July 14, 2009 The Song Adoption Formula
This post has been completely updated. Click here to read the update.
If you want to be semi-scientific about music promotion, here’s a song adoption formula to consider: Listeners * Optimal Frequency Rate * Social Situation Rate * Conversion Rate = Song Fans.
Here’s the short form: (L * OFR * SSR * CR = SONG FANs)
Here’s how the formula breaks down:
Listeners (L)
Listeners (L) is the variable that equals the number of listeners (not fans but receptive listeners) that have frictionless access to your song via a download (paid is ok, free is better), a digital music stream, a broadcast, or by way of receiving your CD.
Side note: In 2009, I would not refer to handing someone a CD as granting them frictionless access to your music; there are a lot of people that can’t be bothered with unwrapping and playing a CD from an unknown artist.
Optimal Frequency Rate (OFR)
It’s often stated that falling in love with a song is a complex process. For the purpose of this post, I am going to speculate (comment below if you have better information) that a song needs to be heard by the average person at least 10 times within 60 days to make a lasting (classic-like) imprint upon one’s memory. Therefore, 10 spins within 60 days equals the Optimal (maximum) Frequency Rate of 100%.
Less spins over a longer time period equates to a lower Optimal Frequency Rate.
Social Situation Rate (SSR)
Once again, the imprinting/socialization process is complex. Most (young) people need social cues (signals from others) to believe in (adopt and evangelize) a song. When people spin songs in a vacuum (think about the lone iPod user with headphones on), they are less likely to adopt a song than when the song is played within a social setting.
Social settings (where social cues are gathered) range from listening to songs with friends, to hearing songs at a club or party, to sharing/playlisting/promoting songs for ‘friends’ online. In a perfect world, 100% of a song’s ‘early’ spins would occur within a social situation; this would equate to a Social Situation Rate of 100%.
All social situations are not created equal. If you want to be more specific, assign varying weights to different social situation types.
Side note: a lot of individualized music engagement that occurs on the Internet doesn’t translate into adoption and popularity. Why? A low SSR is one cause to consider.
Conversion Rate (CR)
Conversion Rate is the subjective component of the formula. Listeners are going to love your song(s) along a spectrum. A percentage of listeners (this would be the conversion rate) are going to adopt your song, while others won’t give it a second listen.
Although optimal frequency rate (OFR) and social situation rate (SSR) drive conversions (CR), investing in iterative song improvement is something you have complete control over. If you want to increase conversions (from listeners to fans) invest in writing sessions, collaborative efforts (try Indaba Music), song critiques, song surveys and expert coaching.
Consider the power of radio…
Radio is great at making fans. Radio has receptive listeners; radio spins songs to death; and for many people (worldwide), radio is the ultimate social cue and social sharing mechanism. (It’s got to be good if it’s on the radio right?) My last post on Music Think Tank - “Don’t go over the self promotion cliff, crush your local radio station instead” - should give you some ideas on how you can create a ‘channel’ to drive the formula (L * OFR * SSR * CR = SONG FANs) covered in this post.
Nobody (sane) records to tape any more…
There are lots of things artists do (like prematurely finalizing songs without seeking the best possible collaborators or expert feedback) and there are lots of things the industry does (like collecting royalties) that are artifacts from days gone by when music was expensive to create and distribute. Anything that prevents any variable in the formula (L * OFR * SSR * CR = SONG FANs) from being the largest number or highest (%) rates possible is something that’s holding you back.
In my next post, I plan to cover the friction that slows, and the forces that accelerate, the song adoption formula.
Reader Comments (13)
an interesting attempt to characterize a useful forumla, but shot full of questionable assumptions.
the most blatant being that the 'lone ipod listener' is less likely to adopt a song than someone hearing it only as background noise at a party! What?
@irrelevant
i guess we are not reading the same things.. one song in an ipod amongst 10,000 others is not that special. hearing a song with friends at a party is much more meaningful.. sorry, I just didn't have the time time to dig out the references.
^^True, but what's great about this model is that all the assumptions will be tested with data. I'm very interested in Bruce's projects for that exact reason....same reason I'm watching TopSpin closely and analyzing their models.
"Yeah I make assumptions/ it's the only way the brain can function/ hard to be creative in a great big naked nothing."
actually, i didn't hunt for references because i thought it was common sense...
scenario a - pimply sixteen year old kid listening to song X through headphones while looking out the bus window...
scenario b - pimply sixteen year old kid listening to song X through the backseat speakers while spending quality time with his prom date, while his best friend is in the front seat with his prom date (and a barking dog and twelve empty zima bottles)...
and song X will be remembered when? i thought that was blatantly obvious?
@justin,
Would love to hear about Topspin's 'models' when you are done analyzing. Please post when you have drawn some conclusions.
