Importantly, the goal here was to estimate the effective value of each radio spin *per listener* so that rate can be compared to not only that rate being observed for the effective value of a stream on music services (e.g., Rdio, Rhapsody, or Spotify) per listener, but also those rates applicable to webcasting streams.

First, a quick clarification: Most chatter about radio royalties hinges on the value of a spin, and yet the chatter about music service royalties hinges on the value of a stream. However, this comparison between spins and streams is not usually/always equivalent. Why?

The usual “spin” value often refers to a radio play on a station or syndicated show that was experienced by a large audience (sometimes millions of people).

A stream payment usually refers to a play/stream by a music service experienced by a single listener (or at least a single subscriber account).

Therefore, I am trying to compare spins and streams on equal terms by converting this spin-to-millions value from Radio to a value per listener, as is the case for music services. Please scroll to the end of this post for an explanation of the per spin/stream per listener comparison in the context of licenses based upon percentages of revenue or blanket fees and advances.

Now for the numbers…

The Short Story:

Just the calculated rates and none of the overly numerical explanations…

Important: effective rates below are estimates of amounts paid only for the performance of the musical work (song/lyrics) and to the stakeholders of those works (publishers, songwriters, and lyricists).  In the US, radio stations pay royalties for only these performance rights and do not pay for performing rights to the stakeholders of the sound recording.

Taking a stand:

$0.0002977923 <- Estimated effective rate per spin per listener*
$0.0000992641 to $0.0005955847 <-Range**
at 15 songs per hour

$0.0003722404 <- Estimated effective rate per spin per listener*
$0.0001240801 to $0.0007444808 <-Range**
at 12 songs per hour

$0.0004963206 <- Estimated effective rate per spin per listener*
$0.0001654402 to $0.0009926411 <-Range**
at 9 songs per hour

$0.0013 <- Effective rate per stream per listener on music services
$0.000300 to $0.0015 <- Range
estimated through songwriter reports, musical work only

The Long Story (with the Inputs):

The effective rates paid by radio and music services in the US are less directly comparable to those rates paid in the UK. Unlike in the UK, radio broadcasters in the USA pay royalties to only one set of music rightsholders: those with an interest in the musical work [the publisher(s), lyricist(s), and songwriter(s)]. Music services in both countries, on the other hand, are paying both sets of rightsholders.

I will begin with the total Dollars collected from Radio by the three performance rights collectives in the US: ASCAP, BMI, and SESAC. While ASCAP openly discloses its domestic collections from Radio, BMI only discloses these values indirectly (in its annual report)—reporting the proportion of total collections that are not international, and that proportion of domestic collections that are from Radio. I had to estimate SESAC’s collections. Being a private company, SESAC does not publicly disclose its collections.

I will then break down this total value of collected Dollars on a daily, hourly, and finally per spin basis (for the set of music tracks hitting the ears of listeners at any moment in time in the US across all music radio stations).

Since not all radio stations are playing music (predominantly or exclusively), I have chosen to follow the royalty dollars to the radio-listening audience, through the tracks plausibly heard by only this audience.

Finally, I arrive at an effective range of the per spin per listener value through a set of estimates of the average size of only the music radio listening audience during the day in the US.

The overly numerical banter:

(A) $230,881,000 <- Dollars collected from Radio by ASCAP (pdf)

(B) $198,303,000 <- Dollars collected from Radio by BMI (imputed)

(C) $42,918,400   <- Dollars collected from Radio by SESAC (estimated)

(A)+(B)+(C)          <- Dollars collected from Radio by the Collectives
equals
$472,102,400       <- Estimate of Total Dollars collected from Radio in the US

/ 365 <- Number of days in the year, resulting in per day payments
/ 24   <- Number of hours in the day, resulting in per hour payments
equals
$53,892.97 <- Dollars collected per hour from US Music Radio

So, if music royalties were measured like a taxi meter, the meter would rack up royalties at a rate $53,892.97 per hour.

/ 12 <- Number of songs played per hour, resulting in per song payments
equals
$4,491.08 <- Dollars collected per simultaneous spins across entire US Music Radio

The meaning of this $4491.08 is simple.  PROs collect royalties from the performance of about X songs per hour (where X might be 12, or 15, or 9) across all music radio stations.  $4,491 is simply the Collections per Hour divided by X, if X were 12 songs per hour.

