Like many of you reading this, I was in radio in the 1990s and it was, without a doubt, a good time to be in radio. Everywhere I went in town I was ‘that radio guy.’ I got free tickets to everything, free food, a free gym membership and even a free car to drive. Basically, I was treated like a celebrity at least locally even though many people only recognized me once I started talking. When I added on a programming title the perks even extended further as the label reps came knocking. So, believe me, I get the nostalgia for the way radio used to be. What I struggle to understand is why so many radio programmers are nostalgic for how we had to program 30 years ago. Here are the three main ways that continues to happen in market after market and across formats.
Valuing Radio Airplay Over Streaming Numbers
The main arguments I get in with programmers and other consultants revolves around everyone’s reliance on following the Mediabase charts too closely while downplaying streaming numbers. If anything, most programmers will only add a song that’s having massive success streaming if it’s also simultaneously climbing the Mediabse airplay charts. Here’s why that approach is backwards. When we follow airplay charts we’re adding songs simply because other radio stations added it and just trusting that they know what they’re doing. When we look at the market-level streaming data we watch we’re adding songs because people within that specific market are already listening to that song on their own. There is no more effective way to determine whether people within a station’s coverage area want to hear a song than looking at that data because it’s collected in real time across every platform and has a sample base near 100%, because virtually everyone listens to music on at least one of their devices every single week. It’s more accurate than call out (which is dated by the time we get it), focus groups (which have a very small sample base) or even online music testing (which has a quicker turnaround and larger sample base than focus groups but is now an unnecessary extra step when we can just run a report showing everything everyone is already listening to on their own). This also extends to recurrent and gold categories where many programmers and consultants are adding songs either because they were played a lot on the radio previously or because they did well in an expensive music test that was done ages ago and no one can afford to redo.
Waiting For The Radio Release Date
Part of why radio lags behind digital competitors as a new music discovery tool is because we’re the only one abiding by the label’s rules. We’ll wait until the official single release date to add a song that the artist or label themselves added to every single digital platform there is weeks, months and occasionally even years prior. Then we have the audacity to run a sweeper going into the tune calling it ‘brand new.’ This makes us sound out of touch to any of that artist’s fans that know the song has been out for quite a while already. Yes, it is true that sometimes a song does pick up momentum with the audience once it’s pushed as a radio single. However, it often doesn’t, and when it does that’s reflected in the market-level streaming data we look at. A programming strategy that’s better aligned with how music is actually consumed today is to do what the artists and labels themselves do, only on the local level instead of nationally or globally unless we’re programming syndicated formats. When an album is released watch the streaming data to see which songs our local audience connects with and add those, regardless of whether they’re the new single or not. Sometimes that’s one song, but with some of the bigger artists within our formats it will generally be two to four songs. Which leads into the third way radio programmers are still programming like it’s 1996.
Outdated Artist Separation Rules
Making the two adjustments above will immediately cause scheduling problems within 99% of radio programmer’s music scheduling software because of the artist separation rules they have setup. That’s because those were all set at a time when music was recorded and released very differently than how it’s done today and therefore consumed very differently by listeners. Those antiquated rules were also reinforced by the small percentage of people who called into radio stations and said they’re tired of hearing the same songs by the same artists and the on-air talent who are always the first to get annoyed by a perceived ‘lack of variety’ on the station. What seven years of watching this song data has shown me is that the vast majority of people do not care about hearing a variety of artists, they care about one thing, hearing the songs they like and not hearing songs they dislike. Which is going to ebb and flow quite a bit based on which massive artist has just released a new album, which new emerging artist is blowing up on social or which older established artist is resurging because they got their forty year old song into a popular new Netflix series. The last thing we want to do as programmers is punish an artist for being too popular with our audience and doing so always pushes songs our audience isn’t connecting with onto them, which no one likes.
So, the big question is why do so many radio programmers refuse to evolve and change? There are a multitude of reasons, fear of failure, feeling like they’re too busy to learn something new or just plain stubbornness. But mainly it comes down to a very true cliché, old habits are hard to break. When we’ve been doing something the same way for decades it’s hard to break that routine. Especially because we often equate longevity in this industry with success. But, if we’ve been doing something for decades and we’re no better at it than we were one or two years in that doesn’t constitute success. To me it constitutes settling and coasting.
What do you think? Are you still programming like it’s 1996 or what other examples of that have you seen in other programmers? Comment below or email me at Andy@RadioStationConsultant.com.
Pic generated using Whisk.