EQEQL Financial Model
Consumer/DTC Startup Financials (Free Excel Download)
B2B SaaS platform managing scarce-product ("hype") launches for retailers - draw/raffle entry capture, fairness algorithm, smart checkout, and analytics.
professionals from Deloitte
Used by professionals from
About this model
EQL is a B2B platform for retailers running scarce-product and hype launches. It provides draw entry, traffic infrastructure, fairness algorithms, checkout, and analytics without forcing brands to replace their existing commerce stack.
The company had run more than 1,000 high-demand launches across 10 markets, analyzing 1.5 million entries and serving more than 720,000 users. Its commercial model is enterprise retail software for brands that need reliable, trusted launch operations.
The model is SaaS and launch-volume revenue. Retail customers, launches, entries, platform fees, usage pricing, expansion, and churn determine revenue. Infrastructure capacity, launch outcomes, enterprise sales, and retention drive profitability.
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 EQL
geteql.com
How to build a detailed financial model for EQL
A complete walkthrough of the business, drivers, and assumptions behind the downloadable EQL model - distilled from its pitch deck and publicly available information.
Product & value proposition
EQL is a headless commerce layer that sits on top of a retailer's existing stack and manages high-demand product launches end-to-end:
- Hype Infrastructure: custom domains and purpose-built stack to absorb traffic spikes without crashing the retailer's core site.
- Fairness Algorithm ("EQLizer"): proprietary draw/raffle engine that boosts odds based on loyalty, proximity, consecutive losses, and other ingestible data points. Trademark: "Run Fair®".
- Smart Checkout / Payments Connect: linear, controlled payment processing; plugs into existing payment gateway; retailer remains merchant of record.
- Launch Automation: end-to-end managed service - product page creation, entry capture, insights, and payments. Dedicated account management.
- Hype Analytics: real-time demand and customer-insight dashboard across launches.
- No-integration required; deployed in days.
Market
- Global streetwear market: $185B in sales
- Resale / circular economy: $25–30B
- Adjacent categories cited but not sized: luxury goods, collectibles, beauty, travel, tickets, NFTs, digital assets
- No SAM or SOM presented. No growth rate given for the platform's addressable market.
Traction & metrics
All from slide 2:
- Launches run: >1,000 high-heat launches
- Markets: 10 markets, 6 languages
- Entries analysed: >1.5M via proprietary fairness algorithm
- Users served: >720K (delivered Run Fair® launches to)
- Funding raised: AUD $25M (Insight Partners + Airtree Ventures)
- Headcount: 21 staff (large engineering focus), targeting ~40 by end of 2022
No revenue, ARR, GMV, churn, NRR, or launch-fee figures disclosed.
Competition / moat
Not explicitly addressed in a dedicated slide. Implied moats:
- Proprietary "Run Fair®" certified fairness algorithm (EQLizer) - differentiated vs generic raffle plugins.
- 1,000+ launches of operational data and ML training data from 1.5M+ entries
- No-integration headless architecture reduces friction vs platforms requiring deep re-platforming
- Named brand customers (Foot Locker, Crocs) act as social proof / switching-cost moat
Team & funding ask / use of funds
- Investors: Insight Partners, Airtree Ventures
- Total raised to date: AUD $25M
- Current headcount: 21 (large engineering focus) → target ~40 by end of 2022
- Founding story: originated from a 2019 Nike/Jordan x Maison Chateau Rouge collab launch ("Fearless collection")
Recommended financial model
Archetype + why: B2B SaaS / per-launch fee hybrid model. EQL charges retailers to run launches on its platform; revenue is most likely a combination of (a) recurring SaaS platform fee and/or (b) per-launch fee, with a potential managed-services layer for account-managed customers. No pricing is disclosed, so the model must be structured to flex around both monetisation assumptions.
Forecast horizon & granularity:
- 3–5 years; monthly for Year 1–2, quarterly for Years 3–5.
- Key unit: launches per month × revenue per launch (or ARR per customer if subscription pricing is assumed).
Key drivers & assumptions:
| Driver | Value | Source |
|---|---|---|
| Launches to date | >1,000 | - |
| Active markets | 10 | - |
| Users in platform | ~720K | - |
| Headcount at model start | ~21–40 | - |
| Engineering % of headcount | ~60–70% | typical early-stage infra SaaS; deck emphasises "Large Eng focus" |
| Revenue per launch | AUD $500–$2,000/launch; no pricing disclosed; enterprise SaaS comps suggest higher per-customer ACV with volume discounts | |
| Launches/month growth | 15–25% YoY; based on 1,000+ cumulative across ~3 years implying ~30–50/month current run rate | |
| Gross margin | 65–75%; SaaS infrastructure business; managed-services component may compress to 50–60% blended | |
| CAC | high (enterprise/mid-market motion); 6–12 month sales cycle; no data given | |
| Churn | low (5–10% annual logo churn) given brand-name customers and account management; no data given | |
| S&M as % of revenue | 25–35% (growth stage, account-managed) | |
| R&D as % of revenue | 30–40% (large eng focus, pre-scale) | |
| G&A as % of revenue | 10–15% |
Scenarios (Base / Bull / Bear - which variables flex):
- Base: launches grow ~20% YoY; revenue per launch stable; managed-services revenue included; gross margin 65%.
- Bull: category expansion (luxury, beauty, NFTs materialises); launch volume +35% YoY; new market entry accelerates; ACV increases as platform matures.
- Bear: retail slowdown reduces hype launch frequency; commoditisation of raffle tech compresses pricing; account-managed costs stay elevated; gross margin compresses to ~50%.
Required sheets / outputs:
- Assumptions & Drivers
- Revenue Build (customers × launches × revenue/launch or ARR × NRR)
- P&L / Income Statement (3-statement if investor-facing)
- Headcount plan (engineering-heavy; ties to opex)
- Cash & Runway (bridge from AUD $25M raise)
- Sensitivity table (revenue/launch vs. launches/month; or ACV vs. logo growth)
- KPI dashboard (launches/month, total users, revenue per launch, gross margin)
Frequently asked
Is the EQL financial model free?+
Yes. The EQL 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 EQL'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
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
Having a template library on hand cuts a first build from hours to minutes.
Need help finding your model? You’ll find me in the Finamodel app!
Other Consumer/DTC Startup Financial Models
Browse another startup in the same category.
Accel Club
Accel Club acquires Amazon third-party (FBA) seller businesses at 3–4x EV/EBITDA and scales them through operational integration, then exits at higher consumer/D2C multiples.
Afrocenchix
D2C brand selling natural, vegan-certified hair-care products for afro and curly hair.
Amperity
Enterprise Customer Data Platform (CDP) that unifies first-, second-, and third-party customer data across siloed systems to power personalization, analytics, and marketing activation.
AnyRoad
Enterprise SaaS platform for managing, measuring, and optimising branded experiential marketing.
Attentive
B2B SMS / mobile marketing SaaS for e-commerce and retail brands.
Aura
All-in-one consumer "intelligent safety" subscription replacing fragmented point solutions for identity, device, WiFi, social, assets, and privacy protection.
Belgian Boys
Belgian-inspired premium specialty food brand selling cookies, refrigerated cheesecakes, frozen waffles/crepes, and snacks through US retail and DTC channels.
Bespoken Spirits
Technology company that replaces barrel aging with a proprietary ACTivation process to produce premium, customizable spirits in days rather than decades.
