious 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.