Book Review of “How Music Got Free”

"CD", Image by Dean Hochman

“CD”, Image by Dean Hochman

It is nearly impossible to compete in a consumer market when a previously lucrative product is suddenly available for free. This phenomenon adds a whole new meaning to the notion of “priced to sell”.

No industry illustrates this tectonic disruption brought about by the Net more than the music business during the last 20 years. While there has been an ocean of ink and a quantum of bits expended telling this story, I have come across none more compelling, thorough and entertaining than How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy by Stephen Witt (Viking, 2015). This is a great story well told with clarity, precision, style and humor.

While the tales of Napster and the other peer-to-peer sharing networks, the lawsuit by Metallica and other litigation by the Recording Industry Association of America (RIAA) to stop them, and precipitous drop in CD sales since then have all been previously told at length elsewhere, the author takes us down some new and alternative narrative paths. Witt has accomplished this skillfully weaving together the stories of the German engineers who created the MP3 format, a prolific music pirate, and a music industry mogul. The intersection of their activities in the music downloading revolution makes for hours of absorbing and instructive reading.

The book succeeds simultaneously as a business case study and a human interest story. It deftly leverages all three main plot threads in a narrative that heightens the reader’s interest as the events steadily crisscross the real world from rural Kentucky to Germany to New York City, and then likewise online across the web. Any one of these stories would have made for engaging reading on their own. Yet they are carefully fitted together by the author in a manner that relentlessly propels the all of them forward.

He also wisely wastes none of his text on superfluous side trips. Rather, he maintains a consistent focus throughout on how the music biz got turned upside down and inside out by a series of fast-breaking developments it neither fully understood nor had any viable alternatives ready to counter it.

A roster of A-List Hollywood writers and talent agents could not have possibly done better in creating the members of the real life cast. There are many useful lessons to be learned from them about business strategy, marketing, competition, and the strength of the human character in the face of the unprecedented and massive disruption* of what had been such a highly leveraged and lucrative market.

First and foremost among them was Benny “Dell” Glover. The details of his online and offline exploits read as though they were extracted from deep inside the You Can’t Make This Stuff Up file. He worked in a rural CD manufacturing plant and that afforded him access to the latest releases by music industry’s top acts. Often a month in advance of their commercial debut, Glover would smuggle them out of the plant, encode them using the MP3 format, and upload them for free distribution online through Napster and a host of other peer-to-peer networks. He was also part of a larger band of well-organized, tech savvy and daring digital music pirates who referred to their collective activities as the “Scene”.  Glover was likely responsible for the largest volume of free music that ever got digitally disbursed.

Second was Karlheinz Brandenburg, the lead engineer and inventor of the MP3 technology. He ran the group that devised MP3 technology without any intent whatsoever of how it eventually ended up being used. It was a technological accomplishment that at first drew little attention in the audio industry. There were other competing compression formats that were gaining more traction in the marketplace. Nonetheless, through perseverance, superior technical skills and a bit of favorable circumstances, MP3 began to find success. This was first in the broadcast marketplace and later on as the tech of choice among the music pirates and their audience. Brandenburg’s transformation over time from a humble audio engineer to an experienced business executive is deftly told and threaded throughout the book.

Third was Doug Morris who, during the events portrayed in the book, was the CEO of Universal Music Group (UMG). While Glover’s and Brandenburg’s parts in this narrative make for some engrossing reading, it is Morris’s meteoric rise and determination in the music industry that pulls the entire story together so very well. Not only does he reach the pinnacle of his field as a top executive in the largest music companies, he does everything in power to try to keep UMG economically competitive while under siege from freely downloadable MP3s recorded by his deep and wide talent bench.

While he did not have a hacker’s understanding of MP3’s technical ministrations, he fully understood, reacted and resisted its profound impacts. His initial line of attack was litigation but this proved to be ineffective and produced much negative publicity. Later he successfully monetized UMG’s vast trove of music video by forming the hosting and syndication service on Vevo. He is the most resourceful and resilient player in this story.

These three protagonists are vividly brought to center stage and fully engaged in Witt’s portrayal of their roles and fates in this Digital Age drama.  Just as the superior acoustics in a musical venue can enhance the performances of musicians and actors,  analogously so too does the author’s reporting and expository skills animate and enliven the entirety of events across his every page of his book. Indeed, “How Music Got Free” completely fulfills its title’s promise and, clearly, hits all the right notes.


