Programmatic advertising for podcasts is becoming commonplace as a way to monetise content. If you’re new to programmatic advertising, it’s the automation of buying and selling of ads, and can be used to automatically place ads in specific episodes of a podcast, based on a variety of factors such as the audience demographics, the content of the episode, and the availability of ad inventory.
But producers and publishers often leave advertising revenue on the table, because creating markers for mid-roll ads (ads that play during the podcast) and adding brand suitability and contextual tags on pre- and post-roll ad markers is a manual, time-consuming process. So, it often doesn’t happen!
At Sonnant, we’ve been developing machine learning models to automate the creation of Smart AdMarkers. User defined parameters for ad marker frequency and number of ad slots per marker lets you control the right balance between listener experience and the level of advertising you want. Sonnant figures out the most appropriate point(s) in the podcast (or catchup radio or other audio streams) to insert the markers based on speaker changes, pauses and other data it extracts from your content. Then it tags those markers with contextual targeting information such as IAB category for brand suitability and safety.
So, in minutes, your podcast has additional inventory (with mid roll ads) and can attract premium ad rates (with contextual targeting information for advertisers). You can apply these markers on new episodes as well as archives that are still attracting listeners. Our initial results have been really exciting.
Even with modest numbers of listeners, content with Sonnant’s Smart AdMarkers generate substantially more advertising revenue and provide 15-20x return on investment for publishers.
That’s a massive return at any scale of content. We’ve designed a calculator so that you can model your potential returns and build your own business case for Sonnant’s Smart AdMarkers. If you’d like a copy, or want more information about Sonnant, drop us a line at email@example.com!