PD’s have an amazing range of tools today to help choose which songs to play. All provide interesting information that can be deployed in valuable ways. While there’s a clear benefit in having insight into which songs are going to be hits in the near future, there’s also a clear need to understanding which songs are hits with your station’s listeners right now.
Services like RateTheMusic essentially quantify a station’s request line and give PD’s a glimpse into the unfiltered demands of listeners. The scores look and feel like the ones we’re accustomed to seeing from callout. The sample is comprised of anyone opts into the panel, including record promoters and competing PD’s, hopefully, the sheer numbers of legitimate panelists outweighs the imposters. When compared to actual callout or properly-conducted online music research, the scores line up about half the time (though it’s impossible to predict which half). It IS, however, a great promotional tool to give a station another way to talk about how it involves listeners in selecting the music.
MScore is a more recent service that scrapes PPM data to line up songs your station played with what your meters did when the songs were playing. Optimally, you get an understanding of which songs cause listeners to switch away in search of a better song. Sometimes you learn which song happened to be on when she switched to another station to find a traffic report or arrived at her destination or decided she needed to think about something important or her cellphone rang or her mood changed because of the weather. On the plus side, it’s based on the same sample that yields the ratings. On the minus side, it’s based on the same sample that yields the ratings.
BigChampagne and others have brought sales figures into the digital age – a long way from calling the local record store to ask what’s selling. Some of these also scrape Social Media, airplay and concert sales to generate charts of what’s popular. To the extent that information about the music for which people will pay predicts what songs they will listen to when cost isn’t a barrier, this can be useful information.
Shazam and its competitors have gotten lots of attention for their ability to aggregate what songs are being tagged. It’s a great tool for showing which songs are getting the attention of those who are fans of artists and early adopters of various music genres.
Both digital-music-sales tools and song-tagging tools provide a glimpse at songs that are getting attention. What they don’t show is whether or not those are the consumers your station needs to engage. Fans of a specific artist or genre can cause tags and downloads to explode for a new song long before the song has crept into the mainstream and gotten the attention of consumers who are less music-active.
One-to-one digital music sources can be infinitely customized to play exactly the songs or types of songs for a specific consumer. Meanwhile, music radio is a one-to-many medium, requiring that lots of people find the choices adequate. Radio rewards consensus. Gauging consensus requires getting reactions from those who wouldn’t buy a particular song or be intrigued enough to tag it. And gauging consensus requires getting reactions on lots of songs from those who might be excited enough to tag or buy any song.
Gauging consensus requires a screened, passively-collected, statistically-valid, representative sample of a station’s audience. It used to require callout, but now online sample and data collection have turned that into what we at NuVoodoo call Online Music Research: full-sized, screened, passively-collected samples giving reactions to all the titles in consideration for a station’s current playlist.
While we struggle, sweat, over-think and care more than anything about what’s going out on our airwaves (and there are ratings rewards for those who truly care), the fact of the matter is, those who keep us employed – the listeners – don’t really care. It’s a passive medium. And legitimate, passive research among those folks, is still the best tool in the box.