Understanding Data Minimization Standards Across U.S. State Privacy Laws

Sameer Ahirrao -

Today, data is as valuable as oil, so collecting, using, and storing it responsibly is more important than ever. At the core of this responsible data governance lies a principle that is simple in theory but transformative in practice: data minimization.

What is Data Minimization?

Data minimization means collecting only the personal data that is necessary for a specific purpose, and keeping it only as long as needed to fulfill that purpose. It’s not just about trimming down server space or reducing IT costs, this principle is about protecting individuals' rights, building trust, and minimizing exposure to breaches, misuse, and regulatory scrutiny.

As privacy regulations proliferate across U.S. states, data minimization is taking center stage as a foundational requirement. Let’s explore how this principle is being codified across various state-level privacy laws.

Data Minimization in the U.S. State Privacy Laws

1. Majority Approach (~15 States)

The most common standard, followed by over a dozen states, emphasizes that:

  • Controllers must limit data collection to what is adequate, relevant, and reasonably necessary for the disclosed purposes.
  • Sensitive data cannot be processed without the consumer’s explicit consent.

This model strikes a balance between business operations and consumer privacy, embedding fairness and transparency into data practices.

2. California’s Nuanced Model

California (CPRA Regulations §7002) takes a more contextual approach:

A business’s data practices must be reasonably necessary and proportionate to:

  • The purpose for which the data was collected, aligned with consumer expectations.
  • Any disclosed purpose compatible with the original context.

California’s model integrates contextual integrity, recognizing that the “why” and “how” behind data collection matter just as much as the “what.”

3. Maryland MODPA (Effective October 1, 2025)

Maryland's MODPA introduces stricter boundaries:

  • Only data strictly necessary to provide or maintain a service can be collected or processed.
  • Selling sensitive data is outright prohibited.
  • Consent for sensitive data is not clearly resolved in the statute—creating some ambiguity in practice.

Maryland sets a high bar, especially for sensitive data handling, positioning itself as one of the more consumer-centric models.

Proposed Data Minimization Standards (2025 Legislation)

Several states are enhancing or introducing similar standards in 2025 proposals:

Colorado SB 25-276

  • Limits collection to what is reasonable, necessary, and proportionate for the requested service.
  • Requires prior consent for sensitive data processing or sale.

Connecticut SB 1356

  • Mirrors Colorado’s framework.
  • Prohibits the sale of sensitive data without explicit consent.

Maine LD 1008

Adds detailed obligations:

  • Minimum necessary data per purpose.
  • Documentation of compliance for 24 months post-processing.

Clarifies that sensitive data sales are inherently incompatible across different buyers.

Oregon HB 2008

Extends restrictions to:

  • Processing for unrelated purposes.
  • Selling personal data of consumers under 16 or precise location data.

Vermont H.208

  • Includes communication exceptions (non-advertising) within the data minimization scope.
  • Prohibits sale of sensitive data and restricts its use to strictly necessary service fulfillment.

Failed but Influential Proposals

Some bills didn't make it past the finish line but are worth noting due to their influence:

Oregon HB 3899

  • Proposed a ban on selling sensitive data even with consent.
  • Targeted profiling and targeted advertising using sensitive data.

Maryland HB 1635

  • Largely mirrored MODPA with enhanced language.
  • Continued ambiguity around consent provisions remains a concern.

What Sets These Standards Apart?

Though diverse in language, most frameworks are converging around core themes:

  • Necessity and proportionality: Data must have a clear, justifiable purpose.
  • Consumer consent: Especially for sensitive data, explicit approval is a prerequisite.
  • Limitations on sale and sharing: Increasingly, legislation is treating sensitive data as a category requiring extra protection.
  • Documentation and accountability: Businesses are expected to prove compliance not just claim it.

How Ardent Privacy helps with Data Minimization Standards in Comprehensive State Data Privacy Frameworks

Ardent Privacy plays a crucial role in supporting Data Minimization standards within comprehensive state data privacy frameworks by providing tools and processes that enable businesses to collect, store, and process only the minimum amount of personal data required for specific purposes. Here’s how Ardent Privacy can assist with data minimization:

1. Data Mapping and Discovery: Ardent Privacy assists organizations in mapping their data flows and discovering what personal data they are collecting, processing, and storing. This enables businesses to clearly understand the types of data they hold and identify areas where unnecessary data might be collected. By understanding their data landscape, organizations can reduce the volume of data they collect to only what's essential.

2. Purpose Limitation: Ardent Privacy's purpose limitation emphasizes that personal data should only be collected and processed for specific, explicit, and legitimate purposes, and not used for any other incompatible purpose. This principle is a key aspect of data protection regulations like GDPR, MODPA, CPRA etc

3. Data Minimization in Consent Management: With Ardent Privacy, businesses can manage user consent more effectively. The platform allows organizations to obtain consent for specific types of data collection. This helps businesses avoid over-collecting data.

4. Data Retention Policies: Ardent Privacy enables businesses to create automated data retention and deletion policies. It ensures that data is only kept for as long as necessary to fulfill the stated purpose and is securely deleted or anonymized once it is no longer needed. This reduces the amount of data retained over time, further minimizing data exposure.

5. Privacy-by-Design Integration: Ardent Privacy helps organizations integrate privacy-by-design principles into their data management practices. This means that data minimization is embedded into the organization's systems and processes from the outset, rather than as an afterthought.

6. Compliance with Data Privacy Regulations: Ardent Privacy supports compliance with a variety of privacy laws (such as MODPA, CCPA, VCDPA and others), which have strict data minimization requirements. The platform automates many of the compliance processes, ensuring that organizations are meeting the standards for data minimization as part of their overall data privacy strategy.

By providing these features, Ardent Privacy helps organizations reduce the volume of personal data they collect, store, and process, minimizing the risk of data exposure and ensuring compliance with privacy regulations.

Final Thoughts

Data minimization is no longer just one of the best practices, it’s becoming a strategic imperative. As the regulatory landscape grows more complex, companies that proactively adopt data minimization standards will be:

  • More agile in responding to legal changes.
  • More trustworthy in the eyes of consumers.
  • More resilient against data-related risks.

In a digital economy driven by personalization and data-driven services, adopting a “less is more” mindset isn't a constraint, it’s a competitive edge.