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Your data is an asset. You are not pricing it.
"Only 39% of firms manage data as a formal business asset. Top performers generate 11% of revenue from it. Lower performers generate 2%. The gap is not a technology problem. It is a decision problem."
39%
Of firms manage data as a formal business asset. The remaining 61% own an underpriced asset.
(SQ Magazine, 2026)
(SQ Magazine, 2026)
11% vs 2%
Revenue from data monetization: top performers vs lower performers. A 5x gap.
(McKinsey, 2025)
(McKinsey, 2025)
THE DECISION STAKES
The asset is there. The revenue model is not.
"Data has become one of the most valuable assets in today's digital economy, driving new revenue streams and reshaping business strategy." — SQ Magazine, Data Monetization Statistics 2026, February 2026
The question is not whether your data has value. It does. The question is whether you have a pricing model, a package, and a governance layer that lets you extract it without exposing yourself.
Internal monetization reduces costs and improves decisions. External monetization creates recurring revenue. Both require the same foundation: an inventory, a price, a product, and a compliance posture.
THE DECISION TOOL
Four moves. One decision you can defend.
01
MAP
Inventory every data asset by category: transactional, behavioral, operational, proprietary. For each, assess uniqueness, timeliness, and addressable use. Most enterprises discover 3 to 5 assets they did not know they could price.
Without an inventory, you cannot build a monetization strategy. You build a data lake. A lake without a pricing model is a storage cost.
02
PRICE
Assign a shadow price to each asset: what would a buyer pay for this insight if it saved them one decision-cycle or reduced one risk? Internal shadow pricing reveals which assets justify external investment
Shadow pricing changes the internal conversation. A data asset worth 2M euros per year in prevented churn is not a BI project. It is a product with a P&L.
03
PACKAGE
Decide the commercialization model per asset: internal analytics, API subscription, data partnership, or insight-as-a-service. The packaging determines the margin. Raw data commoditizes. Insight scales.
The companies with the highest data revenue do not sell data. They sell decisions. Mastercard does not sell transaction records. It sells economic intelligence.
04
GOVERN
Build compliance-by-design into the monetization layer: consent architecture, data minimization, contractual guardrails, audit trail. GDPR, CCPA, and sector-specific rules apply. Governance is not a constraint on revenue. It is the condition for recurring revenue.
The enterprise with clean, consented, auditable data can sell what competitors cannot. Governance transforms a compliance burden into a competitive moat.
Mastercard
USD 32.8bn revenue FY2025. Value-Added Services and Solutions: fastest-growing segment.
(Mastercard FY2025 Annual Results, February 2026)
20-25%
Value-Added Services and Solutions revenue growth YoY in FY2025. The segment includes data analytics, business and market insights, security and authentication services built on Mastercard's transaction data.
(Mastercard FY2025 Annual Results, February 2026)
Mastercard does not sell transaction records. It packages 10.6 trillion dollars in annual gross dollar volume into intelligence products: economic indicators, fraud models, consumer behavior analytics, and market insights. These products are sold to governments, retailers, financial institutions and enterprises that cannot generate this view from their own data alone. The Value-Added Services segment now grows faster than the core payment network, at 20 to 25% annually. The raw material was always there. The decision to price it, package it, and govern it is what created the revenue line.
Mastercard did not acquire a new asset. It decided to treat the asset it already had as a product. That decision is the entire gap between 2% and 11%.
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Key questions
Which of your data assets would your largest competitor pay for, and why are you not already pricing it as a product?
How do you build a compliance-by-design architecture that makes your data sellable without creating GDPR or CCPA exposure for your legal team?
When your shadow pricing exercise reveals a data asset worth EUR 3M in prevented churn, what organizational change is required to treat it as a product rather than a BI project?
Pre-decision checklist
MAP — completed
PRICE — completed
PACKAGE — completed
GOVERN — completed
By Fabrice Macarty
This case resonates?
Map every data asset you own but do not price. Assign a shadow price to the top five. Package the highest-value as insight, not raw data. Then govern it so you can sell it again next year.
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