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How Google Ads Asset-Based Audience Signals Improve Targeting
Description
In this episode, Lucas and Luna dive into Google Ads' shift from traditional audience targeting to asset-based audience signals. They explore how advertisers can use images, videos, and text from their campaigns to let Google's machine learning find the right users, rather than manually defining audiences. Using a concrete example from a mid-size e-commerce brand selling ergonomic office chairs, they walk through the setup process, the impact on cost per acquisition, and why this approach reduces audience fragmentation. Lucas explains the key difference between audience signals and old-school targeting, while Luna questions whether this hands-off approach works for niche products. The hosts also discuss the role of first-party data and how asset-based signals interact with Performance Max campaigns. Listeners will learn how to test this feature and what metrics to watch for success in Q3 2026.