The CUV Framework
Consent, Utility, Value. A simple, repeatable method for evaluating whether a data use case is ethical, valuable, and legally defensible.
CUV (Consent, Utility, Value) is a framework for responsibly activating marketing data through compliant, consumer-centric use cases.
Purpose
The CUV Framework provides a simple, repeatable method for evaluating whether a data use case is ethical, valuable, and legally defensible.
It helps marketing and data teams decide if and how data should be activated, balancing customer consent, perceived utility, and fairness of value exchange.
Used consistently, CUV builds a shared standard for responsible data activation across teams, vendors, and markets.
Model overview
| Component | Definition | Key question |
|---|---|---|
| C, Consent | Legal and ethical permission from the consumer to collect and use data. | Do we have explicit, informed consent for this purpose? |
| U, Utility | The usefulness or perceived benefit to the consumer from the data use. | Does this create a real or perceived benefit for the consumer? |
| V, Value | The fairness of exchange between brand and consumer. Whether the value delivered matches the data’s sensitivity. | Is this a fair trade that respects the consumer’s privacy and expectations? |
Core principle: consent is non-negotiable. Utility and Value can be optimised, but consent must always be explicit and provable.
How to use it
1. List all data use cases. Each campaign, integration, or automation that touches consumer data.
2. Score each use case across the three CUV dimensions:
| Factor | Description | Scale |
|---|---|---|
| Consent (C) | Strength and explicitness of permission. | 0–5 |
| Utility (U) | Real or perceived consumer benefit. | 0–5 |
| Value (V) | Fairness and balance of exchange. | 0–5 |
3. Calculate the composite score:
CUV Score = (C × 2) + U + V
Consent is weighted more heavily to reflect its legal and ethical primacy.
4. Interpret results:
- 16–20: Responsible use; proceed.
- 11–15: Moderate risk; redesign or clarify value exchange.
- ≤10: High risk; obtain explicit consent or discontinue.
5. Document each evaluation in your Data Use Register alongside consent source, data type, and processing purpose.
Compliance best practice
For each use case, record:
- Consent source: where and when permission was collected.
- Purpose alignment: confirm that use matches the stated intent.
- Data category: personal, behavioural, inferred, or sensitive.
- Legal basis: consent, contract, or legitimate interest.
- Retention period and safeguards: time limits, access controls, encryption.
Aligns with:
- GDPR Articles 5 (principles), 6 (lawfulness), and 7 (consent), lawful processing, consent, and purpose limitation.
- Australian Privacy Principles 1.2 & 6, accountability and use limitation.
- IAB Europe TCF, digital advertising consent framework.
Use case library
| Use case | CUV Score | Assessment | Action |
|---|---|---|---|
| Personalised Email Recommendations | C=5, U=4, V=4 → 17 | Fully consented, high relevance. | Proceed; monitor opt-outs. |
| Data Enrichment via Third-Party Provider | C=2, U=3, V=2 → 9 | Weak consent provenance, unclear benefit. | Suspend; review vendor and consent chain. |
| Cross-Device Tracking for Attribution | C=3, U=4, V=3 → 13 | Useful but high sensitivity; consent may be implicit. | Review; improve disclosure and consent capture. |
| On-Site Personalisation via First-Party Cookie | C=5, U=5, V=4 → 19 | Strong consent and clear utility. | Proceed; document lawful basis and retention. |
Outcome
The CUV Framework standardises ethical evaluation of data use cases.
It creates an auditable link between marketing innovation and compliance discipline, ensuring every activation respects consent, delivers genuine consumer utility, and upholds a fair value exchange.
When combined with the Data Value Quadrant, CUV becomes the ethical filter that precedes plotting or activating any data use case.