Elaine follows privacy by design and by default: privacy-aware data use is built into the platform’s processing model instead of being treated only as an administrative task after data has been collected. Marketing teams can use engagement data while applying explicit controls to recipient-level profiling, permissions, access, and accountability.
Privacy is a product capability
Elaine connects customer data, content, campaigns, automation, and analytics. Because these capabilities can process personal data, privacy controls must operate where the data is used. Elaine therefore combines organizational governance with technical enforcement at the level of recipients, data sources, and individual profiling purposes.
This is particularly important when multiple profile, transaction, behavior, product, recommendation, and context sources contribute to an individual decision, including in campaigns involving millions of recipients. PAC, data-source context, permissions, consent-aware processes, and privacy-aware defaults help ensure that only data permitted for the intended purpose enters that decision.
This approach helps teams pursue three goals together:
- use permitted data to create relevant customer engagement;
- limit personal processing when the required permission is not available;
- keep responsibilities and data-use decisions understandable for marketing, privacy, and technical teams.
Privacy by design
Privacy controls are connected to the functional workflows that use data. Privacy Admission Control (PAC), for example, represents permitted recipient-level profiling purposes through PAC flags. Data sources connect those permissions with the origin and context of recipient data. Elaine can then take the assigned permissions into account when processing reactions such as opens, clicks, conversions, or other engagement signals.
Privacy by default
A privacy-aware default avoids assuming the broadest possible permission. When a system is introduced or existing data is migrated, teams can start with a deliberately limited data-use level and extend it only where the relevant permission has been captured and assigned. The precise default and enabled PAC capabilities depend on the Elaine configuration and the organization’s governance model.
Aggregate measurement without unrestricted personal profiling
Elaine can distinguish aggregate measurement from recipient-level processing. For example, if an opening is measured for a recipient without the relevant User Profiling permission, the event can contribute to aggregate statistics without being added to that recipient’s personal message history. This separation preserves useful campaign measurement while limiting personal data use.
Governance across the data lifecycle
| Governance question | Elaine capability |
|---|---|
| Where did the recipient data originate? | Data sources identify the collection or import context. |
| Which recipient-level uses are permitted? | PAC flags represent defined profiling and data-use permissions. |
| How is permitted data activated? | Audiences, personalization, automations, and analytics use the data made available to their workflows. |
| Who may configure or operate the platform? | Tenants, users, roles, and permissions separate data, responsibilities, and access. |
| How are external systems governed? | Dedicated integration identities, scoped permissions, secure interfaces, and optional network controls protect connected workflows. |
Note
Elaine provides technical capabilities for implementing privacy and consent requirements. The controller remains responsible for selecting an appropriate legal basis, designing notices and consent processes, configuring retention, and validating the implementation for the applicable jurisdiction and use case. This documentation is not legal advice.