The Benefits of Using Streaming Data to Pick Music

As on-demand music streaming has become THE manner in which most folks consume music these days, Bridge Ratings has found a growing group of radio station clients that rely on the weekly data we provide.

The reason our on-demand streaming clients align their music rotations closely with our on-demand music streaming data is because it works.

80% of our clients with at least six months using our data have seen the following improvements in audience:

a. Increased daily listening occasions
b. More minutes spent listening with each occasion
c. Increasing daily and weekly cume audience.
d. Resulting in increases in ratings reflected by Nielsen.

Don't pay attention to the myths about streaming research. Actual field experience shows these facts to be true: 

1. On-demand music streaming reflects actual music consumption because users are self-selecting the songs they listen to and listening to those songs frequently and for weeks at a time.

2. Streaming on-demand music is more akin to listening to the radio than any other type of music research because streaming listening behavior mirrors radio listening. Call out research and auditorium testing rely on short hooks of songs played to a small sample of possible station listeners. This is not the way people listen to music.

Believe us: people don't listen to their favorite songs this way and based on our research, fatigue and boredom impact these types of research scores.

3. Streaming data reflects the total spectrum of consumption: positive, negative and neutral. By focusing in on station format, demographics, local market data and listener streaming data, the Bridge Ratings streaming reports are much more granular, i.e. station-specific than broad-based, national rankers of streaming music.

Songs that are not popular over time do not maintain rank status. These songs either don't rank in the top 100 each week or they simply die on the vine as mid-charters. Saying that on-demand streaming research doesn't reflect songs people don't like is inaccurate.

4. Airplay charts only occasionally reflect actual music consumption.

More often than not published airplay charts are built on consensus, i.e. hundreds of station playlists are merged together to present an overall ranking of how much airplay songs are receiving on those stations. Programmers often depend on these airplay charts to align their music categories. This approach simply does not reflect market and station specific listener behavior. Adding to this, record labels are always interested in seeing their new releases climb these consensus charts so record promo folks can encourage other stations to play the record, whether that record is appropriate or not.

Use of market-specific, format-specific and listeners specific on-demand streaming data is a far more effective way to reflect true listening consumption.

5. Streaming data is a true reflection of actual consumption. The data is sensitive to the popularity of a song and any associated fatigue. When people slow down or stop their streaming of a song, its rank falls and either settles at a spot on the chart where it lives for some months (Walk the Moon's "Shut Up & Dance"), or it fades into ranking below 100.

6. With billions of streams nationally, and thousands at the market and station level, on-demand streaming produces a significantly better "sample" than any other music research. These large samples, even in small markets, reduce the margin of error so significantly that the data is consistent week to week providing a higher degree of data trust than any music research available.

7. In our experience of working with on-demand streaming data for more than two years with our client stations using the data weekly, streaming data more often than not is ahead of the curve.

Not only does streaming data pick up popularity immediately, it often is far ahead of record labels in determining successful hits and follow-up hits.

One example of this phenomenon is the Chris Stapleton song "Tennessee Whiskey" which immediately flashed to the top of the Country radio streaming charts right after Chris received his armful of Country Music Awards in 2015.

While the televised awards show was still on, we saw "Tennessee Whiskey" climb to top 10 status. The song has remained in the top 30 since, yet gets little radio airplay.

Why?

From our feedback from our station programmers and music directors, many had not been serviced with the song by Stapleton's label so they couldn't play it. Because so many stations stayed off the song, it never saw any significant chart action on the published airplay charts, yet the song remains hot with Country listeners.

For programmers that rely on these published charts they are missing one of the most popular Country music songs of the year.

Undiscovered songs listeners are consuming at high levels but which radio has ignored is another benefit of on-demand streaming research.

There are numerous examples of this phenomenon.  Also in the Country format, this week and last saw the new Florida Georgia Line song "Smooth" break out in the Country top 10 in Nationally and in many of our markets. It doesn't appear on any airplay chart yet.

While there may be "limitations" in most types of research, on-demand streaming eliminates most research negatives and if you are thinking about using streaming data or are using it. consider these real-world examples of on-demand streaming use cases as confirmation the data works to properly align radio playlists with that of its listeners.

As one of our staunch supporting station owners proclaimed when the ratings book was released after using our data for six months or more, "This sh*t works!".

