# Lolli Financial Model Consumer rewards platform that pays users bitcoin or cashback when they shop online and in-store at partner merchants, earning commission-based revenue from merchants. - Canonical: https://finamodel.com/startups/lolli - Excel download: https://finamodel.com/startup-models/lolli.xlsx - Category: Crypto/Web3 - Model type: Marketplace / GMV - Funding round: Series B - Funding: $8M - Founded: 2023 - Geography: US-primary (25,000+ in-store US locations cited); platform is online-first. - Customer: B2C ## About the company Lolli is a consumer rewards platform that gives shoppers bitcoin or cashback at more than 1,000 online merchants and 25,000-plus in-store locations. Its browser extension, mobile app, and bank-linked card offers let users earn rewards from ordinary purchases while merchants fund the underlying commissions. The platform reported more than 600,000 registered users, 6.5 average transactions per user per month, $175 million-plus of cumulative merchant GMV, and 25–50% net margins. A B2B white-label product allows banks, exchanges, neobanks, and other partners to license the rewards stack alongside the consumer business. Model active-user cohorts, transaction frequency, average order value, merchant commission, and reward payout to derive the contribution spread. Keep white-label contracts as a separate revenue line and record bitcoin reward settlement as a liability-sensitive cost. User growth, merchant commissions, reward rate, engagement, bitcoin price, and partner wins are the principal scenarios. ## 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 - Browser extension + mobile app: users earn bitcoin or cashback at 1,000+ online merchant partners. - Bank-linked card offers (launched mid-2022): patented technology links debit/credit cards to earn additional in-store rewards (gas, coffee, groceries, etc.). Positions Lolli as complementary to exchanges, neobanks, BNPL, and existing loyalty programs. - B2B white-label solution: any third party can license the full consumer rewards stack (merchant-funded content, gamification, data analytics). Target partners: banks, crypto exchanges, neobanks, credit card providers, phone providers, browsers. - Core patent US20220300952A1: "Automating digital asset transfers based on historical transactions" - broad and defensible, covers fungible and non-fungible digital asset rewards. - Strategy: low-CAC rewards product as wedge to higher-LTV features and products. ## Market - Crypto market cap: ~$1 trillion - Global crypto exchange volume: $33B in 2021; projected $348B by 2030 - Rewards/loyalty market: ~$143B globally, ~$127B domestically - 3.3 billion loyalty memberships in the US alone - >90% of companies have loyalty programs - Demand signal: Visa survey - 86% of active crypto owners, 80% of passive crypto owners, 82% of crypto-curious people want crypto rewards ## Revenue model - Primary: affiliate/referral commissions from 1,000+ merchant partners on user purchases. Merchants pay Lolli a commission; Lolli passes a portion back to users as rewards. - Secondary (nascent): B2B white-label licensing fees from banks, exchanges, neobanks, etc. licensing the rewards platform. - Reward rate example shown in app: up to 4.5% earn at Amazon / Ninja Kitchen, 3% at other merchants. - Reward currency: user's choice of bitcoin or cashback. - Specific take-rate (spread between commission earned and reward paid out) not disclosed in deck. ## Traction & metrics - 600K+ registered users - 6.5 avg transactions / user / month - 1,000+ merchant partnerships - $175M+ in cumulative GMV driven to merchant partners - 25,000+ in-store rewards locations - 4.8-star app store rating across 17K+ reviews - 25–50% net margins & growing - Founded: 2018 (implied by "since 2018" on slide 6) ## Unit economics - Net margins: 25–50% and growing - CAC described as "low" but no dollar figure provided - LTV directionally described as growing (roadmap to multiply LTV via higher-value features) ## Competition / moat - Patented bank-linking technology (US20220300952A1) covering digital asset reward automation - Data-rich consumer shopping platform (described as "industry leading") - 1,000+ merchant relationships and 600K+ user base as network effects - Platform positioning as cross-cycle (recession-proof thesis: cost-saving behaviour accelerates in downturns) ## Team & funding ask / use of funds --- ## Recommended financial model - **Archetype + why:** Commission-based marketplace / affiliate rewards platform - 3-statement model with GMV-driven revenue build. Revenue = GMV × commission take-rate; COGS = rewards paid out to users (GMV × reward rate); gross margin = spread. Layer a B2B white-label SaaS/licensing line alongside. Not a pure SaaS ARR model (no subscription), not a DTC inventory model. Closest archetype: marketplace/affiliate P&L with crypto/rewards overlay. - **Forecast horizon & granularity:** 3 years monthly (2024–2026). Monthly granularity needed to model user cohort growth, transaction frequency, and BTC price sensitivity on reward liability. - **Key drivers & assumptions:** | Driver | Seed value / assumption | | -- | -- | | Registered users | 600K | | Monthly active users (MAU) | ~30–40% of registered = ~180–240K; typical rewards app engagement | | Avg transactions / user / month | 6.5 | | Avg order value (AOV) | ~$60–80; inferred from affiliate retail mix; not stated in deck | | GMV | $175M+ cumulative to date; model monthly flow separately | | Merchant commission rate (gross take-rate) | ~8–12%; typical affiliate commission range for retail; not disclosed | | User reward rate (payout rate) | ~3–6% of GMV; deck shows up to 4.5% earn rates | | Net take-rate (spread) | ~4–6%; consistent with 25–50% net margin claim if opex is lean | | Net margin | 25–50% | | User growth (MoM) | ~2–4% MoM new user adds; no growth rate provided | | Churn / attrition | ~3–5% monthly inactive bleed; rewards apps have moderate engagement drop-off | | B2B white-label revenue | $0 in Year 1; small pilot deals in Year 2–3; milestone/contract not disclosed | | BTC price assumption | flat-case at $30K; bull-case at $60K; bear-case at $15K - affects reward liability and user appeal | | Opex (headcount, infrastructure, marketing) | lean team; marketing spend low given CAC claim; no actuals in deck | - **Scenarios (Base / Bull / Bear - which variables flex):** - **Base:** MAU growth 3% MoM, AOV $70, commission 10%, reward rate 5%, BTC flat. - **Bull:** MAU growth 5% MoM, AOV $80, commission 12%, BTC 2x; white-label deal closes Year 2. - **Bear:** MAU growth 1% MoM, higher churn, BTC −50% (reduces user appeal and reward value), commission rate pressure as merchants tighten affiliate spend. - **Required sheets / outputs:** 1. **Assumptions** - all drivers with toggle for Base/Bull/Bear 2. **User Cohort Build** - monthly new users, active users, churn 3. **GMV & Revenue Build** - users × transactions × AOV × commission rate = gross revenue; less reward payout = net revenue 4. **B2B White-label Revenue** - separate simple driver (# of partners × license fee) 5. **P&L (Income Statement)** - revenue, COGS (rewards paid), gross profit, opex line items, EBITDA, net income 6. **Cash Flow** - operating CF; important given crypto reward settlement timing 7. **Balance Sheet** - minimal; flag crypto wallet liability and deferred reward balance 8. **KPI Dashboard** - MAU, GMV, take-rate, net margin %, LTV/CAC proxy ## Frequently asked questions ### Is the Lolli financial model free? Yes. The Lolli 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.