Privacy-Safe Ad Targeting
Intelligent Dynamic Ad Delivery for the Cookieless Future
TieSet’s patented Decentralized Federated Learning framework enables intelligent ad targeting, without dependence on identifiers like the cookie or mobile device ID. User data stays with the owner, training models on the edge device, and only resulting intelligence is shared.
Consumer sentiment is driving a privacy revolution, with regulations gaining momentum worldwide, and major platforms responding by removing identifiers or requiring users to opt-in to identification. Publishers report earning only 50-70% CPMs on anonymized traffic compared to impressions with a cookie, but by 2022, no major browsers will continue supporting this outdated technology. In the mobile ecosystem, Apple is already moving to automatically opt users out of sharing the IDFA (Identifier for Advertisers), on which app campaign targeting relies.
Such changes in the ecosystem tend to drive more dollars toward the walled gardens, but independent players can compete. Continue driving top CPMs for publishers by delivering the results advertisers expect in a sustainable, ad-supported, privacy-protected internet.
Privacy By Design
Traditional centralized databases require data to be pooled in the cloud, presenting significant security risks, potentially violating privacy regulations, and adding unnecessary latency, energy, and cost of large data uploads. TieSet’s decentralized Federated Learning platform instead keeps all data on edge devices, training AI models and uploading them as anonymized and sanitized intelligence.
Data Management Becomes Intelligence Management
1. Replace “Tracking” cookies with edge ML modules, to generate user model
2. Replace database of user profiles with user models
3. Match Ad inventory with user model instead of user private information