Stockholm-based podcast giant Acast has introduced an ad-buying system called Smart Recommendations. It’s an AI-powered search engine for advertisers, and it delivers recommendations of podcasts consumed by audience segments targeted by the advertiser.
The system is capable of granular requests for highly defined audiences; the PR offers this example:
Smart Recommendations acts like an AI media planner — turning a simple prompt like “I want to reach women in Canada interested in investing” into a curated list of high-fit podcasts.
Acast promises “unmatched precision in audience targeting.”
Four key features are detailed:
- Natural language prompts: Advertisers can simply describe their target audience in plain language.
- Advanced semantic search: The system understands the intent behind a query, including context and related concepts. It can extrapolate from a prompt and apply a deeper level of nuance.
- Rich show insights: Recommendations are based on deep analysis of podcast content, audience demographics, engagement, tone, and style.
- Transparent recommendations: Every suggestion is accompanied by detailed explanations of why it was chosen, helping advertisers make informed decisions.
Testing has proceeded with seleced customers, yielding “very promising results” across about 200 campaign briefs. Eighty percent of ad buyers discovered previously unconsidered podcasts for their campaigns. Acas reports double-digit improvemens in median purchase rate and median visit rate. (hose numbers come from Podscribe.)
“This is more than just a search engine; it’s a powerful tool that transforms data into campaign success, ultimately helping advertisers maximize their podcast ad ROI with AI,” MacDonald added. “Smart Recommendations is the next step in our vision to become the intelligence layer powering podcast advertising globally, offering AI-powered podcast recommendations that truly deliver.” — Matt MacDonald, Chief Product Officer for Acast.
