Followers of this blog over the past two years have read about the discovery, analysis and powerful resource that is on-demand streaming data.
When we began to understand the relationship between on-demand streaming data and radio consumption, it didn't take too long to appreciate the fact that programming radio based on actual consumption of the music had incredible potential.
While current-based radio formats benefit greatly from this information, true consumption of library material comes into focus at a time when there is more music to select from than ever before.
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And because we've learned of the true value of long-term "hits", choosing the correct library material is as important as ever.
Prior to the wonderful technology that allows us to finely view weekly, if not daily on-demand streaming consumption, radio programmers relied on use of telephone interviews (call-out research), testing auditoriums full of listeners or sales tracking to try to determine the best songs to play based on popularity.
This was a good approach considering it was all we had, but studying sales doesn't provide insight to actual listening once the CD or digital file was purchased.
“We are seeing marked (ratings) results for CHR, Alternative, Country, AC, Hot AC and Urban formats.”
Observing a room full of listeners marking their responses on paper to seven second hooks of songs the stations would choose, did provide some insight into how listeners related to songs they were familiar with but did not reflect actual consumption of those songs.
Today with the advanced capabilities of the technology, Bridge Ratings has been helping its on-demand streaming clients hone their on-air music presentation so that it better mirrors true listener interest and listening.
And now - after more than a year of field use - empirical results in the form of audience ratings is proving in over 90% of the use cases that all things being equal, shifting to a on-demand music streaming programming approach yields increased audience primarily through a) increased listening occasions and b) longer time spent listening.
As one of our clients uttered after receiving ratings results for the three stations using this approach this past January, "this s**t works!"
As you might have guessed, on-demand streaming research is wildly beneficial to current-based formats.
We are seeing marked results for CHR, Alternative, Country, AC, Hot AC and Urban formats.
The trick is how to use this data when realigning music lists.
Some of our clients use the data as a "guide" and shape their lists weekly or daily at music meetings. The result is progressive audience growth.
Then there are our clients who have used the data long enough to trust it implicitly and program their music as a true reflection of the streaming chart - song for song. For these clients the results have been much more dramatic.
Remarkably, the music industry has been slower to utilize this technology to further define their marketing and promotions strategies.
Each week, I see songs that have very high or extremely high consumption metrics on our on-demand streaming charts that stations are not playing.
When asked why this is, one of my programming clients responded with "I'm not playing it because the record label hasn't serviced us with it yet!"
Remarkable.
We've tested compatibility, correlations to sales, MScores and requests and long-term music preference among all demographics.
Through the numerous posts on this site and others over the past two years, we have urged the radio and record industries to move more fully into use of on-demand streaming data. Because it reflects true music consumption by its customers, why not use it?
There is no doubt now that the local DMA streaming data we provide stations is yielding more listener loyalty and more frequent tune-in contributing to improved audience numbers.
As a programmer or label rep, if on-demand streaming data as a research tool is not for you, please use the response form below to help us understand why.
More conversation will likely yield better understanding.