Note: That figure—$4,491.08—is not the value of a spin on a single station or show, like Jack FM. It is an estimate of the average total value of all spins across all music stations in the US given some number of songs played per hour.  A source like Jack FM would be one of the shows/stations playing music at any time. If, however, I reckoned that any station/network were 10% of the listening audience at some point in time, the value of that spin on that single station might be around $449.11.

Some might disagree with the rate of 12 tracks per hour (or about 36 minutes of music). And so I also ran estimates asserting 15 tracks per hour (about 45 minutes of music) and 9 tracks per hour (24 minutes of music).

We need to divide $4,491.08, however, by the average size of the US radio audience throughout the day that is listening to music radio to get an estimate of the value of each spin per listener. Essentially, if I could flip a switch and know how many people were listening to music on the radio at any moment, how many people (on average) would I find to be listening?

Unfortunately, such a switch does not exist. But a variation exists in the form of Arbitron’s estimates of the radio audience.

In the US, Arbitron estimated that during the most recent quarter approximately 241,300,000 people over the age of 12 listened to the radio at some time. This estimate is not the same as an estimate of the average size of the listening audience, however. In particular, it is not that portion of the audience that is listening to music (on the) radio at moments in time.

Arbitron estimates Hour-by-Hour listening as a proportion of its quarterly radio audience. In their 2010 Radio Today report (page 89), these ratings throughout the day range from a high of approximately 17% of quarterly listeners to a low of around 1% of quarterly listeners. The average across the 24-hour period appears to be in vicinity of 9.5%.

241,300,000 <- Arbitron estimate of quarterly radio listening audience, Q3 2011

$4,491.08      <- Dollars collected per spin if across entire US Radio audience

/ 6,032,500   <- approximately 2.5% of the quarterly radio audience
or
/ 12,065,000 <- approximately 5% of the quarterly radio audience
or
/ 24,130,000 <- approximately 10% of the quarterly radio audience
or
/ 36,195,000 <- approximately 15% of the quarterly radio audience

—————————-

Dollars collected per spin per listener for Radio in the US for various estimates of the average listening audience:

At 15 songs per hour
$0.0005955847 <- if the average listening audience is 6,032,500 people
$0.0002977923 <- if the average listening audience is 12,065,000 people
$0.0001488962 <- if the average listening audience is 24,130,000 people
$0.0000992641 <- if the average listening audience is 36,195,000 people

At 12 songs per hour
$0.0007444808 <- if the average listening audience is 6,032,500 people
$0.0003722404 <- if the average listening audience is 12,065,000 people
$0.0001861202 <- if the average listening audience is 24,130,000 people
$0.0001240801 <- if the average listening audience is 36,195,000 people

At 9 songs per hour
$0.0009926411 <- if the average listening audience is 6,032,500 people
$0.0004963206 <- if the average listening audience is 12,065,000 people
$0.0002481603 <- if the average listening audience is 24,130,000 people
$0.0001654402 <- if the average listening audience is 36,195,000 people

Finally, and importantly, I realize that Radio stations in the US do not pay royalties on a per spin (and per listener) basis. Instead, these Radio royalties are calculated by such means as a percentage of revenue, or as a result of a negotiation over a blanket fee.

I also realize that music services—such as MOG, Rdio, Rhapsody, and Spotify—are not—by default—paying royalties on a per stream (per listener) basis. Instead, these royalties may be calculated through a number of means, none of which can be openly discussed due to the joys of non-disclosure clauses.

However, the resulting pool of money from Radio can be and has been counted. And various sources have reported online their payments from music services. As a result, nerds like me can try to estimate some effective rate given the size of the pools, the rough number of tracks played, and the number of listeners.

*
The estimates above are a function of considering the average music radio listening audience (across moments in the day) to be 5% of the estimated quarterly radio audience as reported by Arbitron. For comparison, Arbitron estimates the average size of US Radio (all formats) audience to be approximately 9.5% of the quarterly audience. I worked below this number given (a) not all stations are music stations and (b) Arbitron may be overestimating the size of the Radio audience.

