# Good Loop Financial Model

Purpose-driven adtech platform that donates a share of ad spend to charities in exchange for user attention, while offering brands impact reporting and carbon-offset tools.

- Canonical: https://finamodel.com/startups/good-loop
- Excel download: https://finamodel.com/startup-models/good-loop.xlsx
- Category: Climate/Energy
- Model type: SaaS ARR / Valuation
- Funding round: Series A
- Funding: $6M
- Founded: 2022
- Geography: UK-headquartered, active in US (>1/3 of 2021 turnover) and Japan (reseller); predominantly English-speaking markets [DECK, slides 10–11].
- Customer: B2B

## About the company

Good-Loop is an adtech platform that lets brands fund charitable donations when audiences watch or engage with advertising. Its Watch-to-Donate and Engage-to-Donate products pair media performance with impact reporting and a Green Ad Tag for tracking and offsetting digital-ad emissions.

The business earns a share of gross marketing spend through managed-service campaigns and programmatic channels, while a defined portion is passed to charity. It delivered £5.4 million of 2021 turnover, with US business exceeding one third of the total and repeat deals representing 48% of wins.

The model should start with GMS by geography and channel, then translate it through the channel-specific take rate and charity pass-through to net revenue. Forecast managed-service versus programmatic mix, repeat business, US expansion, revenue per head, sales and technology spend, and the cash runway required for growth.

## 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 products:
1. **Watch-to-Donate** (premium publishers): user watches the full video ad; a pre-set donation is unlocked to a charity partner.
2. **Engage-to-Donate** (social channels): same mechanic adapted for social inventory.
3. **CTV / Audio**: flagged as "more to come" - pipeline product, not yet revenue-generating.

Supporting platform capabilities:
- **Real-Time Impact Hubs**: reporting dashboards showing donations raised and charity outcomes, visible to brand clients.
- **Green Ad Tag** (1×1 pixel): tracks and offsets CO₂ emissions of a brand's entire digital activity in real time.
- Certified B Corporation; net-carbon negative.

Value prop to brands: higher attention, purpose-aligned media, measurable ESG outcomes, brand-lift metrics (e.g. 66% more brand love for Pantene, 71% switcher intent for Dove competitors).

## Market

- SAM (2024 target): $248bn / £180bn - "responsible, purposeful advertising" segment of global digital ad market.
- Total digital advertising market framing: "$500bn industry ripe for disruption".
- Comparable exit comps cited: IAS ($3.3bn IPO Jun 2021), DoubleVerify ($4.2bn IPO Apr 2021), Oracle/MOAT ($850m), gumGum ($700m valuation).

## Revenue model

Primary metric is **Gross Marketing Spend (GMS)** - the total client ad-budget flowing through the platform. Good-Loop takes a revenue cut from GMS; a portion of GMS is passed through to charity.

Two business model tracks:
1. **Managed Service campaigns** - 50% of campaign value donated; Good-Loop earns the other 50% (effectively a 50% take-rate on GMS, from which it funds operations and donation).
2. **Programmatic campaigns** - 33–50% donation; lower take-rate, higher scalability.

Implied net revenue (Good-Loop's earned portion) is not separately stated; GMS and "turnover" appear to be used interchangeably in the deck at £5.4m for 2021. Pricing structure per campaign: Not in deck.

Channels: direct brand sales (managed service) + programmatic DSP/SSP channels + resellers in US and Japan.

## Traction & metrics

| Year | GMS / Turnover | Headcount |
| ----- | -------------- | ---------- |
| 2017 | £12k | 3 |
| 2018 | £400k | 7 |
| 2019 | £956k | 11 |
| 2020 | £1.9m | 17 |
| 2021 (forecast→actual) | £4m forecast → £5.4m actual ($7.3m) | 22 |

Source:

- 2021 actual was 173% of £4m target.
- >200% YoY growth in Q1, Q2, and Q3 2021.
- Revenue-per-head H1 2021: £160k ($220k) = 309% ROI.
- US: >$2m closed US business in 2021; >1/3 of total 2021 turnover; 246% of 2021 US target; avg US deal size >2.5× global average.
- Repeat business: 48% of deals are repeats; repeat deal size up 168%.
- Close ties with 45% of world's top 100 brands.
- Works with 4 of top 5 global ad spenders (Amazon, P&G, L'Oréal, Samsung, Unilever - 4 confirmed).
- Impact to date: £450,602 donated by 7,501,204 people; >$5m raised for good causes total; 378 tonnes CO₂ emitted and offset; 205 trees planted.