At the time of the events portrayed in How Music Got Free, there was widespread fear that it would become increasingly difficult for artists and entertainment companies to ever profit again as they had done in the past. As a timely follow-up exploration and analysis how this never quite came to pass, I very highly recommend reading The Creative Apocalypse That Wasn’t by Steven Johnson, which was published in the August 23, 2015 edition of The New York Times Magazine.  (Johnson’s most recent book as also reviewed in the January 2, 2015 Subway Fold post entitled Book Review of “How We Got to Now”.)


*  The classic text on the causes and effect of market disruptions, disruptors and those left behind, read The Innovator’s Dilemma by Clayton Christensen (HarperBusiness, 2011). The first edition of the book was published in 1992.

Two Startups’ Note-Worthy Efforts to Adapt Blockchain Technology for the Music Industry

"Coachella Day 1 [2nd week] - Sahara Tent", Image by The Bull Pen, This work is licensed under a Creative Commons Attribution 4.0 International License.

“Coachella Day 1 [2nd week] – Sahara Tent”, Image by The Bull Pen

With the advent and then propulsive web-wide spread of MP3 file technology during the last twenty years*,  all of the music industry’s consumers, artists, recording companies, talent agents, business models,  distribution channels and intellectual property rights have been radically transformed. Today, the big money in the industry today is most often made by artists with established names who are able to draw audiences during their tours, sell merchandise, and continue to sell and stream music from their catalogs.

Of course, nowadays every well-known, moderately known and unknown act has an online presence to engage and inform their fan bases through an array of social media platforms and dedicated websites. Still, the music biz today is an even tougher business to earn a dollar than it ever was before. (See also the December 10, 2014 Subway Fold post entitled Is Big Data Calling and Calculating the Tune in Today’s Global Music Market?.)

In an effort to adapt dramatically new technology to energize, innovate and democratize the music industry, two recent startups, both still in their development stages, are using blockchain technology in previously unseen and imaginative ways. The blockchain is, in its simplest terms, a distributed, decentralized, transparent and encrypted database that acts as an online ledger to record transactions, documents and other information. It is most often used to memorialize transactions involving bitcoin. (See the May 8, 2015 Subway Fold post entitled Book Review of “The Age of Cryptocurrency” concerning a comprehensive new book on this subject.)

These early stage startups were the subject of a truly fascinating article posted on Billboard.com on August 5, 2015 entitled How ‘the Blockchain’ Could Actually Change the Music Industry by Gideon Gottfried. I will summarize, annotate and ask some unencrypted questions of my own.

I.  PeerTracks

The first startup is called PeerTracks. Their plan is to establish a music streaming and retail platform that includes “fan engagement and peer-to-peer talent discovery”, according to its president, Cedric Cobban.  They will use the blockchain for its transactions and paying artists directly for any revenue generated when their music is streamed “on a per-user-share basis”. Their launch is currently planned in about two months.

The core of their approach is to generate marketing revenue through the use of “artist tokens”. This is a system whereby each musical artist can create their own tokens with their name and image, and then set the permanently fixed amount of them to be made available. These tokens are intended to take on the characteristics of a “sub-cryptocurrency” (similar to some of Bitcoin’s characteristics), whereby the value that emerges for them is a direct indicator, based upon supply and demand, of the artist’s appeal. Site users can also speculate on the future value of the music and merchandise of currently unknown musicians.

The artists on PeerTracks will have the capabilities to affect the relative value of their own tokens. They will be enabled to buy back their tokens with any income they generate from “streams, sales, merch, tickets”. They can also permanently eliminate some tokens to decrease their supply and, in turn, increase their value.

Conversely, artists can affect demand by the types of items they offer to their token holders. Among other things, they can offer “discounts, free tickets, giveaways”. By providing incentives for fans to acquire their token, artists can raise the tokens’ relative values. As well, there are potential benefits to advertisers on PeerTracks interested in implementing paid sponsorships for more recognized music acts with product giveaways.

All songs uploaded on the site will be accompanied by a “smart contract“. According to the immediately preceding link to Wikipedia, smart contracts are “computer protocols that facilitate, verify, or enforce the negotiation or performance of a contract, or that obviate the need for a contractual clause”.  The smart contracts on PeerTracks divide up the funds generated accordingly among the parties involved in the song’s composition and performance. This is considered to be an important advance in using the blockchain and, it is hoped by developers currently working on this, will become a platform upon which new business models will emerge.

II.  Ujo

The second startup in this space is called Ujo. Their plan to use the blockchain to improve both the distribution of royalties to artists and music licensing. They intend to accomplish this by establishing a “rights and payment infrastructure”. It will be free to use and open for third parties to create their own apps for new services including, among others, curation, streaming and negotiation.  Similar to PeerTracks, they are working on an alternative means to distributing revenues to “artists and rights holders”. Furthermore, they are trying to build a blockchain-based means to determine ownership of creative works.