**
The ranges above are a function of considering the average music radio listening audience (across moments in the day) to be 2.5%, 5%, 10%, and 15% of the estimated quarterly radio audience as reported by Arbitron. For clarity, the smallest assumed listening audience will lead to the highest estimated rate per stream per listener in the ranges.

Below I try to calculate the effective value of a radio spin *per listener* so that rate can be compared to the rate being observed for the effective value of a music service stream per listener.

First, a quick clarification: Most chatter about radio royalties hinges on the value of a spin, and yet the chatter about music service royalties hinges on the value of a stream. However, this comparison between spins and streams is not usually/always equivalent. Why?

The “spin” value often refers to a radio play experienced by a large audience (sometimes millions of people).

A stream payment usually refers to a play/stream by a music service experienced by a single listener (or at least a single subscriber account).

Therefore, I am trying to convert this spin-to-millions value from Radio to a value per listener, as is the case for music services. Please scroll to the end of this post for an explanation of the per spin/stream per listener comparison in the context of licenses based upon percentages of revenue or blanket fees and advances.

Warning: I end up with a rather small number as the estimate of the value of a UK Radio spin per listener. Fortunately, and importantly, the radio audience in the UK is quite large overall, leading to a total pool of royalty monies that is large enough for most labels, artists, songwriters, and publishers to take notice.

Were the pool of money flowing from music services in the UK, such as Spotify, as large as that flowing from Radio, we might not be having these sorts of discussions. Maybe someday both of these pools will be large. The bigger question than these present rates, therefore, is whether we should and how we might get to that version of someday.

The Short Story:

just the calculated rates and none of the overly numerical banter…

£0.0002992992 <- Estimated effective rate per spin per listener
£0.0000998 to £0.0005985 <-Range
at 15 songs per hour

£0.0003741240 <- Estimated effective rate per spin per listener
£0.0001247 to £0.0007482 <-Range
at 12 songs per hour

£0.0004988320 <- Estimated effective rate per spin per listener
£0.0001662 to £0.0009976 <-Range
at 9 songs per hour

The estimates above are a function of considering the average music radio listening audience (across moments in the day) to be 5% of the estimated quarterly radio audience as reported by RAJAR. The ranges above are a function of considering the average music radio listening audience (across moments in the day) to be 2.5%, 5%, 10%, and 15% of the estimated quarterly radio audience as reported by RAJAR. For clarity, the smallest assumed listening audience will lead to the highest estimated rate per stream per listener in the ranges.

£0.0005000 to £0.005000 <- Music Services effective rate per stream per listener (estimated)

The Long Story (with the Inputs):

The effective rates paid by radio and music services in the UK are more directly comparable as compared—no pun intended— to those rates paid in the US. Unlike in the US, radio broadcasters in the UK pay royalties for both sets of music rightsholders: (a) those with an interest in the sound recording [aka, the neighbouring rights; the owner(s) of the recording, as well as the featured and performing artist(s)] and (b) those with an interest in the musical work [the publisher(s), lyricist(s), and songwriter(s)]. Music services are paying both sets of rightsholders as well.

I will begin with the total Pounds collected from Radio by the two core performance/performing rights collectives in the UK: PRS for Music and PPL.

I will then break down this total value of collected Pounds per day, per hour, and finally per spin (for the set of music tracks hitting the ears of listeners at any moment in time in the UK across all radio stations).

Since not all radio stations are playing music (predominantly or exclusively), I have chosen to follow the royalty dollars to the radio-listening audience, through the tracks plausibly heard by only this audience.

Finally, I arrive at an effective range of the per spin per listener value through a set of estimates of the average size of only the music radio listening audience in the UK during the day.

The overly numerical banter:

(A) £49,500,000 <- Pounds (2010) collected from Radio by PRS (pdf)

£61,700,000 <- Pounds (2010) collected from Broadcast/Online by PPL
x 70% <- Rough approximation of % of PPL B/O from Radio**
equals
(B) £43,190,000 <- Estimate of Pounds collected for Master Performance

(A) + (B) <- Pounds collected from Radio by PPL and PRS
equals
£92,690,000 <- Estimate of Total Pounds collected from Radio in the UK

/ 365 <- Number of days in the year, resulting in per day payments
/ 24 <- Number of hours in the day, resulting in per hour payments
equals
£10,581.05 <- Pounds collected per hour from UK Music Radio

So, if music royalties were measured like a taxi meter, the meter would rack up royalties at a rate £10,581.05 per hour.

