Bigblue Financial Model
AI/ML Startup Financials (Free Excel Download)
Tech-enabled e-commerce fulfillment platform for European D2C brands - "Amazon-standard" delivery without Amazon.
professionals from Deloitte
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About this model
Bigblue is a technology-enabled fulfilment partner for European D2C brands seeking Amazon-standard delivery without selling through Amazon. Its dashboard manages inventory and inbound shipments, while its warehouse network, carrier options, returns portal, and branded tracking communications execute the delivery experience.
Merchants pay per delivery and for storage, with volume discounts as order throughput grows. Bigblue reports more than 350 brands, annual churn of 2.4%, over 3.5-times year-on-year revenue growth, and 60% expansion revenue in 2021; its Fast Tags claim a 40% average sales uplift.
The forecast follows merchant cohorts, orders per merchant, delivery fees, inventory held, and storage pricing rather than a flat subscription. It models warehouse and carrier COGS, working capital, expansion and churn, sales capacity, headcount, gross margin, cash flow, and runway.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Bigblue
bigblue.co
How to build a detailed financial model for Bigblue
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Bigblue model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Outsourced fulfillment for D2C / e-commerce brands operating outside Amazon.
- Three value-prop pillars presented:
- Delivery Promise - "Fast Tags" (Amazon Prime-like badges) shown to increase sales by 40% on average, up to 86% in best cases; checkout Delivery ETA widget; full carrier menu (Free, Express, Standard, Green, Pickup).
- Delivery Success - SaaS dashboard for inventory and inbound shipments; automated warehouse network; branded returns portal.
- Delivery Delight - Branded post-purchase tracking emails (74% average open rate claimed); marketing campaigns embedded in tracking flow.
- Positioning: "new kind of logistics partner leveraging modern technologies." Competes against legacy 3PLs, not Amazon directly.
Market
- +35% growth in e-commerce goods market since 2020.
- 2.0M European e-brands as of Q4 2021 (doubled in 3 years).
- €50B European e-commerce fulfillment market size. - this is framed as TAM; no SAM or SOM breakdown provided.
- Sources cited: Statista, FEVAD, eCommerce News, Bigblue analysis.
Revenue model
Three-component usage-based pricing ("We SaaS-ified delivery"):
- Per-delivery fee - pay-per-shipment; variable with order volume.
- Storage fee - monthly per-item/per-SKU charge; variable with inventory held.
- Volume-based discounts - tiered rates as merchant GMV/order volume grows.
No specific per-unit price points disclosed in the deck. Revenue scales directly with merchant order volume (GMV throughput) and inventory levels. Secondary revenue implied from branded tracking/return portal features (SaaS-like upsell), but not explicitly priced.
Channel: direct sales ("scalable sales process" mentioned, ARPA metric referenced but value redacted).
Traction & metrics
All financial values on the traction slide (slide 10) are intentionally redacted ("XX") in the deck. The following qualitative/relative metrics are stated:
- Revenue growth: >3.5x year-on-year.
- Revenue chart shows bars for 2019, 2020, 2021, 2022(F) - all values shown as "XX" in $M.
- +60% expansion revenue in 2021 (net revenue retention above 100%).
- Annual churn: 2.4%.
- Current Net ARR: €xxM (redacted).
- Signed ARR pipeline: €xxM additional (redacted).
- ARPA: $xxk (redacted).
- LTV:CAC ratio: stated as "xx" (redacted).
- Customers: +350 leading D2C brands.
- Team: 60+ members.
- Tracking email open rate: 74% average.
- Fast Tags sales uplift: 40% average, up to 86% best case.
Unit economics
- LTV:CAC ratio referenced but value redacted.
- ARPA referenced but value redacted ("$xxk").
- 2.4% annual churn implies ~42-year theoretical LTV at constant ARPA - likely gross churn; net churn implied negative given +60% expansion.
- No gross margin, contribution margin, or payback period disclosed.
Competition / moat
- Problem framing positions legacy 3PLs as the competition (slow, limited options, no tracking).
- Amazon implicitly positioned as the delivery standard to match.