The prospective adoption of this by the music industry of this entirely new system is expected to take time because of its tendencies to keep data private as well its outdated and often incompatible systems. Phil Barry, who is involved Ujo along with about 20 other developers, hopes their new system will unify and replace the legacy systems. He believes the platform will provide economic advantages to artists and recording companies receiving their royalties through it. As well, this will provide “new revenue and business models”, new ways for consumers to enjoy music, and simplification to the manner in which “music is managed and licensed”.

When an artist creates a new song in the future, using Ujo it will be permanently stored on the blockchain and assigned a unique ID. If another artists or performers changes anything about the song, their subsequent versions will receive a new ID and be “instantly recognizable”. Any resulting revenue from the song will then be distributed immediately and “proportionately to each rights holder”.

My own questions are as follows:

  • What other marketplaces, technologies and professions would benefit from using comparable types of blockchain adaptations?
  • Could traditional legal documents such as contracts, leases and wills, among many others, be written to the blockchain to make certain that all parties to them met their obligations?
  • Could artists’ tokens likewise be created for actors, writers, painters, graphics artists and other creative types?
  • What would be the results of a book or any other publication being written to the blockchain in terms of royalties, rights, subscriptions and recognition?

March 4. 2016 Update: For a related follow-up on this post please see the new Subway Fold post entitled The Mediachain Project: Developing a Global Creative Rights Database Using Blockchain Technology

June 5, 2017 Update:  An new article posted today, June 5, 2017, on the Harvard Business Review blog entitled Blockchain Could Help Musicians Make Money Again, by Imogen Heap, looks at the potential of blockchain technology from a musician’s point of view. A highly recommended read if you have an opportunity to click through. 


*  For an outstandingly written and highly engaging account of the total transformation of the music industry, I very highly recommend a recently published book entitled How Music Got Free: The End of an Industry, the Turn of the Century, and the Patient Zero of Piracy, by Stephen Witt (Viking, 2015). I just finished reading this and to say the least, it rocked.

Google is Giving Away Certain Patents to 50 Startups In Their Latest Effort to Thwart Patent Trolls

"She Runs Neon Fraction of a Second", Image by Wonderlane

“She Runs Neon Fraction of a Second”, Image by Wonderlane

In the highly competitive world of creating, monetizing, defending and challenging tech-based intellectual property, “free” is neither a word often heard nor an offer frequently made.

However, Google has just begun a new program, for a limited time, to give away a certain types of patents they own to an initial group of 50 startups.  This is principally being done in an effort to resist time and resources devouring litigation with “patent trolls“, companies that purchase patents for no other purpose than to litigate infringement claims in their attempts to win monetary judgments. (We first visited this issue in an April 21, 2015 Subway Fold post entitled New Analytics Process Uses Patent Data to Predict Advancements in Specific Technologies.)

The details of this initiative were carried in a most interesting new article on TechCrunch.com posted on July 23, 2015 entitled Google Offers To Give Away Patents To Startups In Its Push Against Patent Trolls by Ingrid Lunden. I will summarize, annotate, and pose some free questions of my own.

In April 2015, Google successfully started a temporary program for companies to offer to sell them (Google) their patents. Then on July 23, 2015, they launched a reciprocal program to give away, at no cost, “non-organic” patents (that is, those purchased by Google from third parties), to startups.

The recipients of these giveaways are required to abide by two primary conditions:

  • They must join the LOT Network for two years.  This is a tech industry association of patent owners dedicated to reducing the volume of patent troll-driven litigation.
  • The patents can only be used defensively to “protect a company against another patent suit”. Thus, the patents cannot be used to bring a case “against another company” or else its ownership “reverts back to Google”.

Kurt Brasch, one of Google’s senior patent licensing managers who was interviewed for the TechCrunch story, expects other members of the LOT Network to start their own similar programs.

For any of the 50 startups to be eligible for Google’s program, another key requirement is that their 2014 revenues must fall between $500,000 and $20 million. Next, if eligibility is determined, within 30 days they will receive “a list of three to five families of patents”, from which they can make their selection. Still, Google “will retain a broad, nonexclusive license to all divested assets”, as these patents might still be important to the company.

For those startups that apply and are determined to be ineligible, Google will nonetheless provide them with access “to its own database of patents”. These are presumed to alas be categorized as “non-organic”. The unselected startups will be able to ask Google to consider “the potential purchase of any such assets”.

Back in April, when Google began their acquisitions of patents, they were approached by many operating companies and patent brokers. Both types of entities told Mr. Brasch about a “problem in the secondary market“. These businesses were looking for an alternative means to sell their patents to Google and Mr. Brasch was seeking a means to assist interested buyers and sellers.

