New capabilities help advertisers improve audio campaign performance through AI-powered optimization and audience expansion

Podscribe, the leading attribution, measurement, and verification platform for audio advertising, today announced two major additions to SmartServe, its audio ad targeting control platform: AI Optimize and Lookalike Audience Targeting. Together, these capabilities help advertisers improve campaign performance by either automatically optimizing impression delivery with machine learning or expanding reach to new, high-value listeners.

As audio advertising continues to evolve, advertisers are looking for smarter ways to activate the insights generated by attribution and measurement. These new SmartServe capabilities turn campaign data directly into optimization strategies, enabling brands to reach more of the right listeners while reducing manual campaign management.

“Measurement shouldn’t stop at reporting, it should power better and more informed campaign decisions,” said Pete Birsinger, CEO, Podscribe. “With AI Optimize and Lookalike Audience Targeting, advertisers can immediately act on the insights they’re already collecting, whether they want AI to continuously optimize delivery or prefer greater control over audience targeting.”

AI Optimize: Machine Learning To Improve Performance

AI Optimize uses Podscribe’s historical campaign performance data to automatically identify and serve impressions that are most likely to drive conversions.

Rather than relying on manually configured targeting rules, the model evaluates signals such as listener demographics, geography, device, listening app, frequency, ad placement, prior engagement, and time of day to determine which impressions offer the highest likelihood of success.

On average, brands using AI Optimize have seen a 3x improvement in impression performance compared to their historical campaign average.

Advertisers simply set their desired daily impression goal, while AI Optimize dynamically adjusts optimization thresholds to maximize performance.

Lookalike Audience Targeting: Expand Beyond Existing Customers

For advertisers looking to scale beyond retargeting, SmartServe now offers Lookalike Audience Targeting.

The feature identifies households that closely resemble a brand’s existing customers and website visitors using signals such as listening behavior, geography, household characteristics, and device attributes.

While site visitor retargeting remains one of the highest-performing audience strategies, its reach is naturally limited by the size of a brand’s existing audience. Lookalike audiences help overcome that limitation by finding new listeners with similar characteristics, delivering an expected 1.5–2.5x improvement in performance while significantly expanding campaign reach.

Future enhancements will include configurable similarity thresholds and performance projections to help advertisers balance audience scale and precision before launching campaigns.

Turning Measurement Into Activation

Both capabilities are built directly on the attribution and measurement data already available within Podscribe, allowing advertisers to move seamlessly from understanding campaign performance to improving it.

Whether advertisers choose AI-driven optimization or hands-on audience targeting, SmartServe provides flexible tools to help brands maximize performance while reducing manual optimization effort.

Lookalike Audience Targeting is available now within SmartServe. AI Optimize is available today at a promotional rate of $1.50 CPM through the end of 2026 ($3 CPM thereafter).

To learn more or activate these capabilities, visit www.podscribe.com or contact partnerships@podscribe.com.

About Podscribe

Podscribe is the leader in pixel-based attribution, incrementality, and verification for podcast, streaming, CTV, and other hard-to-measure media channels. We help advertisers, agencies, and publishers measure true campaign impact, optimize performance, and scale with confidence—backed by real-time, household-level data.

Media Contacts

Kristy Mei, Podscribe: kristy@podscribe.com

Shreya Paul, Podscribe: shreya@podscribe.com