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Integration of Federated Learning for Privacy-Preserving Ad Targeting

The Ad Tech Blog

Moreover, federated learning can improve the efficiency of ad targeting algorithms by enabling them to learn from a broader range of data inputs without compromising on privacy. This includes understanding the data types involved, the privacy requirements, and the desired outcomes of your ad campaigns.

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Google Privacy Sandbox: What Does It Mean for the Future of Targeted Ads?

Single Grain

Privacy concerns have led to the introduction of new data privacy legislation, such as the General Data Protection Regulation ( GDPR ) laws in Europe and the UK. However, as with all after-the-fact legislation, GDPR is based on the technology at the time. Learn More: The Email Marketer’s 4-Step Guide to GDPR Compliance.

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Digiday+ Research: How marketers are using AI to target ads, recommend products and provide customer service

Digiday

With e-commerce sales soaring in recent years, thanks in part to pandemic shutdowns, and the impending death of the third-party cookie driving a need for new data collection capabilities, more marketers are turning to natural language processing (NLP) and data-driven personalization to automate customer service and gather data for ad targeting.