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Acast launches Smart Recommendations to maximise campaign success
Independent podcast company Acast has launched an AI search engine, Smart Recommendations, to help advertisers find their perfect podcast audiences in seconds.
All they have to do is describe who they want to reach.
Its aim is to change how podcast advertising is bought and sold, making campaign planning faster, smarter and more effective.
Powered by a decade of Acast’s own data and experience, and using OpenAI’s LLM technology combined with retrieval-augmented generation, Smart Recommendations acts like an AI media planner.
It can turn a simple prompt like “I want to reach women in New Zealand interested in investing” into a curated list of high-fit podcasts. Using natural language and advanced search, it quickly surfaces the right shows for precise audience targeting.
A second brain for advertisers
Smart Recommendations is also the first release from Acast Intelligence, a new core capability dedicated to using AI to enhance Acast’s product suite for both creators and advertisers.
Acast Intelligence unlocks the potential of Acast’s expansive dataset to drive smarter discovery, planning and performance in podcast advertising.
“The podcast landscape is vast, and finding the perfect audience can be time-consuming and challenging,” says Matt MacDonald, Acast’s chief product officer.
“Smart Recommendations solves this by harnessing the power of Acast’s decade of proprietary data combined with Podcaster’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. It’s about moving beyond guesswork to truly understand and reach the right audiences,” MacDonald adds.
Smart Recommendations is available to advertisers launching campaigns via Acast’s ad platform, and used by Acast’s internal sales teams around the world.
Key features
- Natural language prompts: Advertisers can simply describe their target audience in plain language.
- 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.
- 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.
Maximise podcast ad ROI with AI
Early testing of Smart Recommendations has yielded very promising results.
Over 200 campaign briefs have utilised the tool in testing, leading to a significant reduction in planning time – by up to as much as 92%.
Notably, 80% of ad buyers in testing also discovered additional, previously unconsidered podcasts for their campaigns.
Early indicators from shows with under 50,000 weekly listens show a significant uplift. According to Podscribe data, this includes a 14% increase in median purchase rate and a 35% increase in median visit rate.
“This is more than just a search engine. It’s a powerful tool that transforms data into campaign success, ultimately helping advertisers maximise their podcast ad ROI with AI,” says MacDonald.
“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.”
Henrik Isaksson, Acast ANZ’s regional managing director, says: “The launch of Smart Recommendations is a perfect example of our relentless pursuit of valuable podcast audiences in Australia and the use cases are nearly endless.
“Simplifying the buying process for advertisers has long been our mission and we’re uniquely positioned to offer this at scale across our entire content slate.”
