# Prolific Financial Model Online research participant recruitment platform connecting researchers with a verified, incentivised participant pool - Canonical: https://finamodel.com/startups/prolific - Excel download: https://finamodel.com/startup-models/prolific.xlsx - Category: Marketplace - Model type: SaaS ARR / Valuation - Funding round: Series A - Founded: 2023 - Geography: UK-headquartered (GBP revenues cited); expanding to US [DECK slide 11] - Customer: B2B ## About the company Prolific is a research-participant recruitment marketplace connecting researchers with a verified, incentivized participant pool. Its self-serve platform supports study design and targeting, while identity checks and quality controls aim to produce more reliable research responses. The platform has more than 30,000 researchers and 100,000 active verified participants. Researchers fund participant incentives and Prolific retains 25% of GMV, serving both repeat academic customers and faster-growing corporate research clients. The model builds study spend from researchers, studies per researcher, average project value, and customer mix, then applies the 25% take rate. Participant supply, study completion, quality control, payment timing, and segment retention drive the marketplace economics. Academic expansion and corporate adoption should be forecast separately. ## 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 - Research participant recruitment platform at www.prolific.co - 100,000+ active, verified participants screened via ID checks, ML, and behavioural controls - Integrations with thousands of third-party research platforms - Claims empirically superior data quality vs. alternatives - Researchers use self-serve platform to design studies, target segments, and collect responses - Participant pool broken into Academic, Corporate, and Other segments ## Revenue model - Marketplace take-rate model: Prolific charges a percentage of GMV (spend by researchers on participants) - Take rate: **25% (Rev/GMV)** - Revenue = GMV × 25%; balance goes to participants as incentives - Two customer segments: Academic institutions (subscription/repeat purchase pattern) and Corporate / non-academic (project-based, growing rapidly) - No per-seat or SaaS fee structure described; purely transaction/usage-based on participant spend ## Traction & metrics - **>£ monthly revenue** (bootstrapped to this level) - **£ Revenue 2022; ~£m GMV 2022** - **7x growth since YC S19** (batch: Summer 2019) - **25% take rate** (Rev/GMV) - **30,000+ researchers** from world-class institutions - **100,000+ active, verified participants** - **90+ employees** - Land-and-expand pattern visible in top-institution bar charts (CY2017A–CY2021A): each top institution grows revenue year-on-year; CAGR labels present but values redacted - Non-academic revenue growing rapidly, starting near zero and showing steep acceleration as of Dec 2022 - "Recent AI customer journey" chart shows Revenue and GMV prepaid both growing sharply in the most recent periods ## Unit economics - **3-year institutional retention**:% of academic institutions; **100% for Ivy League & Russell Group** - **2-year researcher retention**:% across individual researchers - **YoY revenue expansion within institutions** (rate redacted) - confirms NRR > 100% pattern - Take rate of 25% is the primary gross margin driver; no COGS, S&M, or contribution margin figures disclosed ## Competition / moat - Primary named competitor: Amazon Mechanical Turk - Prolific claims superiority on: High Data Quality, Excellent Participant Experience, Control/Customisation, Audience Segmentation, Multipart/Tracker Studies - Moat sources cited: fair incentives driving participant quality, network effects (participant pool size), ML/behavioural screening, platform integrations, institutional stickiness (100% Ivy/Russell retention), expanding participant diversity ## Team & funding ask / use of funds - **CEO & Co-Founder**: Phelim Bradley, Ph.D. (University of Oxford) - **COO**: Jim Moodie - **VP Finance**: Jess Fiander (ex-PwC) - **VP Engineering**: Matt Tuplin (ex-Cinch) - **VP Product**: Sara Saab (ex-Charlotte