v3.0
Privacy SDK

Use Cases / Case Studies

The ADARA Privacy Token Server SDK framework for collecting and processing data securely without third-party cookies allows matching and linkage to consortium identities, as well as generating and managing ADARA Privacy Tokens. Use these privacy tokens to help address your use cases such as:

  • Provide a secure, private, durable, and agnostic mechanism for identity recognition across consortiums and data platforms
  • Create a private set of anonymized tokens to obscure privacy-centric data on your own cloud or servers
  • Avoid privacy breaches with a decentralized approach to data augmentation
  • Link your customers to the over 1 billion digital identities in ADARA’s Digital Identity Graph
  • Harmonize and combine the disparate digital identities associated with your customers
  • Access ADARA's globally-scaled identity network to increase reach and addressability on the ADARA Cortex platform to meet your marketing and advertising goals
  • Match your existing third-party cookie data to first-party to maximize retention of your existing digital assets as platforms and browsers continue to progressively eradicate third-party cookies
  • Leverage harmonized digital identities through ADARA's identity solutions to address your Identity Verification (IDV) and fraud detection use cases
  • Securely share tokenized data with public consortiums where you can monetize your data while controlling how your data is used
  • Securely share tokenized data with private data consortiums to control how your data is shared and collaborate with other groups within your corporate organization, partner organizations, or even your customers
  • Securely and privately share tokenized data between between outside collaborators without involving ADARA
  • Tokenize data on your site to ensure that your customer data does not leave their firewall
    • Future-proof against using registration data like email addresses to link individuals between brands and publishers
    • Avoid portability issues inherent in browser-specific non-individualized cohort development schema, such as Chrome's “Federated Learning of Cohorts (FloC)”
    • Bypass the identity harmonization limitations inherent in a decentralized 'data bunkers' approach