SOC 2 P2.1: Privacy - Choice and Consent
What This Control Requires
The entity communicates choices available regarding the collection, use, retention, disclosure, and disposal of personal information to the data subject and the consequences of each choice to meet the entity's objectives related to privacy. Explicit and implicit consent is obtained from data subjects as required.
In Plain Language
If you are collecting personal data, people need to have a genuine choice about it - and they need to understand what happens if they say no. Pre-checked boxes and buried opt-outs do not count.
In practice, this means building proper consent mechanisms: clear opt-in for sensitive data and marketing, easy opt-out where regulations allow implied consent, and honest explanations of what users lose by declining. Every consent decision needs to be recorded - who agreed, when, to what exactly, and how. Auditors will ask for these records.
The key word here is "meaningful." Auditors evaluate whether your choices are genuine (not dark patterns), whether consent matches the sensitivity of the processing, whether you actually honour the choices people make, and whether you can prove it all with records.
How to Implement
Map every data collection and processing activity to the appropriate consent mechanism. Consider GDPR lawful bases (consent, legitimate interest, contractual necessity), CCPA opt-out requirements for sale and sharing, and any industry-specific rules that apply to your business.
Build consent collection that is unambiguous. For explicit consent, use unchecked opt-in boxes with specific language describing what the person is agreeing to. For email marketing, implement double opt-in. For implied consent scenarios, make the implied terms clear in your privacy notice and provide straightforward opt-out.
Give users a preference centre where they can view and manage all their consent choices in one place. Make withdrawing consent as easy as granting it - if they clicked one button to opt in, they should be able to click one button to opt out. When preferences change, update your processing immediately.
Keep detailed consent records. For every consent event, log who consented, when, the exact version of the consent language they saw, the method (checkbox, form, written), and any subsequent withdrawal. These records are your primary audit evidence.
Write consent language that is specific and unbundled. Do not lump multiple consent requests into one checkbox. Use plain language. State clearly what happens if someone declines - for example, "You will not be able to use personalised recommendations." Link to the full privacy notice for detail.
Define a process for handling withdrawals. When someone revokes consent, stop the associated processing promptly. Decide in advance what happens to data already collected under prior consent. Confirm to the user what actions you have taken and any resulting limitations to their service.
Evidence Your Auditor Will Request
- Consent mechanism designs and implementations for all data collection and use activities
- Consent records showing who consented, when, to what, and by what method
- Privacy preference center or consent management platform documentation
- Consent withdrawal process documentation and records of consent withdrawals honored
- Consent language versions with clear, specific descriptions of data processing activities
Common Mistakes
- Consent checkboxes are pre-checked, undermining the validity of opt-in consent
- Consent language is vague or bundled, not allowing granular choices for different processing activities
- No records of consent are maintained, making it impossible to demonstrate valid consent
- Consent withdrawal requests are not processed in a timely manner or are not honored completely
- Consequences of declining consent are not communicated to data subjects
Related Controls Across Frameworks
Frequently Asked Questions
When is explicit consent required versus implied consent?
Do we need a consent management platform?
How do we handle consent for existing users when we change our data practices?
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