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Podchaser Brings Radio’s Relied-On Airchecks Feature To Podcast Advertisers With An AI Twist.


Airchecks have been used by radio sales reps for decades to demonstrate to advertisers that their spots ran as planned. Now that concept is coming to the podcast world. Podchaser is launching a new tool that, while not like the cassette tapes that salespeople once dropped on client desks, will rely on a sophisticated machine learning algorithm to achieve a similar goal.

Called Airchecks, Podchaser’s new tool will produce transcriptions of host-read ads to confirm that their ad ran on the intended podcast. It will also provide other insights to help a marketer quickly understand the brand positioning and representation within the ad by the podcaster that they can then use to help fine-tune their current and future campaigns. That could include adjusting the talking points that the brand shares with hosts.


Podchaser CEO Bradley Davis says that podcast advertising is reaching such scale that many brands are now buying across hundreds or even thousands of podcasts at a time, and that has made the methods of tracking live-reads too cumbersome.


“With Airchecks, our Podchaser Pro users are able to quickly discover, listen to, and learn from podcasts ads through voice transcription technology,” Davis says. “Having access to this data is not only a powerful validation tool for in-progress campaigns, but also yields crucial insights for planning future campaigns.”


Airchecks is currently in beta across the top 5,000 podcasts and is the latest feature to be added to the Podchaser Pro suite of podcast data, insights, and planning tools for advertisers and media planners. Podchaser Pro also includes audience reach, listener demographics, brand safety, and other insights into who is hearing the ad. This news comes on the heels of Podchaser’s launch last month of an industry-first predictive language modeling capability that allows advertisers to refine their podcast audience targeting. By using AI, Podchaser says it is able to analyze the language spoken within a podcast to predict the age and gender of its likely audience.


“Having access to this data is not only a powerful validation tool for in-progress campaigns, but also yields crucial insights for planning future campaigns,” Davis says.

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