Podcasting: Moving from Downloads to Listens

Over the past decade the media and advertising industries have come together to create a clear definition of a download for ondemand audio content amp160With this metric championed by the IAB and industry leaders everyone can speak the same language and transact business in a meaningful way which has added to the 85 percent growth in podcast advertising revenue between 2016 and 2017 according to the 2017 IAB Podcast Advertising Revenue Study with even more significant growth anticipated in 2018The analogy I use is the magazine industry amp160a wellestablished model that few question amp160We all know what circulation means and we all know who the audience for any publication is based on surveys and qualitative data amp160That39s similar to podcasts today Downloadsamp160are the equivalent of the magazine making it to the mailbox amp160We can guarantee the file made it to a user who requested itSince it39s hard to accidentally download a podcast there39s great confidence backed by qualitative data that people have chosen to subscribe and are listening amp160Qualitative data can also tell you who is listening amp160Publishers have great survey data on the audiences listening to their podcasts amp160At NPR we39ve found podcast fans are happy to take surveys and help us out amp160Beyond publisherspecific data firms like Edison Research regularly quantify the audience at scale and brands often conduct their own brand lift studies to measure impact of their campaignsSo that39s the good news amp160But we39re still talking about delivery of a file and not actual listening amp160Given the digital age we live in we as an industry can do betterThe technology for delivering and playing podcasts is different from the standard Internet models for video or text content amp160There are no cookies in podcasting it39s just the transfer of a file amp160This made a lot of sense when podcasts were developed more than a decade ago as data was expensive and podcast files were big amp160Downloading them over WiFi and listening later without using expensive cellular data was the normBut that39s all changed amp160Most basic data plans today provide ample overhead for even the heaviest of podcast listeners and WiFi is more readily available than everListening behaviors are shifting quickly too amp160Edison Research in their Podcast Consumer 2017 research found that 77 percent of people now simply click on a podcast and immediately listen amp160With 42 million people listening to podcasts each week that39s a lot of activityThe time has come to move the metric from downloads to listens amp160We don39t have to settle for knowing the magazine made it to the mailbox amp160We can know how many pages someone read and even which pages they skipped along the wayThere are no fundamental barriers to real listening analytics on podcast content amp160It just requires a new model and participation from the industry amp160But there are things that have to happen to get thereFirst there needs to be an agreedupon model for what listening metrics to track amp160For the advertising community the most relevant metric would be ads that were played in full or at least enough of an ad to count as meaningfulSecond there needs to be a way for publishers to mark which ads are in a podcast and where they areThird playback platforms need to alert publishers when a human has heard an ad amp160Note Not which human Just a humanamp160amp160We don39t need to jeopardize privacy to get a model where real listening is measuredTechnically none of this is challenging amp160Why Because earlier this year NPR developed a new method to do all of the aboveamp160and tested it in the NPR One app amp160We embedded some additional metadata into podcast episodes that marked important points in the file amp160We also embedded a URL for sending anonymous listening event data back to NPR39s servers amp160Then in NPR One a simple model was built to read that data and send it back amp8211 a simple anonymous ping when listening happened at those key pointsIt39s called Remote Audio Data or RAD for shortIt worked just fine amp160Now NPR can tell how much of the content people listened to which sponsor messages and even if people skipped the sponsor messages amp160And this technology is easy to scale amp160The problem is that NPR One accounts for just one portion of NPR39s podcast listening amp160Listeners also hear NPR podcasts through Apple Podcasts and dozens of separate and independent platformsTo move the entire industry to a listeningbased metric we would need a model like RAD adopted far and wide amp160We39re working on that amp160NPR is preparing to move into phase two of testing RAD and will conduct a wider test along with several of the largest podcast publishers multiple ad vendorsamp160and at least one other large podcast app amp160It works on both IOS and AndroidIn the meantime other changes are afootLater this year Apple will roll out Apple Podcast Analytics a major step in sharing actual listening data with publishers amp160This is fantastic but again it only addresses the 65 percent of our audience on Apple platforms amp160At least from what Apple has shown thus far at the Worldwide Developers Conference WWDCamp160it doesn39t do it in a way that can easily become a transactable metric at scaleWe39re talking to Apple about RAD and hope they will support it amp160We39re also talking with most larger publishersamp160and most large listening platforms There seems to be a lot of interest and supportMy hope is that RAD or something like it can become an open industry standard in 2018 amp160If we can achieve that podcasting will become an even more valuable platform amp160We already know podcast ads are extremely effective at delivering on both branding and direct response goals amp160Tying that ROI with metrics that give marketers a clear understanding of how budget and listening combine to deliver value will make podcasting one of the most transparent and effective platforms in the modern media mixPhoto credit National Public MediaClick the social buttons above or below to share this story with your friends and colleaguesThe opinions and points of view expressed in this content are exclusively the views of the author andor subjects and do not necessarily represent the views of MediaVillagecomMyersBizNet Inc management or associated writers

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Podcasting: Moving from Downloads to Listens

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Bryan Moffett

Jim Lecinski | Clinical Marketing Professor | The Insomnia Cookies Case - The GOST Model Taught at Northwestern - By Mike Linton

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Bryan Moffett

Jim Lecinski | Clinical Marketing Professor | The Insomnia Cookies Case - The GOST Model Taught at Northwestern - By Mike Linton

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