GOGoodcarbon Financial Model
Fintech Startup Financials (Free Excel Download)
Builds and manages long-term carbon credit portfolios from Nature-based Solutions (NbS) for corporate net-zero buyers.
professionals from Deloitte
Used by professionals from






About this model
goodcarbon builds and manages long-term carbon-credit portfolios from nature-based solutions for corporate net-zero buyers. It connects companies seeking credible credits with projects such as reforestation, mangroves, and avoided deforestation.
The business can sell third-party credits at a markup, originate credits with a higher margin, and provide ongoing advisory or portfolio-monitoring services. Its commercial challenge is therefore part marketplace, part inventory manager, and part trusted climate adviser.
The model should forecast credits sourced and sold by project, realised price per credit, inventory timing, and gross spread. Advisory revenue can be built from managed tonnes or client portfolios, while cash conversion, project commitments, and credit-quality assumptions make the inventory economics transparent.
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 Goodcarbon
goodcarbon.earth
How to build a detailed financial model for Goodcarbon
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Goodcarbon model - distilled from its pitch deck and publicly available information.
Product & value proposition
Three layers:
- Retail / Marketplace - curated third-party NbS projects (15 projects, ~10m credits) sold as spot or forward contracts.
- goodcarbon Originals - proprietary project development (e.g. Great Green Wall mangrove restoration, India; >2m tonnes CO2 over lifetime).
- Portfolio Management SaaS layer - monitoring dashboard, Nature Analytics Framework scoring (165 criteria; sample score 3.7/5), sustainability reporting output for client stakeholders.
Contract types offered: Spot (short-term); Forward/Offtake (mid-term); Stream / Bespoke Project (long-term to 2040). Swiss Re partnership for delivery-insurance launching Q2 2024.
Market
- Carbon removal issuance 2023: ~30m tonnes CO2e.
- Carbon removal need 2030: ~200m tonnes CO2e.
- Carbon removal need 2050: ~1.5bn tonnes CO2e - x50 vs. 2023 issuance.
- ~3,000 leading companies have set science-based net-zero targets (SBTi / Net Zero Tracker).
- 10bn tonnes CO2e annually can be removed/avoided by 2030 through NbS at attractive economics.
- Credit price forecast: $80–150/tonne by 2030; $150–200/tonne by 2050 (Nature-enabled Net Zero scenario).
- No explicit EUR TAM/SAM/SOM figure stated in deck.
Revenue model
Three revenue streams, all B2B direct sales:
| Stream | Mechanism | Sample pricing |
|---|---|---|
| Retail / Marketplace spot & forward | Sell third-party NbS credits with markup | €12–€60/credit depending on project |
| goodcarbon Originals spot & forward | Sell self-originated credits at higher margin | €15–€25.50/credit |
| Portfolio management / SaaS | Ongoing advisory and monitoring service | Not priced in deck |
Example project prices from slide 9:
- Tambopata (Brazil, REDD+, avoidance): €12/credit, 14,000,000 credits
- Great Green Wall (India, mangroves, removal): €15/credit, 37,000 credits
- Two Ejidos (Mexico, reforestation): €20/credit, 116,000 credits
- Varaha (India, regen. ag.): €20/credit, 116,000 credits
- Mindanao (Philippines, agroforestry): €25/credit, 50,000 credits
- Generation Forest (Panama, reforestation): €25.50/credit, 10,000 credits
- Klim (Germany, soil): €60/credit, 7,000 credits
Slide 8 also lists: Ita Blue (€30/credit), RESEX Jacunda (€15/credit), Tambopata (€12/credit) - marketplace tier.
Gross margin on transactions flagged as a tracked KPI but values redacted.
Traction & metrics
- Total inventory built: ~9,000k tonnes (9 million tonnes) across Retail, Platform, and Originals - spot + forward.
- Named clients (slide 12): Deutsche Telekom, Bertelsmann, Berner, Melitta, Klett, Redcare Pharmacy, Solarisbank, BCD Travel.
- Contracted revenue chart (slide 13) shows growth from Q4 2022 through Q1 2024 with a sharp step-up in Q1 2024 - but all y-axis values and total "EUR XXm" are redacted.
- Revenue by client (slide 14): 10 named clients + Other shown with bar chart - all EUR k values and gross margins redacted ("X%").
- Key metrics box (slide 14) listed but fully redacted: Sales cycle (X–X months), Median contract value (X EUR), Median contract value ICP (X EUR), Average gross margin on transactions (X%), Sales person efficiency (X).
