GL

Good Loop Financial Model

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).

• 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).

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.

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.

• 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.

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.

• 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.

• 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 %.