/ 15 <- Number of songs played per hour, resulting in per song payments
equals
£705.40 <- Pounds collected per spin across entire UK Music Radio

Note: That figure—£705.40—is not the value of a spin on a single station, like BBC Radio 1. It is an estimate of the average value of all spins across all music stations in the UK at a moment in time, one station of which would be the BBC’s Radio 1. If, however, I reckoned that BBC Radio 1 were 10% of the listening audience at some point in time, the value of that spin on that single station might be around £70.54.

Some might disagree with the rate of 15 tracks per hour (or about 45 minutes of music). And so I also ran estimates asserting 12 tracks per hour (about 36 minutes of music) and 9 tracks per hour (24 minutes of music).

We need to divide £705.40, however, by the average size of the UK radio audience throughout the day that is listening to music radio to get an estimate of the value of each spin per listener. Essentially, if I could flip a switch and know how many people were listening to music on the radio at any moment, how many people (on average) would I find to be listening?

Unfortunately, such a switch does not exist. And so, now is that uncomfortable time when assumptions, guesstimates, and hopefully well-reasoned estimates are made.

In the UK, RAJAR estimated that during the most recent quarter approximately 47,137,000 people over the age of 15 listened to the radio at some time. This estimate is not the same as an estimate of the average size of the listening audience, however. In particular, it is not that portion of the audience that is listening to music (on the) radio at moments in time.

Below, I will calculate an estimate of the value per spin per listener at three guesstimates of the average size of the music radio listening audience during the day in the UK, given the peak/trough variation in this audience. Please feel free to share your thoughts/insights as to what other inputs I could/should use here.

Added: In the US, Arbitron estimates Hour-by-Hour listening as proportion of its quarterly radio audience. In their 2010 Radio Today report (page 89), these ratings throughout the day range from a high of approximately 17% of quarterly listeners to a low of around 1% of quarterly listeners. The average across the 24-hour period appears to be in the 8-10% range.

47,137,000 <- RAJAR estimate of quarterly radio listening audience, Q3 2011

£705.40 <- Pounds collected per spin if across entire UK Radio audience
/ 2,356,850 <- approximately 5% of the quarterly radio audience
/ 4,713,700 <- approximately 10% of the quarterly radio audience
/ 7,070,550 <- approximately 15% of the quarterly radio audience

—————————-

Pounds paid per spin per listener for Radio in the UK for various estimates of the average listening audience:

At 15 songs per hour
£0.0002993 <- if the average listening audience is 2,356,850 people
£0.0001496 <- if the average listening audience is 4,713,700 people
£0.0000998 <- if the average listening audience is 7,070,550 people

At 12 songs per hour
£0.0003741 <- if the average listening audience is 2,356,850 people
£0.0001870 <- if the average listening audience is 4,713,700 people
£0.0001247 <- if the average listening audience is 7,070,550 people

At 9 songs per hour
£0.0004988 <- if the average listening audience is 2,356,850 people
£0.0002494 <- if the average listening audience is 4,713,700 people
£0.0001662 <- if the average listening audience is 7,070,550 people

Finally, and importantly, I realize (realise) that Radio stations in the UK do not pay royalties on a per spin (and per listener) basis. Instead, these Radio royalties are calculated by such means as a percentage of revenue, or as a result of a negotiation over a blanket fee.

I also realize (realise) that music services, such as Spotify, are not—by default—paying royalties on a per stream (per listener) basis. Instead, these royalties may be calculated through a number of means, none of which can be openly discussed due to the joys of non-disclosure clauses.

However, the resulting pool of money from Radio can be and has been counted. And various sources have reported online their payments from music services such as Spotify. As a result, nerds like me can try to estimate some effective rate given the size of the pools, the rough number of tracks played, and the number of listeners.

