Cloosiv Financial Model

• Consumer-facing mobile app enabling order-ahead at local and mid-market coffee shops.
• POS-agnostic integration - works alongside any existing point-of-sale system.
• Tailored to independent coffee shop branding and workflows; not a generic marketplace.
• Consumer incentives: $3 off first order, $5/user referral (up to 5 friends = $25 max), in-app rewards, in-store promotional kits.
• Four strategic pillars: Point-of-sale agnostic, Tailored Function, Repetitive Value, Network Availability.
• Future product expansion roadmap: Channel Expansion, Social Engagement, Loaded Balance (stored value), Targeted Marketing.

• Independent coffee shops annual sales: $20B.
• Starbucks: $10B, Dunkin': $5B, McDonald's: $3B, Peet's: $1B - provided as context for scale.
• Starbucks app gross volume grew from $0.25B (2011) to $5B (2019) - used as proof of mobile-order adoption.
• Target segment (2019–2020): small specialty chains with 10–30 US locations (e.g. Not Just Coffee 10, Gregory's 29, Birch Coffee 11).
• Target segment (2021–2023): mid-market chains with 14–60 locations (e.g. Blue Bottle 52, La Colombe 30, Stumptown 14).

Three revenue streams, all merchant-side (consumer pays nothing beyond the order):

Stream 1 - Tiered per-order take-rate (primary):

• 12% on orders 1–50/month per location
• 10% on orders 51–150/month per location
• 8% on orders 151+/month per location
• Take-rate applies to gross order value (GMV); paid by the coffee shop.

Stream 2 - Optional merchant service upgrade:

• $499 one-time (or recurring - cadence not stated) fee per merchant location.

Stream 3 - Per-swipe consumer service fee:

• $0.10 per transaction charged to the consumer (in addition to order value).

• GMV growth rate: +40% month-over-month.
• Time series shown (Jul 2018 – Aug 2019) for: GMV, Mobile Orders, Active Users, Coffee Shops on platform, Total Monthly Revenue - all charts show consistent upward trajectory with similar shape.
• All absolute axis values are redacted ("$X" / "X") in every chart - no specific GMV, order, user, or revenue levels can be extracted from the deck.
• Total Monthly Revenue (slide 22): sharp spike at Aug 2019 with footnote "PIVOT TO NEW PRICING MODEL" - implies a meaningful change in revenue recognition or rate structure at that date.
• Case study - Not Just Coffee (est. 2011): Locations, Users, Orders, Volume all redacted (placeholder zeros shown).
• Case study - Piccolo Coffee Co.: Same - all metrics redacted.

• Blended effective take-rate: 8–12% of GMV depending on shop order volume.
• Consumer acquisition cost signals: $3 first-order discount + $5/referral (max $25/referral chain of 5); no total CAC figure disclosed.

• Implicit competitive frame: Starbucks has its own proprietary app; independent shops have none - Cloosiv fills that gap.
• Named competitors: not explicitly listed; deck positions Cloosiv as the only POS-agnostic shared app for independents.
• Moat claims: POS-agnostic architecture, network effects (ubiquity across locations makes the consumer app stickier), tailored coffee-shop UX vs. generic delivery marketplaces.
• Largest chains (Starbucks 12,938 locations, Dunkin' 8,573) explicitly excluded from target - deck focuses on 10–60 location chains and independents.

Team:

• Tim Griffin - CEO (Product, Sales & Marketing)
• James Burkhardt - CTO (Engineering & User Experience)
• Jessie Kolbenschlag - Sales (Business Development & Customer Service)

Ask & use of funds:

• Raising: $1,000,000
• Use: Product, Sales & Marketing
• Post-raise targets: Add 800+ coffee shops; achieve $60K+ monthly net revenue.

Archetype + why: Marketplace GMV model with tiered take-rate revenue. Cloosiv's economics are driven by the number of merchant locations, orders per location per month (which determines which take-rate tier applies), average order value, and consumer fee attach. This is structurally a two-sided marketplace with a dominant merchant monetisation layer, not a pure SaaS ARR model (no recurring merchant subscription as the primary line), though the $499 merchant upgrade adds a SaaS-lite component.

Forecast horizon & granularity:

• 3 years monthly (Sep 2019 – Aug 2022) to match the deck's 2019–2023 targeting roadmap.
• Monthly granularity driven by the deck's own monthly traction reporting and the tiered take-rate (which resets monthly per location).

Key drivers & assumptions:

*Merchant side:*

• Beginning coffee shop count: ~current level implied by Jul 2018–Aug 2019 ramp; exact base unknown - model should parameterise this and sensitise.
• New shops added per month: accelerating post-funding; deck target is 800+ shops post-raise - implies ~30–50 new shops/month over 18–24 months.
• Shop churn rate (monthly): 2–3% - no data in deck; small-business mortality is meaningful.
• Average orders per location per month: start in the 1–50 bracket (12% tier), grow toward 51–150 bracket (10% tier) over 12–18 months as consumer adoption deepens.
• Average order value (AOV): $6–8 - typical specialty coffee ticket; not disclosed in deck.
• GMV growth rate: +40% MoM - use as historical anchor; model should show deceleration as base grows.

*Revenue lines:*

• Take-rate revenue = GMV × effective blended take-rate (function of orders/location distribution across tiers).
• Merchant upgrade revenue = new shops signed × adoption rate × $499; adoption rate 20–30%.
• Consumer swipe fee = total orders × $0.10.

*Cost side (not in deck - all ASSUMED):*

• Payment processing: ~2.5–3% of GMV (Stripe/Braintree standard rates) - must be deducted; material against an 8–12% take-rate.
• Hosting / infrastructure: $2–5K/month scaling with order volume.
• Sales & marketing (post-raise): ~40–50% of raise allocated here per use-of-funds framing.
• Headcount: 3 founders currently; 2–4 hires post-raise.
• Consumer acquisition cost: $5–10/user (referral mechanics imply $5 base cost + discount amortisation).

*Target / milestone:*

• $60K+ monthly net revenue post-raise - use as a model calibration checkpoint.

Scenarios (Base / Bull / Bear - which variables flex):

• Base: 40 new shops/month post-raise, AOV $7, orders/location growing to mid-tier (51–150) by month 12.
• Bull: 60+ new shops/month (viral referrals, strong sales team), AOV $8, shops accelerate to 151+ tier sooner - take-rate compresses to 8% but volume more than offsets.
• Bear: 20 new shops/month (slower B2B sales cycle), higher shop churn (4%), orders/location stay in lowest tier (12% rate, but low volume base).

Required sheets / outputs:

1. Assumptions - all drivers in one place, flagged vs.
2. Merchant cohort model - monthly adds, churn, active shop count by cohort; orders/location ramp per cohort.
3. GMV build - active shops × orders/location × AOV.
4. Revenue - take-rate by tier (requires order distribution across tiers), merchant upgrade fees, swipe fees.
5. Cost build - processing fees (% of GMV), S&M, headcount, infrastructure.
6. P&L summary - net revenue, gross profit, operating expenses, EBITDA.
7. Cash / runway - burn rate vs. $1M raise; months to $60K MRR milestone.
8. Dashboard - GMV, MRR, active shops, active users, effective take-rate, months of runway.