Tilbury) - **VP People & Ops**: Wahida Samie (ex-Monzo) - **Board**: Enrico D'Angelo (Parkwalk) - **Advisors**: David Rothschild Ph.D. (Microsoft/Yahoo), Badr Khan (ATG/Matches Fashion) - **Funding ask**: "Raising to accelerate growth" - amount not stated - **Use of funds**: Sales & Marketing; AI Research R&D (specialised/exclusive participants, annotation integrations); Enterprise expansion (infra, privacy/security, scaling Sales & CS); US market entry --- ## Recommended financial model - **Archetype + why**: **Usage-based marketplace GMV model with two-segment revenue split (Academic vs. Corporate/Non-Academic)**. Revenue = GMV × 25% take rate; GMV is driven by researcher count × studies per researcher × average study spend. Two cohorts behave differently: Academic is sticky/expanding (land-and-expand); Corporate/AI is hypergrowth from a small base. This is not a SaaS ARR business - there are no fixed subscription fees - so a pure ARR model would misrepresent the economics. A 3-statement model wrapping the GMV engine is appropriate given the company has 90 staff and is fundraising. - **Forecast horizon & granularity**: 3 years (CY2023–CY2025), monthly for year 1, quarterly for years 2–3. YC S19 was mid-2019; with 7× growth since then the business has meaningful history; annual actuals from CY2017 exist for top institutions. - **Key drivers & assumptions**: - Take rate: **25%** - hold flat as base case; flex in scenarios - Academic researcher count growth rate: ~25% YoY; historical land-and-expand pattern supports ongoing institutional expansion; 30,000+ researchers on platform today - Average annual spend per academic researcher: derive from implied GMV ÷ researcher count once actuals disclosed; proxy ~£2,000–£5,000/researcher/year - Academic institutional retention (3-year): >90% implied by 100% for Ivy/Russell Group; blended 85–90% for model - NRR within institutions: >100% confirmed; 115–125% blended - Corporate/Non-Academic GMV growth: 150–200% YoY in near-term given steep acceleration from near-zero; taper to 60–80% by year 3 as base grows - Non-academic mix shift: grows from ~15–20% of GMV in 2022 to ~35–40% by 2025 as AI Training demand compounds - Participant pool growth: grows in line with GMV; participant pay-out = GMV × 75% (inverse of take rate) - Headcount: 90+ today; scales to ~130–160 by end of year 2 given US expansion and Sales/CS scaling - COGS: primarily infrastructure + participant trust/safety operations; ~15–20% of revenue - Gross margin: ~80–85% (marketplace economics, low direct COGS) - S&M: ~25–35% of revenue, rising with US expansion push - R&D: ~20–25% of revenue, elevated given AI Research R&D investment planned - G&A: ~10–15% of revenue - **Scenarios (Base / Bull / Bear - which variables flex)**: - **Base**: Corporate GMV grows 150% YoY → 80% → 50%; Academic NRR 115%; take rate held at 25% - **Bull**: Corporate GMV 200%+ (AI Training demand spike); Academic NRR 125%; US expansion lands 2 enterprise accounts in year 1 - **Bear**: Corporate growth moderates (AI Training commoditises); Academic NRR 105%; take rate compression to 20% as competition intensifies; US expansion delayed 12 months - **Required sheets / outputs**: 1. **Assumptions** - all drivers in one place, toggle-able 2. **GMV Build** - Academic vs. Corporate splits; researcher cohort model with retention + expansion 3. **Revenue & Take Rate Bridge** - GMV → Revenue reconciliation 4. **P&L (Income Statement)** - Revenue, COGS, Gross Profit, OpEx (S&M / R&D / G&A), EBITDA, EBIT 5. **Headcount Plan** - by function, tied to S&M and R&D spend 6. **Cash Flow & Runway** - key given fundraise context; show months of runway at each scenario 7. **Balance Sheet (simplified)** - for completeness; participant payables are key working capital item 8. **Scenario / Sensitivity Toggle** - 3-way scenario + sensitivity on take rate and Corporate GMV growth 9. **Dashboard** - KPI summary: GMV, Revenue, Take Rate, Researcher Count, Gross Margin %, EBITDA Margin %, Runway ## Frequently asked questions ### Is the Prolific financial model free? Yes. The Prolific 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.