** As far as I could tell, PPL does not breakdown its Broadcast and Online revenue further in its Annual Report. There was not direct comparable for this estimate of the proportion of PPL collections that are derived from UK Radio royalties. I erred on the side of too large a proportion rather than too small. Any guidance on this figure would be appreciated

And, first off, many thanks to Jeff and Tunecore for releasing these data for the rest of us to investigate.

It appears life in the long tail of music sales may be rather rough. DMN has one angle (minimum wage), while I took a sales distribution approach.

Of the top 6000-ish (5938) artists about which Tunecore just released sales data, the sales distribution follows an 80/20 rule relatively closely. Collectively, the top 22% of these artists earned about 80% of the monthly money.

Given these 6000 are only 1% of reported 600,000 accounts, however, it would appear that Tunecore artist sales exhibit an extremely pin-headed distribution rather than a long tail distribution (as per Chris Anderson).

In fact, these 6000-ish artists produce enough revenue that, if converted to annual dollars, they might be earning half or more of total Tunecore artist revenue.

The Big Question: Is a Network (blanket license) Worth Doing? from david touve on Vimeo.

In the wake of this announcement, Eliot VanBuskirk over at Wired.com suggested YouTube viewing now tops network prime time viewing—at least in the US.

Recently at the Telco 2.0 conference, I tried to put YouTube viewing in context and made some estimates and conversions so I could compare YouTube to the World of Television viewing.

Daily YouTube views = 2,000,000,000
Average length of YouTube video = 4.3 minutes
Average time US household watches TV each day = 5.4 hours
Household TV viewing hours converted to YouTube views = 75.4 YT views

US household daily TV viewing converted to YT views = 19,355,665,442
Global household daily TV viewing converted to YT views = 389,019,943,256 (high)
Global household daily TV viewing converted to YT views = 311,215,954,605

——————————–

YouTube views as a percentage of global TV viewing = 0.514% low estimate
YouTube views as a percentage of global TV viewing = 0.643% high estimate

For a video of these data as presented, just follow this YouTube link

Unfortunately, the methods for and outcomes of mimicry often get conflated.  The result of this conflation is something we might call Best Practice Bingo.  A few people are starting to be concerned about the nature of this bingo game (Billboard, more), and these concerns are warranted.  We are in danger of confusing consequences for causes, attributing success to what really are outcomes while overlooking the far more complicated How and Why that led to these outcomes.

The basic equation for this bingo game are as follows:

SO + IF + E³ = BPB

(Study Outliers) + (Ignore Failures) + (Exceptions Exceptions Exceptions)
= (Best Practice Bingo)

Study Outliers

The first stage of best practices bingo involves studying outliers—i.e., successful firms (or individuals)—and describing either  the basic process of what these winners do or the basic attributes of these winners.  The appeal of this first stage is so compelling, quite frankly, we cannot help ourselves.  Winners often seem to success despite the odds, and condition that should immediately suggest outlier status.

When presented within the best practice argument for success the SO stage usually takes the form of case studies—rich stories that present the behaviors/attributes of winners as truly novel and or unique.  Importantly, these stories are told backwards.  They describe what the winner did from the beginning with the end result of these actions being success.  In truth, the winner succeeded and this success led the researcher to notice the firm and then attribute a set of behaviors/attributes to this success.

Ignore Failures

The second yet obviously related stage of this bingo game involves ignoring failures through the outlier selection process.  Ignoring failures is built into the study outliers stage, yet the presence of failures should be key to any test in search of what separates the wheat from the chaff, the winners from the losers.  By way of ignoring failures we turn off the capacity to tell whether what we see winners doing happens to be something truly unique to winners.  And by explaining the behaviors and attributes of only the winning outliers in arrears, we lose the ability to distinguish prediction from description. Losers in Bingo games never stand up and scream “we lost!”

Exceptions Exceptions Excpetions

The final condition for the best practice bingo game is the ongoing introduction of exceptions, exceptions, exceptions.  In the event of any failing firm (or individual) that seems to otherwise display the attributes of winning firms we propose exceptions, usually based on some prototypical case or argument.  By prototypical I simply mean the process or attributes of winners are argued to stand as ideal examples of the process or attribute in question.  Failed firms may have something that looks like these processes/attributes, but they just didn’t do/have these things just right.  These firms are, therefore, excluded from the condition in arrears.  When you start hearing the word “but” all the time, be very worried that someone may be making as ass of you.

