# Hopper Financial Model Mobile-first travel marketplace (flights, hotels, cars, homes) that pairs best-price inventory with proprietary fintech ancillaries (price freeze, cancel-for-any-reason, disruption protection) and syndicates its tech stack to third-party partners via Hopper Cloud. - Canonical: https://finamodel.com/startups/hopper - Excel download: https://finamodel.com/startup-models/hopper.xlsx - Category: Fintech - Model type: Marketplace / GMV - Funding round: Series G - Funding: $175M - Founded: 2021 - Geography: North America primary (largest travel app in North America); global inventory; Hopper Cloud targets global OTA/TMC/supplier market. - Customer: B2B2C ## About the company Hopper is a mobile-first travel marketplace for flights, hotels, cars, and homes, augmented by proprietary fintech products. Its consumer proposition pairs travel inventory with tools such as price freeze, flexible cancellation, and disruption protection. The company earns travel booking commissions but seeks a richer margin mix from ancillary products it underwrites and sells at checkout. Hopper Cloud adds a B2B distribution path by making its travel and fintech technology available to partners. The model should separate travel GMV and booking take rate from ancillary attach rate, premium revenue, claims, and underwriting margin. Build Hopper Cloud as a third revenue stream, while marketing cost, supplier economics, and working capital reflect the scale of the travel marketplace. ## 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 - Travel marketplace: Flights (200+ airlines, GDS + NDC + API), Hotels (2M+ properties, closed-user-group / mobile-only rates), Cars (launched late 2020, ~15% of bookings by deck date), Homes (pipeline). - AI price prediction: Proprietary forecasting predicts future travel prices with 95% accuracy; sends push notifications advising when to book. - Fintech ancillaries (in-house underwritten, dynamically priced): - Price Freeze: locks price 1 hr–14 days; avg. $60 per transaction; redeemable against booking. - Cancel/Change for Any Reason (CFAR): 5–20% of trip cost → 80% cash back on cancel, or free date/carrier change. - Disruption Protection: rebooking or reimbursement if delayed/missed connection; ~$20/traveler shown in app. - Price Prediction: free feature; drives install/engagement flywheel. - Carrot Cash: in-app wallet / loyalty currency funded by fintech margin, returned to customers to lower effective travel price. Growth loop: fintech revenue → lower travel prices → higher conversion → higher retention → more fintech revenue. - Hopper Cloud (B2B, launched 2021): syndicates fintech products via API, modular travel categories, white-label travel portals, and full-stack cloud to OTAs, TMCs, rewards programs, airlines, banks. ## Market - Online Travel TAM: $662B - Mobile Travel market: $264B - Travel Fintech TAM (Hopper Cloud addressable): $200B annually (theoretical: if Hopper Cloud fintech powered all OTAs, price-comparison, TMCs, supplier sites) - No SAM or SOM breakdowns presented. No CAGR figures stated. ## Revenue model - Booking commissions / net revenue on air, hotel, car transactions (agent model; take-rate on GDS/NDC/direct-contract) - Fintech ancillary attach revenue: Price Freeze (~$60 avg per transaction per slide 17, or $5 min deposit shown in mockup), CFAR (5–20% of trip cost), Disruption Protection (~$20/traveler shown), sold at time of booking checkout. All underwritten in-house; Hopper retains 100% of premium net of claims. - Hopper Cloud (B2B API): partners pay to embed fintech products; Hopper earns upfront commissions on ancillary sales through partner channels. - Fintech mix: >50% of total Hopper revenue derived from fintech ancillary products. - Hotel direct-contract margin improvement: in 2021 built 20+ person hotel direct-sales team; expected to improve hotel category margin by 50% by contracting top hotels directly. - Car direct-contract: already 40%+ of car volume contracted