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Podcasters need listening data, so Nielsen is going to call people’s homes to ask for it

Podcasters need listening data, so Nielsen is going to call people’s homes to ask for it

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Photo by Amelia Holowaty Krales / The Verge

Nielsen, a company best known for tracking TV shows’ popularity, is getting into the podcast data collection business. The company will begin assembling information on podcast listeners’ consumption habits, like their genre preferences and how long they listen to shows, and it will then sell access to that data to podcasters and podcast ad networks. The information could help these companies sell ads, especially because they often have little insight into their listeners’ broader consumer habits.

Nielsen’s initial clients are some of the industry’s biggest names, including, iHeartPodcast Network, Cadence13, Midroll, Westwood One, and Cabana. Given that these companies sell ads for podcasts, they’ll likely use the database to build a more enticing pitch for advertisers.

To build the database, Nielsen will poll random Americans about podcasts and then give its clients the opportunity to list their shows among those that people say they consume. The end goal is that podcasters will know more about their listeners and more about who enjoys podcasts more generally.

Nielsen will ask what genres they like and how long they listen

The service is part of Nielsen Scarborough, a product that’s been around for decades and involves Nielsen asking consumers detailed information about their media consumption and buying habits. Nielsen surveys more than 200,000 people every year through phone interviews, physical surveys, and online surveys about a range of things, like what kind of car they own, their demographics, their favorite beer brands, what concerts they go to, and how often they visit the mall, for example. (You can see a full list here; it’s extensive.)

Nielsen’s podcast survey will be conducted with 30,000 people twice a year. As clients pay to join, they can then have their shows included in the next survey batch.

Even if a company doesn’t list their show on the survey, the data could still be useful. A network that primarily focuses on true crime shows, for example, can look at what brands are purchased by people who said they liked shows within the genre. Armed with this information, they could go to advertisers and point out that their fans likely know their brand and are interested in what they’re selling. It’s not necessarily direct information, but it’s more precise than what podcasters have access to now.

Nielsen will poll 30,000 people every six months

Podcasting is a growing business, but a lack of listener data has made it more challenging to sell ads. Up until recently, podcasters had little information on who actually listens to their shows. Most hosting platforms only offer IP addresses, and thereby the locations of where their listeners are based as well as where they heard the show (on an iPhone through Apple Podcasts, for instance). Spotify has altered that reality a bit by offering demographical data through its internal analytics dashboard. But compared to what Facebook and Google know about people, the podcast industry is woefully lacking data.

Spotify, overall, is in a more powerful spot than other podcast networks when it comes to selling ads, solely because it can attribute episode listens back to specific users. Those users identify their gender, age, location, language preference, and listen to all their music on the platform, so Spotify knows a bit more about them than other networks whose listeners are spread across various platforms. Spotify’s already making use of this advantage by letting advertisers target ads based on the podcast genre that listeners consume. Notably, these automated ads are placed in between songs, not within podcast episodes.

As the industry grows and more podcasts vie for advertiser dollars, podcast networks are going to have to make the case that an advertiser is best served by their specific show. Nielsen’s data could help build a compelling argument.