Best Practice Bingo

The result of this all-too-common three stage process is a situation we might call best practice bingo.  Upon learning about these behaviors and attributes of winning firms, other firms begin to mimic these features and the bingo game begins.  Some of these firms succeed, others fail.  The pundit excludes failures from the model for simply not doing/having it “just right .”  Successful outcomes are almost always accepted as de facto and are used to support the model.

Example #1: CWF + RTB = $$$

Circulating the network of pundits (examples here, here and here) these days is Techdirt’s recent proposition that the model for future business success can be phrased: (Connect with Fans) + (Reason to Buy) = $$$.  When presented in public (here and here), this proposition is pretty much always a function of case studies—Trent Reznor, Jill Sobule, etc.

Just about every presentation on the CWF+RTB premise involves studying outliers—winners who seemed to embody the ethos of this model.  These artists appear to be succeeding by way of this model, so what’s the problem?  IF + EEE.

First and foremost, failures are ignored.  Any number of artists, both now and in the past, have employed a method through which they aspire to connect with fans and give these fans a reason to buy.  In fact, just about every business on the planet is in the business of trying to connect with potential customers and give these customers are reason to open their wallets.  Some of these artists have succeeded while others have failed.

Finally, the exceptions are starting to roll in.  In order to workaround the bingo game, we are starting to hear about folks just not really connecting with fans, or just not given those fans are reason to buy.  And so, the big buts will begin.

Example #2: CWE + RTV = Election

Let’s be honest, a translation of the CWF model for politics would be: Connect with the electorate + Give them a reason to vote for you = Election to office.  CWE + RTV = Election

When translated to other markets, the model seems to offer less insight than description.  The winner of any election connected with the electorate and gave that electorate a reasons to vote.  However, these features were consequences not causes.

Here’s to a bingo-free lifestyle.

Click here to download: Structuring the Resolution.

The text version:

From a platform mindset, our approach to not only licensing but also providing music on networks might dramatically change.  In the following section I will briefly describe a simple three-tier structure for music licensing that could be considered.

Importantly, the structure described below does not involve a fundamental shift in how we approach and design music licenses.  Licensing music rights by way of collectives and blanket terms is a premise that is more than 100 years old.  The intent of the platform structure is to recognize music rights as a commons environment, rather than try to enact technical or legal measures that might somehow attempt to treat these rights as truly, privately controlled property.  The intent of the tiered structure is to make plausible the licensing of a range of consumer-facing services.  Essentially these services would operate “on top of” a licensed platform.  This three-stage structure is an intentional modification of what might otherwise be seen as a two-part tariff.  As the reader will see, I have broken up the enactment of the tiers so as to weaken the concerns for monopoly control.

Three-Tiered License

In an effort to resolve the music providers’ dilemma, I propose a three-tier license structure for establishing music as a platform underlying the infrastructure of internet service provision.  Tier One licenses would be granted directly to ISPs, while Tier Two licenses would be granted by ISPs to MSPs in exchange for the latter partys’ reliance upon the primary platform for the development of consumer-facing products, services and experiences.  Tier Three licenses involve the relationships between FANS, and their associated ISPs and/or MSPs.  This third tier involves the business models through which music is ultimately experienced by FANs.

Tier One

The Tier One license is provided directly to ISPs for the provision of music on their networks.  This primary tier of service license essentially establishes the music platform.  Music files are made available to ISPs, who then can resolve requests for these files on behalf of end users.  This licensed platform for music might even inherit its own informal URL space (e.g., music://  ), and a request made for some location within this space would be resolved by ISPs and fulfilled (i.e., served from some recognizable location) by the assigned representative of a music rights holder.

An immediate benefit of such a platform structure can be seen in the phenomena that are URL linking and bookmarking – the simple act of sharing the location of a web page (http://www.website.com/really_cool_webpage).  Given linking to a web page is so damn easy – merely a function of copy-paste – and generally reliable, the average web user does not choose to download and pass along the raw HTML file of interest with all of the associated media.  Instead, we simply copy a link, paste it into an email, and share with friends some experience we find compelling.

