Data usage labels in AEP: what I1 and I2 mean and why marketers should care

Why this matters

Marketers who activate audiences rely on data accuracy and compliance. Without data usage labels, they risk using personally identifiable information—like email addresses (I1)—in ways that break privacy rules or violate agreements. This can lead to failed activations or data rejection, wasting time and potentially exposing the organization to regulatory penalties.

A policy defines what data can or cannot be used in marketing actions. If a dataset lacks labels, the system can’t detect if an activation would violate those rules. For example, using a browser ID (I2) in a third-party campaign might breach a policy. Without upfront labelling, marketers only discover the issue at activation time—after data has already been processed. Early labelling during dataset creation prevents these errors and ensures activation workflows stay compliant and reliable.

The key ideas

In Adobe Experience Platform, data usage labels help marketers understand how data can or cannot be used. The most common label is I1, which marks directly identifiable data like an email address. This means the data can be used to directly identify a person. I2 marks indirectly identifiable data, such as a browser ID, which can’t be linked to a person with certainty but still holds personal information. These labels are applied when datasets are created, making it easier to manage data use from the start.

Marketers must understand the policy that governs these labels. A policy defines which labels can be used in specific marketing actions—like sending an email or exporting data. For instance, a policy might forbid using I1 data in third-party exports. If an activation would break such a policy, Experience Platform flags it before the data is sent. This helps prevent compliance issues.

Because labels are applied at dataset creation, it's better to assign them early. Waiting until activation time to discover a label restriction can lead to delays or errors. Knowing what data is I1 and what policies apply helps marketers make safer, more compliant decisions when activating audiences.

How to apply it

When setting up a dataset in Adobe Experience Platform, assign data usage labels during creation to ensure compliance from the start. For example, if a dataset includes email addresses, apply the I1 label to mark them as directly identifiable. If it contains browser IDs or device fingerprints, use the I2 label for indirectly identifiable data. This early tagging helps avoid costly or risky activation errors later.

Define policies that restrict how labeled data can be used—such as banning I1 data from third-party exports. These policies act as rules that prevent unauthorized use. When a marketer attempts to activate an audience using data that violates a policy, Experience Platform flags the action before any data is sent.

Applying labels at dataset creation is more effective than discovering label restrictions during activation. Without upfront labeling, marketers may unknowingly use data that breaks policy rules, risking compliance issues or data misuse. By embedding labels and policies in the data setup phase, marketers ensure their audience activations are both accurate and compliant from day one.

Mistakes to avoid

• Applying data usage labels at dataset creation instead of at activation time prevents last-minute surprises. If a marketer discovers a dataset has I1 or I2 labels during activation, they may not realize it violates a policy restricting use of identifiable data. This can lead to failed activations or compliance risks.

• Marketers should review policies before activating audiences to ensure data use aligns with label restrictions. For example, using I1 data in a third-party campaign may be blocked by policy. Without upfront labelling, such violations go undetected until data is sent—when Experience Platform flags the issue. Proactively assigning labels and verifying against policies stops compliance breaches and ensures activation success.

Quick checklist

• Check if the dataset contains any I1 data (like email addresses) and ensure it’s properly labelled.
• Verify that any indirectly identifiable data (I2, like browser IDs) is tagged with the correct label.
• Confirm that sensitive data is marked with the sensitive (S) label to comply with data governance.
• Review contract labels (C) to ensure no data usage violates agreed-upon restrictions.
• Review the policy settings to confirm that the data labels align with allowed marketing actions.
• Ensure labels are applied during dataset creation, not discovered at activation time.
• Test activation workflows to ensure the system flags any policy violations before data is sent.
• Document the labels and policies used so the team can audit and maintain compliance.