directly. ## Traction & metrics - Downloads: 60M+ lifetime installs - New installs: 2M+ per month - Organic install rate: 60% of installs are organic - Annual GTV / GMV: $1.5B in travel and travel-related financial services per year - App store ranking: #4 free app in North America travel category (behind Uber #1, Lyft #2, Yelp #3; ahead of Airbnb #5, United, Southwest, American, Delta, Booking, Expedia) - COVID recovery: revenue as of July 2021 is +180% above the pre-pandemic high point (Q1 2020); monthly revenue chart shows clear V-shape recovery Jan 2019 – July 2021, with Jul-21 the highest bar in the series - 2020 revenue growth: +112% YoY (2020 vs 2019), the only positive performer among major OTA peers (eDreams -80%, Trivago -79%, TripAdvisor -65%, Expedia -57%, Booking -55%, Ctrip -49%, Airbnb -30%) - Air market share: Hopper North America MIDT air bookings at 150–151% of 2019 levels as of Jun-Jul 2021, vs. OTA comp set at ~50–58% of 2019 levels - Customer demographics: 70% of booking customers under 35; 25% under 25; skews female in 18-24 and 25-34 buckets - Fintech revenue share: >50% of total revenue from fintech ancillaries - Cohort revenue retention: 2020-or-earlier cohorts will contribute 100% more revenue in 2021 than in 2020 - Booking retention: net negative revenue churn; all cohorts (2016–2019) show booking retention above 50% by Year 5, most above Airbnb's S-1 benchmark (~45% by Year 2); 2018 cohort reached ~160% by Year 3; 2019 cohort reached ~165% by Year 2 - Cancel/Change product: 110,000+ travelers purchased CFAR in 2021 YTD - Cars: grown to ~15% of travel bookings since late-2020 launch - Funding raised: ~$600M USD private capital; backers include CDPQ, Goldman Sachs, Capital One, OMERS Ventures ## Unit economics - Fintech ancillary margin: described as "high margin" vs. travel commission revenue; no gross margin % stated explicitly. - Price Freeze avg. revenue: ~$60 per transaction (customer pays; redeemable if they book, so net revenue depends on conversion). - CFAR pricing: 5–20% of trip cost per transaction. - Disruption Protection: ~$20/traveler per booking. - Hotel margin uplift: direct-contract strategy expected to improve hotel category margin by 50%. - Cars: 40%+ directly contracted, improving margin vs. multi-sourced. ## Competition / moat - Direct comps: Booking.com, Expedia, TripAdvisor, Airbnb (lodging), Google Flights (meta-search), OTA incumbents. - Moat claims: 1. Proprietary price-prediction ML (95% accuracy, built on large historical pricing data set since 2015). 2. Mobile-native distribution - 60% organic installs, low blended CAC vs. SEO/SEM-dependent rivals. 3. In-house fintech underwriting - CFAR and Disruption Protection are risk products Hopper underwrites itself (dynamically priced, no third-party insurer margin leakage). 4. Net negative revenue churn / cohort expansion - booking retention exceeds Airbnb S-1 benchmark; growing cohort revenue contribution. 5. Hopper Cloud B2B moat: once integrated, switching cost for partners is high (API-embedded fintech underwriting + white-label portals). - No discussion of regulatory/IP protection or exclusive supplier agreements beyond direct-contract programs. ## Team & funding ask / use of funds - Key executives: Frederic Lalonde (CEO, Co-Founder), Dakota Smith (CSO), Daniel Calderon (CFO), Ella Schreiber (GM Fintech), Brian Carroll (General Counsel). - Board: Patrick Pichette (ex-Google CFO, Nova), Laurence Tosi (ex-Airbnb CFO, Blackstone), Damien Steel (OMERS Ventures), Sophie Forest (Brightspark), Jeff Fagnan (Accomplice), Stephen Crawford (Capital One). - Funding raised to date: ~$600M USD. --- ## Recommended financial model - **Archetype + why:** Hybrid marketplace GMV model with fintech ancillary attach layer, plus a nascent B2B SaaS/API revenue line (Hopper Cloud). The business has two distinct P&L profiles - (1) thin-margin travel transaction revenue (OTA take-rate on GMV) and (2) high-margin fintech ancillary underwriting revenue. These