The objective of music:// as a URL space is to make acquiring and sharing licensed music files just plain easier and more reliable than transmitting these files through alternative venues.  Any end user wishing to share a file simply needs to share the music:// URL associated with that file.  This URL, when selected, transmits the file to the end user by the preferred method (e.g., streaming or download).  In the results as presented within the file sharing applications or search engines, these verified and reliable files would likely be granted higher priority given their greater likelihood of satisfying user requests.

Furthermore, by converting music to a URL space mediated by ISPs we can introduce not only the ability to gather data relevant to the distribution of royalties, but also the capacity to gather these data anonymously.  ISPs release to the rights representatives the usage of files that have been served, while user-specific data would be gathered separately and used independently.  These user-specific data would only be associated with usage upon the user’s permission.

Tier Two

A Tier Two license might be provided by ISPs to MSPs for the reliance of these commercial operators upon the hosted music platform in the development of consumer-facing products, services and experiences.  Essentially, copyright holders would invite ISPs to become relevant and relied upon actors in the music value chain, with the capacity to develop licenses and fee structures for downstream MSPs.  A portion of these downstream license fees might pass through to MRPs, the assigned representatives of music rights holders.  As a result, a sort of secondary marketplace forms for the provision of music to end users – this secondary market providing a means for informing the negotiated price for the Tier One license.

Quite truthfully, the availability of tens of millions of music files presents end consumers not only with a clear opportunity, but also with a very clear problem – navigating and organizing such a vast catalog of music. The purpose of the Tier Two license is to empower MSPs with not only the rights but also the infrastructure through which the problems of end consumers might be reasonably solved.

For example, search providers such as Google and even file sharing applications such as Limewire, rather than being populated by links to unqualified files and transitory IP addresses, would instead be populated by URLs resolving upon qualified and reliable music files.  Music services such as Rhapsody, iLike or Project Playlist would be supported by a platform of consistently available media.

Tier Three

A Tier Three license is the final bridge between FANs, ISPs and MSPs.  The third tier involves the innovations and associated business models, through which music is ultimately experienced by FANs.  By separating this tier from direct influence by MRPs, the goal is to empower innovation, while permitting the gains from these innovations to filter through the system to music rights holders.  The price paid by FANs and MSPs for the provision of music filters through to the license paid by ISPs for the right to provide such music openly.

A visual of the layers and tiers:

By Theory, I simply mean a statement of some causal relationship(s), and/or conditional process(es) that can be proven to be false.  Notice, I did not say that a theory is something that can be proven to be true.  This distinction – falsification – is fundamental to what it seems we call our scientific method.  Furthermore, as highlighted by the Oxford dictionary, a theory involves “general principles independent of the thing to be explained.”  The outcome and conditions are not the theory – the theory is in the spaces in between the cause and the consequent.

By Ideology, I simply mean “a system of ideas and ideals” that can be shown to be true.  Importantly, these principles may not be independent of the thing to be explained.  Instead, ideologies are alternatively explanations or interpretations.  The cause and the consequent are fused together, no longer independent.

For example, the various disciplines of the social sciences – economics, sociology, political science – are supported by various ideologies.  These disciplines are cornerstoned, and at times distinguished, by certain ideas and assumptions about the world such that explanations make sense. These ideologies then give birth to all sorts of theories about human behavior, at the level of individuals or the aggregation of individuals we call markets or societies.

The Long Tail may in fact be an Ideology – a system of ideas and ideals that once in place can be shown to be true.  I am coming to this conclusion given most challenges to the claims of the Long Tail are met with re-stated conditions and exceptions.  The objective of the Long Tail thesis appears to be to describe a set of conditions under which both the cause and the consequent would be shown to be true.

As such, the premise(s) of the Long Tail may not form a Theory to be tested, but an Ideology to be adopted and adapted.

Quite honestly, as an iPhone owner, I can say that this thing makes other phones just look like toys.  Not that toys are a bad thing.  But as more phones live and work like iPhones, social life will have to be impacted in unexpected ways.