CCPA Data Minimization Requirements

Introduction

Many businesses associate data minimization with abstract privacy principles or with GDPR-specific requirements. Under the California Consumer Privacy Act (CCPA) and the California Privacy Rights Act (CPRA), data minimization has a more practical role.
Data minimization shapes how much personal information a business collects, how it uses that information, and how long it retains it, based on what is reasonably necessary for disclosed purposes. These limits influence whether data practices remain within scope, whether additional obligations apply, and how regulators assess risk.
This article focuses on data minimization requirements under California privacy law. To understand whether your business falls within scope in the first place, see our CCPA applicability guide. For broader context across obligations, refer to the CCPA compliance guide for businesses.

What data minimization means under the CCPA and CPRA

Under California Civil Code section 1798.100(c), personal information must be collected, used, retained, and shared only to the extent that is reasonably necessary and proportionate to achieve the purposes for which it was collected or processed, as disclosed to the consumer.
This means that data minimization is grounded in the idea that personal information should be:

• Collected for specific, explicit purposes
• Used only in ways reasonably related to those purposes
• Retained only as long as justified by those purposes

The CPRA strengthened this concept by tying it more closely to purpose limitation and use-based restrictions, rather than treating it as a general best practice.
Importantly, data minimization under California law does not require businesses to eliminate data collection entirely. Instead, it requires businesses to evaluate whether their data practices exceed what is reasonably necessary for what they claim to do.

Data minimization does not mean collecting less data

A common misconception is that data minimization means collecting the smallest possible amount of data in every situation. That is not how the CCPA operates.
In practice, data minimization asks different questions:

• Why is this data being collected?
• Is this data necessary to provide the requested service?
• Is it being reused for secondary purposes?
• Is it being retained longer than justified?

A business may lawfully collect significant amounts of personal information if that collection is proportionate to its stated purposes. Problems arise when data is collected “just in case,” reused for unrelated purposes, or retained indefinitely without a clear justification.

Where businesses commonly over-collect personal information

Many data minimization issues arise from routine website and product decisions rather than from intentional misuse.
Common examples include:

• Website forms that request more fields than are needed to complete a transaction
• Analytics configurations that collect granular identifiers without clear necessity
• User accounts that retain historical data long after accounts become inactive
• Tracking tools enabled by default without reassessing their purpose

These practices can increase risk under the CCPA because collecting unnecessary data expands the scope of personal information subject to disclosure, consumer rights, and potential enforcement.
Understanding what qualifies as personal information is a prerequisite for minimization analysis. See what is personal information under the CCPA for a detailed breakdown.

Data minimization examples for ecommerce, SaaS, and media

Example 1: Ecommerce websites

An ecommerce store collects names, shipping addresses, and payment information to fulfill orders. This collection is reasonably necessary and aligned with data minimization.
Issues arise when the same store:

• Requires account creation with extensive profile fields for one-time purchases
• Retains failed checkout data indefinitely
• Collects detailed browsing and purchase history for marketing purposes without reassessing necessity

In these cases, data minimization requires reviewing whether each data element is needed to complete the transaction or whether it supports secondary uses that should be limited, disclosed, or avoided.

Example 2: SaaS platforms

A SaaS provider collects user credentials, usage logs, and support interactions to deliver its service. This is generally justified.
However, data minimization questions arise when:

• Detailed activity logs are retained long after accounts are closed
• Usage data is repurposed for analytics or profiling beyond service delivery
• Optional features collect data by default rather than based on user choice

Minimization in this context often focuses on retention periods, default settings, and whether legacy data remains necessary.

Example 3: Media and content websites

Media websites often rely on analytics, advertising, and personalization.
Data minimization issues may occur when:

• Tracking technologies collect persistent identifiers beyond what is needed for measurement
• Location or device data is collected at a granular level without clear justification
• Historical engagement profiles are retained indefinitely

In these environments, data minimization helps limit how much personal information enters advertising or analytics workflows in the first place.

Data minimization and sensitive personal information

Data minimization becomes especially important when sensitive personal information is involved.
Sensitive personal information is subject to additional use limitations under the CPRA. Collecting or retaining sensitive data beyond what is reasonably necessary increases the likelihood that consumers may be entitled to restrict how that data is used.
For example:

• Collecting precise geolocation to provide a location-based feature may be justified
• Retaining that same data for analytics, profiling, or secondary uses may not be

This interaction between minimization and sensitive data is explained in more detail in our guide on sensitive personal information under the CPRA.

How data minimization affects selling and sharing analysis

Over-collection of personal information also increases exposure under selling and sharing rules.
When more data is collected than necessary, that data may:

• Be disclosed to additional vendors
• Be used for advertising or analytics purposes
• Trigger selling or sharing classifications unintentionally

Minimization helps limit downstream risk by reducing the amount of data that can be transferred, combined, or repurposed.
For more on how disclosures affect selling and sharing obligations, see selling and sharing under the CCPA.

Data minimization, retention limits, and disclosures

Data minimization is evaluated against what a business tells consumers at the point of collection. Under California privacy law, the Notice at Collection plays a central role in defining which purposes justify collection and retention. If a purpose is not disclosed at collection, retaining or reusing personal information for that purpose may conflict with data minimization expectations.
Data minimization is closely linked to retention practices and disclosure accuracy.
Under California privacy law, businesses are expected to disclose:

• The purposes for which personal information is collected
• How long categories of personal information are retained, or the criteria used to determine retention

If data is retained longer than necessary for disclosed purposes, those disclosures may no longer accurately reflect actual practices.

Where tools and platforms can support data minimization

Data minimization also applies when businesses respond to consumer rights requests (also known as data subject requests). Verification steps and request handling must themselves follow minimization principles, meaning businesses should not require more personal information than is reasonably necessary to process a request, as emphasized in recent CPPA enforcement guidance.
Once businesses understand data minimization requirements, the next challenge is maintaining visibility into how data collection and retention evolve over time.
Platforms like Clym provide tools that support privacy operations connected to data minimization, without replacing legal analysis or determining scope on their own. Relevant capabilities include:

• Cookie Scanner
• Consent Widget
• Privacy & Cookie Policy Management
• DSAR management
• Governance Portal and Control Center

Next steps

Data minimization is a core concept that connects applicability, personal information definitions, sensitive personal information, and selling or sharing analysis.
To see how these obligations fit together, explore our CCPA 2026 compliance guide for businesses. For related topics, review our article which explains CCPA applicability, what is personal information under the CCPA or what counts as selling and sharing under the CCPA.