Acast has unveiled a new AI tool aimed at transforming how podcast campaigns are planned.
It helps advertisers to identify relevant shows in seconds simply by describing their target audience.
The new feature, Smart Recommendations, is powered by a combination of Acast’s own decade-long dataset, Podchaser insights and OpenAI’s large language model technology.
Users can input natural language prompts like “I want to reach women in Canada interested in investing” and receive a curated list of podcasts that best match the brief.
The tool is the first release from Acast Intelligence, a new capability focused on applying artificial intelligence across the company’s services to benefit creators and advertisers alike.
According to Acast, the system not only saves time but also increases precision in audience targeting through its use of retrieval-augmented generation (RAG), semantic search, and audience analysis.
Matt MacDonald, Acast’s Chief Product Officer, said: “Smart Recommendations solves this by harnessing the power of Acast’s decade of proprietary data combined with Podchaser’s insights, and providing a ‘second brain’ for advertisers.
“This empowers them to discover hidden gems and connect with ideal audiences with unprecedented speed and precision.”
Advertisers can access Smart Recommendations through Acast’s ad platform, and the tool is also now in use by Acast’s sales teams worldwide.
Key features include natural language search, transparent explanations for why shows are recommended, and data-rich insights on audience engagement and podcast tone.
Initial tests showed a 92% reduction in campaign planning time and a 14% increase in purchase rates for podcasts with under 50,000 weekly listens. Additionally, 80% of users found podcasts they hadn’t previously considered.
Smart Recommendations is now live and Acast says it represents the first step in its broader ambition to integrate AI throughout the podcast advertising ecosystem.