Stop Programming By Consensus

If you've been following Bridge Ratings' research pieces about on-demand music streaming and its value to radio programmers, the following is the latest in the insight we've gained from discussing this important technology with programmers in markets large and small.

Back in the day when there were no radio station monitoring services like BDSradio (from Nielsen) or Mediabase, radio programmers had to rely on their own gut, local research and listener input to determine the best songs to play.

Sometimes, programmer ingenuity provided insight.

If a programmer wanted to hear a respected station in another city, they'd ask the GM for some travel money, get on a plane and spend a few days in that other market manually monitoring the station, logging all songs, promos and clocks.

Returning to their home market, the Program Director would lovingly analyze their notes and determine the application - if any - to their local situation.

With the coming of technology these types of market trips are generally no longer necessary, what with monitoring services and on-line streaming.

Isn't technology great?

In this case, I think not.

Published station and radio format charts are now available to programmers, many of whom depend on these charts to determine song selection and rotations. The published charts do have their value to some program directors.

These format charts are an aggregation of dozens - even hundreds - of stations in different markets. Now that music research has been eliminated from many radio station budgets, the phenomenon of "Consensus Programming" has disrupted radio's ability to properly expose music to its listeners.

Programming by consensus means that programmers all across our great land look to the published charts for their formats and adjust their music categories based on the aggregate.

The resulting playlists may be 100% appropriate for some market situations.

Or more likely - those lists are a general view of radio airplay across fifty states.

The result is hundreds - maybe thousands - of radio stations are playing song lists that are very similar.

And this is where the wheels come off.

For over two years, Bridge Ratings has been providing on-demand streaming music research to our clients and we have learned at least a couple of important concepts:

1. Programming by consensus results in stations adding songs too late and getting off songs too early in more cases than not.

2. The lifecycle of hit songs - whether current or old - is much longer than we've ever thought.

Here are two examples:

A) The current multi-format smash "I Took A Pill In Ibiza" by Mike Posner has just recently appeared in published charts in the top ten most-played songs on Top 40 radio. It's still trending up. Our streaming research showed that true consumption of that song was in the Top 5 eight weeks ago!

What does this mean? It means that the published charts showed "Ibiza" gradually climbing the charts from outside the top 50 to it's current Top 10 status. Radio's listeners were streaming this song multiple times a week long before radio caught on!

B) Country music star Chris Stapleton's song "Fire Away"  blasted into the top 20 most on-demand streamed songs right after Chris' ACM award windfall on April 3. Yet the song was not even ranked in the top 50 most-played songs by the aggregate of America's Country music stations.  Based on personal guidelines, a Country music programmer seeing this may consider that it's too early to play that song and will wait to see if it rises high enough to warrant adding to their playlist.

Meanwhile, Country music fans were streaming the heck out of that song.

If not enough Country stations add "Fire Away", it could very well stall outside the top 40 and never get a rightful place on American broadcast radio.

In our analysis, Bridge Ratings found that in 55% of the cases studied, the aggregate music charts are not representative of true music consumption has observed in week after week of on-demand streaming data.

As digital data becomes more available through streaming data providers and platforms like Shazam, programmers are, indeed, better equipped to see how music fans are consuming.

Click Here to enlarge.

Yet, the most accurate method we have found to determine song popularity, longevity and viability, is on-demand streaming data.

The chart to the right compares a recent Pop song's on-demand streaming lifecyle with that of consensus/published charts over the course of 15 weeks.

Upon release, on-demand streaming for this song vaulted into the top five almost immediately. It's popularity grew as more fans became aware through word-of-mouth, broadcast radio and other streaming services.

It sustained this lofty position for the full fifteen weeks.

By comparison, upon its release, radio added the song and it was first ranked #78 on published radio airplay charts. As the chart shows, it took six to seven weeks before the aggregate of radio had pushed the song into the top 10 where it slowly faded after programmers must've considered the song overplayed or burned out.

As this song's progress on the published chart slowed, programmers got off the record or slowed its rotation.  Meanwhile, demand for the song remained extremely hot through on-demand streaming platforms from YouTube to Spotify to Amazon Prime.

We have found that on-demand streaming where consumers choose what they want to listen to, is more closely aligned with the behavior of radio listening than any other type of music research.

So, if you're a radio programmer reading this...do your listeners a favor and stop programming by consensus.