# Sensorfact Financial Model

IoT energy-monitoring platform for industrial SMEs - plug-and-play hardware + SaaS analytics that identifies and tracks energy savings.

- Canonical: https://finamodel.com/startups/sensorfact
- Excel download: https://finamodel.com/startup-models/sensorfact.xlsx
- Category: Climate/Energy
- Model type: SaaS ARR / Valuation
- Funding round: Series B
- Funding: €25M
- Founded: 2023
- Geography: Europe - headquartered Utrecht (NL), offices in Amsterdam, Berlin, Barcelona [DECK slide 8].
- Customer: B2B

## About the company

Sensorfact combines wireless machine-level energy sensors with analytics and action tools for industrial SMEs. Its plug-and-play hardware feeds a cloud dashboard and savings recommendations across uses such as compressed air, steam, HVAC, and plastics.

Customers avoid upfront capex because the sensors, software, and analytics are bundled into a recurring offering. Direct sales teams in the Netherlands, Germany, and Spain sell an affordability and rapid-installation proposition against high industrial energy costs and efficiency targets.

The model should treat this as hardware-enabled SaaS: new sites and sensors create MRR, while deployed hardware drives shipment COGS and inventory needs. Forecast customer additions, sensors per site, subscription price, churn, gross margin, and expansion, then link sales coverage, data-product costs, and hardware procurement to 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

Three-layer offering:
1. **DATA** - Non-invasive, wireless, no-battery plug-and-play sensors; machine-level energy measurement; cloud dashboard live in hours.
2. **ANALYTICS** - Algorithmic savings advice drawn from a library of 60+ savings categories (compressed air, steam, HVAC, plastics, etc.) + pattern-recognition data science (e.g. detecting compressed air leakages from compressor energy signatures).
3. **ACTION** - Automated tracking reports + smart alerts; recurring feedback loop.

USPs targeting SME plant managers:
- Easy to install: non-invasive, wireless, no downtime, no after-care.
- Affordable: no CAPEX, within plant-manager sign-off budget.
- Full service: hardware + software + analytics advice bundled.

## Market

- Context: EU -32.5% energy reduction target by 2030 vs business-as-usual.
- German baseload electricity prices spiked from ~€50/MWh (2019) to ~€350/MWh peak (2022).
- No TAM/SAM/SOM figures provided in deck.
- Target segment: industrial SMEs in Europe.

## Revenue model

- Model: Hardware-enabled SaaS - "no CAPEX" for customer implies hardware is bundled into a recurring subscription fee.
- Channels: Direct sales (dedicated sales offices in NL, DE, ES).
- Contract structure: Recurring (implied by "no investment plan needed, easy to sign off"); contract length not stated.

## Competition / moat

- Proprietary savings database (60+ categories) accumulated through deployments.
- Unique combination of industry knowledge + ML pattern recognition.
- Full-service bundle removes integration friction for SMEs.

## Team & funding ask / use of funds

Team:
- Pieter (CEO/Founder) - founded 3 smart energy startups (2 active, 1 exit).
- Hans (CFO/COO) - 10+ years strategy & VC, joined 2019.
- Jamie Persijn & Senan King - Head of Sales (dual role, 10+ years leading sales teams).
- Paco Trujillo - Head of Platform.
- Dennis Ramondt - Head of Data Science.
- Karel Nanninga - Head of Growth, 8 years strategy & VC.

Offices opened: Utrecht (Dec 2019), Berlin (Jan 2022), Amsterdam (Sept 2022), Barcelona (Sept 2022).

## Recommended financial model

- **Archetype + why:** Hardware-enabled SaaS ARR model. Revenue flows as recurring subscription (sensors bundled, no customer CAPEX), so ARR/MRR is the primary metric. Hardware COGS must be modelled alongside software gross margin to capture blended economics. Closest archetype: SaaS ARR with hardware attach layer.

- **Forecast horizon & granularity:** 5 years (2024–2028), monthly for Year 1–2, quarterly for Year 3–5. Monthly needed to track sensor deployment ramp and cash burn given hardware inventory cycles.

- **Key drivers & assumptions:**

| Driver | Value |
| -- | -- |
| Geographies active | NL, DE, ES |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Base: steady 10–15% MoM new customer adds, 1.2% monthly churn, blended GM 55%.
  - Bull: faster enterprise upsell (more sensors/site), lower churn (0.7%), GM expansion as hardware becomes smaller % of revenue.
  - Bear: slower sales ramp (regulatory/procurement friction), higher churn (2%), hardware cost inflation.

- **Required sheets / outputs:**
  1. Assumptions - all drivers in one place with scenario toggle.
  2. Customer & ARR Build - new customers, churned customers, ending customers, MRR/ARR waterfall.
  3. Hardware P&L - unit shipments, COGS, inventory.
  4. Revenue & Gross Profit - subscription revenue + hardware revenue, blended gross margin.
  5. Opex - headcount by function (Sales, Tech, CS, Growth), office costs, other.
  6. Income Statement (IS).
  7. Cash Flow - particularly important given hardware inventory cash drag.
  8. KPI Dashboard - ARR, net new ARR, NRR, blended GM%, CAC payback, burn rate, runway.

## Frequently asked questions

### Is the Sensorfact financial model free?

Yes. The Sensorfact 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.