## Unit economics

- Gross margin / take-rate: Implied ~50% of GMS on managed service; 33–50% on programmatic. No explicit gross margin % disclosed.
- Revenue-per-head: £160k ($220k) in H1 2021.

## Competition / moat

Competitive context:
- Brand-safety / brand-ethics adjacent: IAS, DoubleVerify, MOAT (Oracle), gumGum, Infosum.
- No direct competitors cited that combine the charity-donation mechanic with adtech.
- Moat claims: trust/transparency positioning; B Corp certification; established charity network; proprietary Impact Hub reporting; Green Ad Tag carbon-offset tool; early relationships with 45% of top-100 brands.
- Strategic vision: moving the market from "brand safety" (don't fund fraud) to "brand ethics" (actively good media).
- Disruption angle: positioned alongside Shopify vs. Amazon, Lemonade vs. Prudential, Bulb vs. British Gas as the ethical disruptor in a legacy $500bn market.

## Team & funding ask / use of funds

- **Funding ask**: Series A - £4m.
- Use of funds (pie chart shown, no exact % per category, proportions estimated from image):
  1. Ops / Tech / R&D - largest slice (teal, ~35%)
  2. US Expansion - second largest (dark red, ~25%)
  3. UK & EU Sales - (red, ~20%)
  4. Other OpEx - (yellow, ~12%)
  5. Marketing - smallest (pink, ~8%)
  Note: percentage splits are visual estimates from the pie chart; exact allocations available on request per deck.

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## Recommended financial model

- **Archetype + why**: **AdTech / Media Revenue model** - specifically a GMS (Gross Marketing Spend) + take-rate P&L model. Good-Loop is not a pure SaaS (no ARR/subscription), not a marketplace in the traditional sense, but a managed-service + programmatic media intermediary. The right frame is: GMS → net revenue (take-rate) → gross profit (after charity pass-through and direct campaign costs) → EBITDA. This is analogous to how a trading desk or DSP models revenue.

- **Forecast horizon & granularity**: 5 years (2021 base → 2026), quarterly for Years 1–2, annual for Years 3–5. 2021 actuals (£5.4m GMS) serve as base year.

- **Key drivers & assumptions**:
| Driver | Value |
| ------- | ------ |
| GMS base (2021 actual) | £5.4m |
| GMS growth rate - Year 1 (2022) | 100% YoY (conservative vs. historical >200%) |
| GMS growth rate - Years 2–3 | 75% / 50% |
| GMS growth rate - Years 4–5 | 30% / 25% |
| Managed service share of GMS | ~60% declining to 40% |
| Take-rate - managed service | 50% of GMS |
| Take-rate - programmatic | 40% blended |
| Charity pass-through | 50% on managed / 40% on programmatic (inverse of take) |
| Revenue-per-head (net) | £160k H1 2021 benchmark |
| Headcount growth | ~5–8 heads/year post-raise |
| US GMS share | >33% in 2021, targeting 50%+ by 2024 |
| Avg deal size growth | 168% YoY increase on repeats |
| Repeat deal share | 48% today |
| Programmatic GMS ramp | Minimal in 2021, growing with tech investment |

- **Scenarios (Base / Bull / Bear - which variables flex)**:
  - **Base**: GMS growth 100% → 75% → 50% → 30% → 25%; take-rate held steady; headcount per plan.
  - **Bull**: GMS growth sustains at 150%+ through 2023 (US lands large always-on deals, top-5 spenders increase commitment); average deal size continues 168% pattern for 2 more years.
  - **Bear**: US expansion slower than planned (sales cycle 12–18 months); GMS growth drops to 50% in 2022; headcount overshoot on OpEx side; take-rate compression on programmatic.

- **Required sheets / outputs**:
  1. **Assumptions** - all drivers in one place, clearly tagged vs..
  2. **GMS Bridge** - annual GMS by channel (managed service vs. programmatic) and geography (UK/EU vs. US).
  3. **Revenue & Gross Profit P&L** - GMS → take-rate revenue → charity pass-through → net revenue → headcount costs → S&M → tech/R&D → gross and operating profit.
  4. **Headcount Plan** - by function (sales, tech, ops, marketing), linked to hiring assumptions.
  5. **Cash Flow / Runway** - uses of Series A proceeds against burn; months of runway.
  6. **Scenario Toggle** - Base / Bull / Bear switcher.
  7. **KPI Dashboard** - GMS, net revenue, headcount, revenue-per-head, repeat deal %, US mix %.

## Frequently asked questions

### Is the Good Loop financial model free?

Yes. The Good Loop 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.