must be modelled separately; blending them obscures the economics. A 3-statement operating model is appropriate given scale ($1.5B GTV). Hopper Cloud adds a third segment modelled as API/license revenue with commission pass-through. No M&A or SPAC structure - standard operating forecast. - **Forecast horizon & granularity:** Monthly for Year 1 (2022), quarterly for Years 2–3 (2023–2024). A 3-year view is appropriate given rapid growth rate and uncertainty in Hopper Cloud ramp. - **Key drivers & assumptions:** *Volume / top-line* - GTV (Gross Travel Value): $1.5B as of deck date; grow at ~80% in 2022 (recovery continuation + car/hotel mix shift), then ~40% in 2023, ~30% in 2024 - tapering as base grows. Flex heavily in scenarios. - Travel revenue take-rate on GTV: ~8–12% blended (air ~10%, hotel ~15%, car ~12%); industry comps suggest this range. Deck does not disclose. - Monthly installs: 2M+/month; retention curve built off cohort data - existing cohorts growing 100% YoY in revenue contribution. - App installs cumulative: 60M; organic mix 60%. *Fintech ancillary* - Fintech revenue as % of total revenue: >50%; model at 52% in Year 1, growing to 60% by Year 3 as Hopper Cloud scales attach. - Price Freeze avg. transaction: $60; attach rate ~15% of air bookings. - CFAR pricing: 5–20% of trip cost; model at 10% avg. attach; attach rate ~12% of air bookings. - Disruption Protection: $20/traveler; attach rate ~10% of air bookings. - Claims / loss ratio on fintech products: ~25–35% (insurance/fintech product typical range; deck does not disclose loss ratios). *Hopper Cloud* - Hopper Cloud launched 2021; contributes ~5% of total revenue in Year 1 growing to ~15% by Year 3 as partners integrate. - API commission rate: ~15–25% of ancillary revenue generated through partners (partner gets balance). *Costs* - Hotel direct-contract margin improvement: +50% on hotel category margin modelled as phased in over 2022 as sales team scales. - Car direct-contract: 40% volume already direct; grows to 70% by end of Year 1. - CAC: blended $8–15/install (low vs. comps given 60% organic); model CAC on paid installs only (40% of new installs). - S&M: ~15–20% of revenue (well below Booking/Expedia at 30–40%, reflecting organic advantage). - R&D / Engineering: ~20–25% of revenue (ML + pricing infrastructure is core). - G&A: ~10% of revenue. - Fintech claims & reserves: modelled as COGS against fintech revenue line. *Retention / cohort* - Existing cohorts (pre-2021): contribute 2x 2020 revenue in 2021; reversion to ~120% in 2022 as COVID-recovery effect normalises. - Booking retention Year 2+: modelled at ~65–70% of Year-1 bookings per cohort per year (mid-point of slide 23 range, better than Airbnb). - **Scenarios (Base / Bull / Bear - which variables flex):** - Base: GTV grows 80%/40%/30% YoY; fintech attach rates as above; Hopper Cloud at 10% of revenue by Year 3; claims ratio 30%. - Bull: GTV grows 100%/60%/50%; fintech mix reaches 65% of revenue; Cloud reaches 20%; claims ratio 25%; hotel/car direct-contract margin uplift fully realised. - Bear: GTV grows 50%/25%/15% (macro travel softness, competition); fintech attach rates 30% lower; Cloud slow ramp (5% by Year 3); claims ratio spikes to 45% in a disruption event. - **Required sheets / outputs:** 1. Assumptions dashboard (all drivers in one place, colour-coded) 2. Monthly GTV build (by category: air, hotel, car, homes) 3. Revenue bridge (travel take-rate revenue vs. fintech ancillary revenue vs. Hopper Cloud revenue) 4. Fintech P&L (premium written, claims, net fintech margin by product) 5. Cohort model (existing vs. new cohort contribution to annual GTV/revenue) 6. P&L (3-statement; IS, BS light, CF) 7. CAC / payback / LTV waterfall 8. Scenario toggle (Base / Bull / Bear) with KPI summary 9. Hopper Cloud segment model (partners, ACV per partner, attach revenue) ## Frequently asked questions ### Is the Hopper financial model free? Yes. The Hopper 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.