MFour is one of the few mid-size firms that is genuinely both a data licensor — OmniTraffic® datasets and MFour Studio™ subscriptions, sold directly and via the Snowflake Marketplace — and a data buyer, through Fair Trade Data® panel compensation. Both sides of that model are financeable.
OmniTraffic® datasets and MFour Studio™ subscriptions are sold under recurring contracts to creditworthy counterparties — Google, Microsoft, Samsung, Walmart, Disney, Spotify — plus marketplace distribution through the Snowflake Marketplace listing for App + Web Data.
Fair Trade Data® panel compensation ("Payday") is a recurring, predictable data-acquisition cost — a stable obligations stream on the buy side of the model.
This combination — contracted recurring revenue on the sell side, stable cost obligations on the buy side — is exactly the profile non-dilutive lenders underwrite. Key caveat throughout: the collateral is the contracts and receivables, never the raw data itself, given first-party consent and privacy restrictions.
Structure: advance against invoices or contracted license/subscription revenue from investment-grade customers; repayment from collections.
Why it clears: blue-chip payer base, recurring billing, low dilution sensitivity (only ~$5M raised since 2017).
Typical terms: 70–90% advance rate on eligible receivables; cost roughly 8–18% annualized depending on tenor and concentration.
Lender diligence asks: customer concentration, contract assignability, churn/renewal rates, billing currency and jurisdiction.
Structure: facility secured against qualifying license revenue and MFour's identifiable IP — trademarks (OmniTraffic®, Fair Trade Data®, DANI™, Surveys On The Go®), the Apple-approval moat, panel relationships, methodology patents, and the curated dataset corpus with 2+ years of history.
Why it can clear: durable, defensible data asset with demonstrated marketplace monetization; recurring revenue supports debt service.
Lender diligence asks: IP ownership chain (especially any co-developed data rights), license contract security/assignment clauses, consent-based usage restrictions, revenue history (≥24 months preferred).
Most data companies monetize only one side of the counterparty relationship. MFour monetizes both — and each side maps to a different financing instrument.
The key insight: the collateral is never the raw consumer data — first-party consent and privacy restrictions make it weak collateral. The collateral is the contracts, the receivables, and the identifiable IP. That framing is what makes both routes credible, and it is the framing MFour's counsel will already be comfortable with.
| Route | Fit | Rationale |
|---|---|---|
| A — Receivables / revenue-based financing | High | Recurring license and subscription revenue billed to creditworthy brands; the lead recommendation. |
| C — IP-backed lending / structured credit | Moderate–High | Real IP moat (panel, Apple approval, trademarks, methodology); credible where license contracts permit security. |
| B — Trade / supply chain finance | Low | No physical goods — LCs and documentary collections not applicable. Sole niche: a payables facility against Fair Trade Data® panel payouts; specialized, not a lead product. |
| D — Non-security / unregulated tokens | Not recommended | Tokenizing consented first-party consumer data conflicts with privacy and consent restrictions and adds regulatory risk without financing benefit. Excluded from recommendation. |
This page speaks for itself. If any route is relevant, the next step is simply understanding MFour's licensing model — from there we identify the most credible financing options. CONTACT