Coleman Insights recently introduced the FACT360 Strategic Music Test. FACT360 is online music testing done right through the latest sampling techniques and data collection capabilities, and includes the same benefits that Coleman Insights has provided through its FACT Strategic Music Tests for more than 20 years. These benefits help radio stations build the most appealing and strategically on-target libraries possible.
In the spirit of our launch of FACT360, we present the final installment in a series of five blogs authored by Coleman Insights executives covering important considerations about music testing and music strategy. This blog is written by vice president John Boyne and covers how using Fit data can help you get maximum value out of a library test.
“Is this song too poppy for my Hip Hop station? It tests really well…”
“Is this song too wimpy for my Rock station? It tests really well…”
“Is this song too old for my CHR station? It tests really well…”
As a researcher, I get this kind of question all the time. At issue is what to do with songs that are popular yet seem to push beyond the boundaries of what “fits” the radio station. Fit matters, of course, because listeners tune in to your station for a reason. Need traffic info? Go to the station that you know delivers it. Need a good laugh? Go to the station that you know delivers it. In the mood for Country? Go to the station that you know delivers it. Wanna Rock out? Go to the station that you know delivers it. Up for hearing the latest hits? Go to the station that you know delivers it.
In this sense, ratings are generated through a combination of catering to listeners’ tastes and expectations. Great programming only gets a station so far if the people who would like what it is doing are not thinking of that station for what it is doing. This is why stations sometimes get in trouble when product evolution outpaces perceptual evolution. We probably all know examples of stations with well-intentioned, evolutionary changes that ended up alienating the people who had been listening without changing market perceptions enough to bring in new listeners.
This is why it is so important to understand listeners’ perceptions and consider them in light of market tastes, competitive opportunities and station resources. Sometimes the best path is to stay pretty close to listener expectations. Sometimes the best path is to aggressively try to change or evolve listener expectations. The key is to have the best information at hand so that you can develop the appropriate strategy. While strategic studies—such as the Plan DeveloperSM and FLIPSM studies used by many Coleman Insights clients—are ideal when mapping out where a station should go, music testing helps keep a station from veering off course along the way.
This is where Fit comes into play as a music testing measurement. In Coleman Insights’ FACT360 studies, listeners indicate which stations—if any—they expect would play each song. Fit is not a measure of whether your listeners think you should play a song; it is simply a measure of what your listeners expect. It is a highly valuable measure that is separate from our measure of how much listeners like or dislike a song. Just as smart programmers rely on more than just their gut instincts when assessing a song’s familiarity and popularity, it is wise to also get a read on how strongly listeners associate a song with your station and your closest competitors. Better data for better decisions.
Coleman Insights clients use FACT360 Fit data in a variety of ways. From a macro perspective, we are able to aggregate the Fit scores of different music genres and eras to help clients get a sense of how their station is being perceived and whether those perceptions are aligning with that station’s strategy. If, for example, a station is trying to develop a more contemporary identity, Fit data in library testing can help track the station’s progress and influence its on- and off-air marketing decisions.
From a micro perspective, we are able to show clients the Fit for every song tested. This gets back to the questions posed at the beginning of this article. What do you do with a popular song that has low Fit? Well, like many questions, the answer varies depending on the situation. If it is a low Fit song that aligns with your strategy and your vision, then it probably makes sense to play it—perhaps aggressively—and possibly even feature it in on-air imaging to help bring it into the perceptual wheelhouse of your station. But if it is a low Fit song that is also not particularly relevant to your strategy and your vision, then it is worth considering whether this song should be limited in exposure (perhaps to specialty programming or an “oh wow” category) or left off the station entirely.
Of course, these decisions are also influenced by a station’s format and brand strength. For example, a variety-imaged Adult Hits station is going to have more latitude to get away with and even benefit from surprising departures from core expectations than stations in many other formats. And a well-known station with a healthy base music image position is not going to need to be as closely aligned with core expectations as a weaker station that needs a lot of strategic focus to build its brand.
Music radio stations that enjoy sustained ratings success play the songs their target audiences love and expect to hear when they tune in—understanding that this sometimes requires evolving those expectations along the way. Using Fit data in a library test helps ensure that your station can do that as often as possible.