- No explicit competitor matrix or named competitors in deck.
- Moat stated as: automated warehouses (enterprise-grade), proprietary tech stack (Fast Tags, ETA, tracking), and branded post-purchase experience.
- Network with Shopify, WooCommerce, PrestaShop, Magento, Wix logos shown - platform integrations as switching cost.
Team & funding ask / use of funds
- Founders:
- Tim Dumain - Founder / CEO
- Mathias Griffe - Founder / CTO
- William Meunier - Founder / COO
- Key hires: Antoine Laurore (Head of Sales), Paul-Marie Dubois (Head of Product), Robin Diligent (Head of Transportation)
- Team size: 60+ members
- Investor/alumni logos shown: Doctolib, Vimeo, Alan, Apple, Amazon, Kapten, Criteo
Recommended financial model
- Archetype + why: Usage-based / transactional 3PL revenue model with SaaS ARR overlay. Primary driver is order volume (deliveries shipped) × per-delivery fee, plus storage revenue (SKUs stored × days × rate). Net ARR metric is used internally suggesting ARR framing for merchant contracts. Closest archetype: usage-based recurring revenue model (similar to transactional SaaS), not a pure subscription model. A 3-statement model is appropriate given physical warehouse operations (COGS-heavy).
- Forecast horizon & granularity: Monthly for Year 1–2 (operational detail needed for cash/working capital); annual for Years 3–5. Suggested: 2022–2026 (5-year).
- Key drivers & assumptions:
- Number of merchant customers (brands): 350; net new merchants/month based on >3.5x YoY growth rate applied to customer cohorts
- Average orders per merchant per month: derived from ARPA and implied per-delivery fee; suggest ~500–2,000 orders/merchant/month as placeholder
- Per-delivery fee (€): €4–8/shipment for European 3PL; not in deck
- Average SKUs in storage per merchant: 20–100 SKUs
- Storage fee per SKU per month (€): €0.10–0.30/SKU/day, industry standard
- Revenue growth rate YoY: >3.5x stated; model at 3.0x–3.5x for 2022, step-down to 2.0x in 2023, 1.5x in 2024, normalizing to 30–40% by 2025–2026
- Net revenue retention (NRR): implied >160% (2.4% churn + 60% expansion); model at 140% NRR conservatively
- Annual gross logo churn: 2.4%
- ARPA ($k): redacted; €30–80k/year per merchant based on 3PL comparable and ARR metric framing
- Gross margin: 25–40% (3PL/fulfillment tech comps; Flexport ~20–25%, ShipBob ~30–35%); not in deck
- Headcount: 60+; grows with revenue, OpEx scales at ~50% of revenue growth rate
- Warehouse CapEx / lease: operating leases in France, Spain, UK; model as variable COGS % of fulfillment revenue
- LTV:CAC: redacted; 3–5x for unit economics build; requires CAC assumption
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: 3.0x YoY growth in 2022, step-down per above; 35% gross margin; NRR 140%
- Bull: 3.5x YoY growth sustained into 2023; NRR 160%; gross margin expands to 45% with automation benefits
- Bear: Growth slows to 2.0x in 2022 (macro / customer concentration risk); churn increases to 5%; gross margin compressed to 25%
- Flexing variables: order volume growth, per-delivery yield, NRR, gross margin %
- Required sheets / outputs:
- Assumptions - all drivers in one place, tagged vs
- Revenue build - merchant cohorts × ARPA, split delivery fees vs storage fees
- P&L (Income Statement) - revenue, COGS (fulfillment ops), gross profit, S&M, R&D, G&A, EBITDA
- Headcount plan - by department, linked to OpEx
- Balance Sheet (light) - AR, inventory (client goods not on BS), PP&E / leases, payables
- Cash Flow Statement - operating CF, CapEx (warehouse automation), net burn / runway
- Unit Economics - ARPA, CAC, LTV, payback, NRR waterfall
- KPI dashboard - MoM orders, merchants, NRR, churn, ARR bridge
Frequently asked
Is the Bigblue financial model free?+
Yes. The Bigblue model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Bigblue's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
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