- Portfolio composition example (Redcare case, slide 11): Avoidance 86% / Removal 14%; REDD 86% / Reg Agri 4% / Reforestation 10%.
No unredacted ARR, MRR, or total revenue figure appears anywhere in the deck.
Unit economics
- All per-client gross margin values redacted (shown as "X%").
- Average gross margin (transactions) listed as a tracked metric but value redacted.
- Sales cycle, median contract value, and salesperson efficiency tracked but redacted.
- Pricing spread observed: €12–€60/credit implies substantial margin variance by project type; goodcarbon Originals likely highest-margin tier.
Competition / moat
Moat claims in deck:
- Proprietary Nature Analytics Framework - 165-criterion scoring (Impact, Risk Mitigation, Integrity) applied to all projects.
- Exclusive supply agreements - spot and forward inventory locked with project developers.
- Originals pipeline - first-party project development (Great Green Wall, India) differentiates from pure brokers.
- Swiss Re insurance partnership for non-delivery risk, launching Q2 2024.
- Trusted partners: GIZ, Conservation International, World Bank, Plan Vivo.
Competitive landscape: not explicitly mapped in deck. Greenwashing press clippings (Disney, Shell, BP, VW) used to frame the quality-gap problem goodcarbon solves.
Team & funding ask / use of funds
Team (slide 17):
- Jérôme Cochet, Co-Founder & MD - Global MD at Dunnhumby, SVP Zalando, McKinsey EM, INSEAD.
- David Diallo, Co-Founder & MD - Multi-exit entrepreneur (GoodJobs, GoodBuy, Enorm, epubli, myphotobook).
- Dr. Nicola Rodewald, Director NbS - PhD Biology, McKinsey EM, healthcare MD.
- Ricarda Röller, Director Biz Dev - Kearney EM, London Business School.
Recommended financial model
Archetype: Carbon credit marketplace + inventory P&L with SaaS-layer overlay.
goodcarbon combines two distinct economic engines: (1) a trading/inventory P&L - buying credits from project developers and selling to corporates at a spread, with volume x price x margin as the core drivers; and (2) an emerging recurring advisory/management fee tied to AUM (tonnes under management). The model should be built as a commodity-trading P&L at its core, not a pure SaaS ARR model, because unit revenue is per-tonne not per-seat.
Forecast horizon & granularity:
- 5-year annual (2024–2028), with quarterly detail for Year 1 given the early stage and visible Q1 2024 ramp.
Key drivers & assumptions:
*Demand / Revenue*
- Number of enterprise clients signed per year
- Average contract value (ACV) per client
- Mix: Spot vs. Forward vs. Stream
- Average credit price by category
- Tonnes sold per year
*Supply / Inventory*
- Total inventory (k tonnes) - spot and forward
- Originals pipeline additions per year
- Cost of credits (purchase price from developers)
*Gross margin*
- Transaction gross margin %
- Originals margin premium
*Operating costs*
- Headcount: 4 named senior leaders; ASSUMED small team (~10–20 FTE at April 2024)
- Personnel cost growth in line with new client additions and project development
- Project development capex (Originals)
- Tech/platform (monitoring dashboard)
*SaaS / management fee*
- Annual management fee per client portfolio under management
Scenarios (Base / Bull / Bear - which variables flex):
- Base: ~10 new clients/year, blended ACV €75k, GM 35%, Originals 1 new project/year.
- Bull: Corporate climate mandates accelerate (SBTi signatories grow faster), credit prices rise toward $80/tonne by 2030, goodcarbon captures outsized share via Originals and Swiss Re insurance.
- Bear: Voluntary carbon market credibility crisis deepens (more greenwashing headlines), regulatory delays, credit price stagnation, client churn as net-zero timelines slip.
- Key flex variables: ACV, tonnes sold, credit price, gross margin %, client count.
Required sheets / outputs:
- Assumptions - all drivers centralized, toggled by scenario.
- Revenue build - by segment (Retail, Platform, Originals, Mgmt Fees); volume × price × margin.
- Inventory / supply tracker - opening inventory, additions (Originals + new marketplace), sales, closing balance.
- P&L - Revenue → Gross Profit → EBITDA → Net Income.
- Headcount & Opex - by function.
- Cash flow - operating + capex (Originals project dev); runway.
- KPI dashboard - clients, tonnes sold, ACV, GM%, tonnes under management, contracted revenue.
- Scenario toggle - Base / Bull / Bear switchboard.
Frequently asked
Is the Goodcarbon financial model free?+
Yes. The Goodcarbon 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 Goodcarbon'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
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.
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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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