Five Cents a Song…

The other day, I attended a talk titled, “The Future of Music and the 5¢ Solution — How artists and consumers can reclaim ownership of music,” by Daniel Levitin, a professor in the psychology department of McGill University, who has had an impressive career in the music/recording industry.

The basic idea behind the talk was originally proposed by Sandy Pearlman and Professor Levitin in March 2005 — Specifically, that the Apple iTunes price point of 99 cents per song is much too high and that a price point closer to 5 cents per song would substantially increase revenues for record companies and artists.

Price Point

His argument that the price point is too high is based on the [2004 ?] statistics that there were 300 million legal iTunes downloads and 30 billion illegal downloads (where one billion is a thousand million) during the year. By lowering the price and getting some fraction of the illegal downloaders to become paying customers, you increase revenue. By using a simple-minded calculation, I figure that at a 5 cent price point 18.8% of those 30 billion illegal downloads would have to have been paying downloads instead to generate the same gross revenue. Here are some other price points:

 Price per Song   Percentage of the 30 billion illegal downloads that would need to be legal/paying downloads 
$0.99  0.0%
$0.50  1.0%
$0.10  8.9%
$0.05 18.8%
$0.01 98.0%

Of course, the economics are not that simple. Such an adjustment would eat into the total sales ($3B in 2004) and simultaneously encourage the legal downloaders to potentially purchase even more music. Note that Professor Levitin emphasized that 5 cents was an example; it could be bigger or smaller as long as it was greater than zero. Also, instead of purchasing a song with unlimited plays, one could imagine that each time a song is played, the consumer is charged, say a tenth or a hundredth of a cent. The idea is that the actual value would be small enough that an individual consumer doesn’t really care but still generates a revenue stream.

State of the Record Industry

In order to discuss how consumers and musicians can reclaim ownership of music, Professor Levitin gave a rather interesting overview of the record industry. I wasn’t able to keep up with all the details. Here are some of the main points he made:

  • The top 5% of the artists make 95% of the money.
  • Most musicians either have days jobs or are on the road 340 days of the year.
  • Record companies no longer find talent and then nurture it (e.g., Bob Dylan, Talking Heads, Barenaked Ladies). Rather, they find money makers and milk them (e.g., Spice Girls, ‘NSync, Britney Spears).
  • In the 1980s, groups of investors began to buy radio stations and national consulting firms began to program (select songs for play) groups of stations.
  • With the passage of the Telecommunications Act of 1996, the cap on the number of stations an entity could own in a given market was lifted. As a result, Clear Channel grew from 40 stations to 1240 stations.
  • Massive consolidation in the record industry leaves four major labels (Sony BMG, EMI, Vivendi, Warner)—all are losing money and all are for sale for pennies on the dollar.

The main take-aways from this discussion are (1) the distribution of revenue is not fair to artists, and (2) the consolidation of the record industry, the radio broadcasters, and the radio programmers has reduced the diversity of broadcast content to the point that 90-100% of radio play is from the four major labels. The major labels have a market share of about 75% meaning that about 25% of the record industry gets little or no radio play.

Value Add-ons

For the people paying 99 cents a song, dropping the price by a factor of twenty sounds great; however, how does one get people to pay (even a nickel) for something they’ve always gotten for free? The answer: value add-ons.

The value add-ons could be that every song (including The Beatles) would be available online for every codec (i.e., in every format: MP3, AAC, Ogg) and that downloaded songs would not be corrupted and their tags would be accurate. Also, there would be the assurance that the musicians are participating in the revenue stream—musicians should be able to make a living as musicians.

Professor Levitin made a point of noting that the idea of paying for something that was once free is not without precedent. He gave two examples: TV and books. In the case of TV, if you use an antenna to pick up the broadcast signal, it is free. However, people regularly pay $50 a month for cable. I’m not sure that this is analogy completely works for digital music. I do concede that the cable signal is likely to be better than that from an antenna and that’s worth something. Having extra channels on cable is more a case of “bundling” rather than value-added. In the case of books, libraries will loan you one yet people still buy books. At this point in the talk, someone from the audience pointed out that people simply like to own the artifact—the actual book or CD—for reasons that may be purely emotional.

New Problem: Selection/Recommendation

If you’re like me, the growth rate of your CD collection significantly dropped after graduating from college—after that, there were far fewer people available to recommend music for you to try. If every song becomes available on the web, simply finding new music that you are likely to want to buy becomes a big problem. Given its decrease in diversity, broadcast radio is not likely to be much help. Professor Levitin explained that a recommendation engine would represent a significant value add-on. The recommendation engine would need to take into account a user’s personal tastes as well as their current mood. He then showed a screenshot of a system he worked on from MoodLogic.com.

Interestingly, the recommendation engine idea points to how the record industry might evolve to where music is 5 cents a song: Professor Levitin wrapped-up the talk by suggesting a buy-out by the major search engine companies. While there are certainly non-trivial differences between Internet searching and music recommendation, there are no doubt similarities. If Google, Yahoo, Microsoft, and Ask were to purchase a significant portion of the record industry, they would be in the position to index all available music and implement the proposal.

Additional Thoughts

Because the talk only lasted about an hour, we weren’t able to explore the nuances of the proposal in depth. While preparing this weblog entry, I’ve had the time to think about how I’d like the system to work. For me, the big issues preventing me from acquiring music online are:

  1. Privacy/Anonymity — no one needs to know if I’m a closet ABBA fan
  2. Unrestricted Personal Use — I want to be able to manipulate the bits of the song for my own use
  3. Reasonable Cost — $0.99 per song from iTunes is too much for a song with digital rights management (DRM) restrictions (see #2) that is purchased from a named account (see #1)
  4. Musician Compensation — I’d like to know that the artists and musicians benefit from my purchase

With the right kind of cryptographic protocols, it should be possible for me to anonymously purchase a song while still compensating the musicians.

In addition, I would like to use a recommendation engine. However, the design of MoodLogic’s system requires that one’s collection be uploaded to their servers for analysis. From MoodLogic’s Privacy Policy:

Why does MoodLogic identify my songs? Do they need to know what’s in my collection?
Simply stated – If we don’t know what songs you have, we can’t help you organize them, clean their tags, discover new music, or build one click playlists.

MoodLogic understands digital audio – and we know that a very high percentage of files have been linked with incorrect (or altogether missing) filenames and tags. It’s not easy to sort your music if artist and song names are misspelled – and it’s impossible to build one click playlists if your songs can’t be linked to descriptive data. In an effort to eliminate this problem, MoodLogic developed powerful media recognition technology to identify songs (and return their profiles) without the need for filenames or tags.

MoodLogic also compiles lists of identified songs, which help us better understand our community on an aggregate basis while improving the quality of our services. MoodLogic also may publish lists of such aggregated data (like ‘most popular songs’) so that others may also benefit from this information.

Instead of uploading my collection, I would much rather their system work like a virus scanner. That is, I periodically download (on a subscription basis) updates to the recommendation database so that I could get the latest recommendations.

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