Artificial Intelligence · 30.07.2026, 16:48 UTC
How Yahoo enhances search retargeting using Amazon Bedrock
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | AWS Machine Learning ↗ |
| Veröffentlicht | 30.07.2026 UTC |
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Connecting user search intent with relevant ad experiences across channels is a longstanding challenge in digital advertising. Advertisers need sophisticated ways to reach audiences based on their demonstrated interests and behaviors, particularly their search activity, which is one of the strongest signals of user intent. Traditional keyword expansion approaches often struggle with outdated vocabulary, limited semantic understanding, and inability to capture the nuanced meaning behind search queries. The Yahoo omnichannel Demand-Side Platform (DSP) addresses these challenges by providing advertisers with advanced technology, premium supply access, vast scale, and trusted consumer relationships. A DSP lets advertisers purchase ad inventory across multiple exchanges and channels through a single interface. Yahoo DSP enhances this capability with sophisticated audience targeting powered by advertiser-defined rules, machine learning (ML), and generative AI. At the heart of this targeting is the concept of an audience segment: a group of users who share specific interests, demographics, or behaviors and can be targeted collectively in advertising campaigns. These segments are passed to targeting systems for ad serving, making sure that users are matched with the most relevant advertiser campaigns. In this post, we demonstrate how Yahoo implemented Amazon Bedrock to enhance their Search Retargeting (SRT) capabilities in the Yahoo DSP ad tech suite. SRT is a core audience targeting solution that helps advertisers reach users based on their historical search behavior, bridging …
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