Data Diligence

Our data governance processes and policies ensure our data drives positive change without compromising privacy.

Privacy protected

At smrtr our first consideration is the law, which defines personal information as “information or an opinion about an identified individual, or an individual who is reasonably identifiable”. We have three key factors to consider when managing and using personal information:

  1. Privacy and Compliance: We rely on a wide variety of partners to power our data universe. Our contracts ensure all data providers must meet applicable privacy requirements when sourcing, using, and sharing data.
  2. Opt-out: Consumers can easily opt-out of their data being used by us and our clients.
  3. Security: We use the highest level of encryption to transfer data and our cloud backend security is at the highest industry standards.

Anonymised data

We address the balance of maintaining privacy and maximising data value by aggregating our data into micro-segments so that we cannot identify specific individuals. This means we can derive insights and create audiences without passing through individual-level data.

Privacy protected

At smrtr our first consideration is the law, which defines personal information as “information or an opinion about an identified individual, or an individual who is reasonably identifiable”. We have three key factors to consider when managing and using personal information:

  1. Privacy and Compliance: We rely on a wide variety of partners to power our data universe. Our contracts ensure all data providers must meet applicable privacy requirements when sourcing, using, and sharing data.
  2. Opt-out: Consumers can easily opt-out of their data being used by us and our clients.
  3. Security: We use the highest level of encryption to transfer data and our cloud backend security is at the highest industry standards.

Anonymised data

We address the balance of maintaining privacy and maximising data value by aggregating our data into micro-segments so that we cannot identify specific individuals. This means we can derive insights and create audiences without passing through individual-level data.

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