# Stayflexi Financial Model Modern operating system for hotels and vacation rentals - SaaS management platform plus transactional upsell engine - Canonical: https://finamodel.com/startups/stayflexi - Excel download: https://finamodel.com/startup-models/stayflexi.xlsx - Category: Marketplace - Model type: Marketplace / GMV - Funding round: Seed - Funding: $1.6M - Founded: 2021 - Geography: US & India [DECK slide 15] - Customer: B2C ## About the company Stayflexi is an operating system for hotels and vacation rentals that combines property management with a digital sales engine. It manages reservations, channels, housekeeping, revenue, payments, and operations while enabling guests to purchase upgrades, early check-in, late check-out, and in-room services. The company reported 650 properties and more than 10,000 rooms managed, growing properties 30% month over month. Its business has two revenue streams: recurring per-property software fees and a transactional share of upsell and ancillary sales processed through the platform. The model separates property SaaS ARR from guest-transaction revenue. Properties live, rooms, ARPU, and churn build subscription revenue; occupied rooms, upsell attach, average ancillary spend, and take rate build marketplace revenue. Property onboarding, hotel retention, payment costs, and guest adoption determine margin. ## 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 Stayflexi OS is a unified hotel property management system (PMS) built around guest flexibility and revenue automation. Two engines: - **Management Engine (SaaS):** Reservations management, channel management, inventory calendar, housekeeping, revenue management, POS/shops, accounting, staff management, access control, reporting - **Sales Engine (Transactional):** Direct website booking, booking extensions (early check-in / late check-out), pre-check-in upsell purchases, in-room purchases, contactless payments Guest journey is fully digitised: reserves via OTA/direct site → self check-in via WhatsApp → self-upgrades → in-room orders → booking extension → self-checkout. Platform also supports post-stay review management and guest retention/retargeting. Key value claim: a single flexible booking example would add $300 of incremental revenue and save 30 minutes of hotel staff time. ## Market No explicit TAM/SAM/SOM dollar figures in the deck. Context provided: - 80% of guests ask for early check-ins / late check-outs, yet few hotels can provide them - Vacation rentals projected to grow 5x in the next 3 years post-COVID, fuelled by Airbnb - Deloitte Hospitality Outlook cited as source for alternative revenues, automations, and guest connectedness ## Revenue model Two-stream model: 1. **SaaS subscription** - Management Engine; recurring monthly/annual fee per property. No price point disclosed in deck. 2. **Transactional revenue** - Sales Engine take-rate on upsell transactions (early check-in, late check-out, in-room orders, room upgrades, booking extensions, ancillary services). No take-rate % disclosed. Distribution channels shown: Airbnb, Google, Booking.com, Expedia, TripAdvisor (OTA channel management), plus direct website. Payment infrastructure via Stripe and Shift4 Payments. ## Traction & metrics - 650 properties on platform - 10,000+ rooms managed - 30% MoM property growth - Growth chart (slide 13): 60 properties in Jan 2020 → ~150 May 2020 → ~325 Sep 2020 → 650 Feb 2021 - Funding raised: $1.6M - Target implied by opportunity slide: 3,000+ properties in US & India ## Unit economics Single illustrative data point: one flexible-booking guest interaction adds ~$300 revenue per booking while saving 30 min of staff time - not a stated average, presented as example. ## Competition / moat Implicit moat: end-to-end control of the booking funnel from search through post-stay; integrations with all major OTAs, Google, Airbnb plus WhatsApp-native self-service reduce switching friction; YC backing signals quality bar. ## Team & funding ask / use of funds **Team:** - Venkatesh Sakamuri - CEO / Product; MS CS Carnegie Mellon; ex-Oracle - Preetam Shetty - CTO / Tech; MS CS Cornell; ex-Oracle - Sasank Talasila - CIO / UI; MS CS Cornell; ex-Oracle **Funding:** - Raised to date: $1.6M - No explicit ask amount, valuation, or use-of-funds breakdown in deck --- ## Recommended financial model - **Archetype + why:** Dual-stream SaaS + transactional marketplace model. The Management Engine is a classic per-property SaaS subscription. The Sales Engine is a GMV/take-rate layer on top - similar to how Toast or Mindbody layer payments on PMS. Both streams must be modelled separately because their growth drivers, margins, and predictability differ significantly. - **Forecast horizon & granularity:** 3 years monthly (Year 1 monthly detail, Years 2–3 quarterly then annual roll-up). Monthly is essential to capture the MoM property growth curve. - **Key drivers & assumptions:** | Driver | Value | | -- | -- | | Properties at model start | 650 | | MoM property growth rate | 30% | | Average rooms per property | ~15 | | Monthly SaaS fee per property | $150–$300 | | Average upsell revenue per occupied room-night | $25–$50 | | Transactional take rate | 10–20% | | Average occupancy rate (hotel customers) | 60% | | Average room rate (for transaction GMV sizing) | $100 | | SaaS gross margin | 75% | | Transactional gross margin | 50% | | Blended S&M % of revenue | 30% | | Monthly churn (properties) | 2% | | Headcount growth | model as % of revenue until revenue data available | - **Scenarios (Base / Bull / Bear - which variables flex):** - **Bull:** MoM growth sustains at 25–30% for 12 months, ACV per property at top of range ($300/mo), take rate 20%, churn 1% - **Base:** Growth decelerates to 10–15% MoM by month 12 as TAM concentration hits; ACV $200/mo; take rate 15%; churn 2% - **Bear:** Growth falls to 5% MoM (execution / market saturation in India); ACV $150; take rate 10%; churn 3.5% - **Required sheets / outputs:** 1. **Assumptions** - all drivers above with scenario toggles 2. **Property Cohort Model** - monthly new property adds, churn waterfall, active property count 3. **SaaS Revenue** - active properties × monthly ARPU 4. **Transactional Revenue** - active properties × avg rooms × occupancy × room-night AOV × take rate 5. **P&L** - blended gross profit, OpEx (S&M, R&D, G&A), EBITDA 6. **Cash & Runway** - starting from $1.6M raised; monthly burn; months of runway 7. **KPI Dashboard** - ARR, properties, rooms, GMV, take-rate revenue, blended ARPU, LTV/CAC (when data available) ## Frequently asked questions ### Is the Stayflexi financial model free? Yes. The Stayflexi 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.