@bruce, how do you intend to measure these assumptions?
Have you seen Salganik's analysis of music popularity model?
http://www.livescience.com/health/060209_hit_songs.html
It seems to suggest that popularity is mostly a function of early adoption or momentum and that this can be artificially created.
I'm not taking a position on this, just pointing out the scientific study. I'm curious as to the reaction of the readers of this blog. Take a close look at the findings. The study was pretty well done and leaves me wondering if 'making good songs' is the key to success or if its something else. Again I'm not saying that it is not, just that a scientific study seems to suggest that it has more to do with proper (and early) marketing and promotion than the quality of the music.
Thoughts from the group on this study?
-Jed
Jed - your making my point... (somewhat).. social cues are important (see my formula). I wrote last year on how to use a momentum toward celebrity strategy to give off the right cues.
After I published this post, I thought to myself - I could have just said the following:
- make the best songs you can, and get help doing so.
- get them played as often as possible, and during the shortest possible time span.
- lonely spins played in solitude are not as impactful as spins enjoyed with friends (see my previous comment on this point).
- anything that smacks as celebrity momentum is a cue that hugely helps.
It's all common sense right? So the post was just mental masturbation unless you like shorthand formulas (L * OFR * SSR * CR = SONG FANs)..
As for data that provides "proof", the proof that I am interested in uncovering proves (right or wrong) is that digital music can't be marketed and that incremental improvements to song quality (or an artist working to become a better songwriter) are the biggest determinants to success (from today onward).
Since unlimited free and practically unlimited free streaming, music recommendation, and real-time data collection (regarding song traction) are relatively new (to the masses), and because accurate music filtering (by subjective quality - other than social filtering) hasn't even hit the marketplace yet, it's going to be a couple of years before we can definitively prove (right or wrong) which career tactics are most effective.
For me, I will take song quality over song promotion as the eventual winner, but I suspect both will remain important for at least another five years. Since I am betting (on one and not the other), within five years - nobody will bother doing anything with songs that don't fall into the top 10% (100,000 out of the 1,000,000+++ songs a year that are being uploaded to the Internet). These other songs (the bottom 90%) will barely see the light of day.
I know you are going to say artists are always going to want to honk their own horns - no matter how good or how bad their songs are... But, nobody has built the mechanism 'yet' that definitively tells artists when, where and why they should or should not bother (honking). I think the mechanisms are coming and I believe they will be trusted as accurate. (I seriously doubt they will be machine-based BTW.)
Bruce,
Honestly, I was trying so very hard not to make any points myself. :)
I was just kind of noodling this study and wondering how it all fits in, if at all.
Can you say more about the 'mechanisms' you believe to be coming? Now I'm dying of curiosity.
nope not here - working on closing the funding. but, I was going to call you soon about being an adviser.
I'd like to see all the assumptions tested more. The totally reasonable, common-sense assumptions often don't hold up to data, once data emerges. Of course, the problem is that most of us aren't interested in second-guessing what we're comfortable about, so oftentimes, that data never shows up.
@Jed
TopSpin assumptions are interesting because they've got a large pool of artist data to work with. They're valuing email list contacts at almost twice the rate of a website visit. I think that's an assumption we can ALL agree with. More interesting, though, they seem to value Google searches higher than anything -- if people are typing your name into the magic white box, that's a clear sign of intent to buy....or at least learn more and talk about the artist.
What interests me about TopSpin the most isn't their monetary models, though, it's how (if, really) they're looking at an artists fanbase demographics and THEN deciding how to proceed and format and market the NEXT project. In other words, are there key demographic "tells" they're looking for, which indicate a fanbase is more interested in an EP series than albums, for example?
To me, that's the biggest value of a huge database. Then again, I'm also more artist than businessman.
"They're valuing email list contacts at almost twice the rate of a website visit. "
those hotmail email addresses are like gold..
-B
@Bruce,
Don't go turning it around on me! You give ME advice, remember? Be forewarned, I am only more qualified than 2 of the people who post here regularly, and one of them is an alt that I use when I want to be anonymous. You may regret your choice...
@Justin
thanks for explaining more about Topspin. You are fundamentally asking the right question:
What can this data, or any other data, do to help us (the Artists and those that support them) optimize what we at ReverbNation call the Lifetime Value of the Fan (LTVF)? If it isn't actionable, its just an interesting factoid. Keep us posted on what you learn, please.
for the all the hype of formulae, they’re really only applicable to financial sustainability/success today. maybe one day we’ll evolve and create a metrics system with the appropriate variables to compute success in the form of happiness, peace, et al.
i am however curious to check out that Indaba Music site and your future post on what slows/accelerates the formula.
Lennon and McCartney were fortunate.