Google eventually purchased 28% of the patents they were offered that the company felt could potentially be used in their own operations. As these patents were added to Google’s patent portfolio, a portion of them were categorized as “non-organic” and, as such, the company is now seeking to give them away.

Both sides of Google’s latest patent initiative demonstrate two important strategic points as the company is now:

  • Taking more action in enabling other tech firms to provide assistance against litigation brought by troll-driven lawsuits.
  • Presenting the company as a comprehensive “broker and portal” for patents matters.

Last week, as another part of this process, Google substantially upgraded the features on its Google Patents Search. This included the addition of search results from both Google Scholar and Google Prior Art Finder.  (For the full details and insights on the changes to these services see Google’s New, Simplified Patent Search Now Integrates Prior Art And Google Scholar, also by Ingrid Lunden, posted on TechCrunch.com on July 16, 2015.)

While both the purchasing and selling operations of Google’s effort to test new approaches to the dynamics of the patent marketplace appear to be limited, they might become more permanent later on depending on the  results achieved. Mr. Brasch also anticipates continuing development of this patent market going forward either from his company or a larger “group of organizations”.  Just as Google has moved into other commercial sector including, among others, “shopping, travel and media”, so too does he expect the appearance of more new and comparable marketplaces.

My own questions are as follows:

  • In addition to opposing patent troll litigation, what other policy, public relations, technical and economic benefits does Google get from their new testbed of marketplace services?
  • What other industries would benefit from Google’s new marketplace? What about pharmaceuticals and medical devices, materials science (see these four recent Subway Fold posts in this category),  and/or automotive and aerospace?
  • Should Google limit this project only to startups? Would they consider a more expansive multi-tiered approach to include different ranges of yearly revenue? If so, how might the selection of patents to be offered and other eligibility requirements be decided?
  • Might there be some instances where Google and perhaps other companies would consider giving away non-organic patents to the public domain and allowing further implementation and development of them to operate on an open source basis? (These 10 Subway Fold posts have variously touched upon open source projects and methods.)

Recent Visualization Projects Involving US Law and The Supreme Court

"Copyright Sign in 3D", Image by Muses Touch

“Copyright Sign in 3D”, Image by Muses Touch

There have been many efforts over the past few decades to use visualization methods and technologies to create graphical representations of the law. These have been undertaken by innovative lawyers in diversity of settings including public and private practice, and in legal academia.

I wrote an article about this topic years ago entitled “Graphics and Visualization: Drawing on All Your Resources”, in the August 25, 1992* edition of the New York Law Journal. (No link is currently available.) Not to paint with too broad a brush here, but things have changed dramatically since then in terms of how and why to create compelling legal visualizations.

Two very interesting projects have recently gotten significant notice online for their ingenuity and the deeper levels of understanding they have facilitated.

First are the legal visualizations of Harry Surden. He is a professor at the University of Colorado School of Law. He teaches, researches and writes about intellectual property law, legal informatics, legal automation and information privacy.

I had the opportunity to hear the professor speak at the Reinvent Law NYC program held in New York in February 2014. This was a memorable one-day event with about 40 speakers who captivated the audience with their presentations about the multitude of ways that technology is dramatically changing the contemporary marketplace for legal services.

On Professor Surden’s blog, he has recently posted the following three data visualization projects he built himself:

  • US Code Explorer 1 consisting of a nested tree structure for Title 35 of the US Code covering patents. Clicking on each levels starting with Part I and continuing through V will, in turn, open up to the Chapters, Sections and Subsections. This is an immediately accessible interactive means to unfold Title 35’s structure.
  • US Code Explorer 2 Force Directed Graph presents a different form of visualization for Title 17 of the US Code covering Trademarks. It operates as a series of clickable hub-and-spoke formations of the Code’s text whereby clicking on any of the hubs will lead you to the many different sections of Title 17.
  • US Constitution Explorer is also presented in a nested tree structure of the Constitution. Clicking on any of the Articles will open the Sections and then the actual text.

Professor Surden’s visualizations are instantly and intuitively navigable as soon as you view them. As a result, you will immediately be drawn into exploring them. For legal professionals and the public alike, he impressively presents these displays in a clear manner that belies the complexities of the underlying laws. I highly recommend clicking through to check out and navigate all of these imaginative visualizations. Furthermore, I hope his work inspires others to experiment with additional forms of visualization of the other federal, state and local codes, laws and regulations.

For a related visualization of the networks of law professors on Twitter, please see the February 5, 2015 Subway Fold post entitled Visualization, Interpretation and Inspiration from Mapping Twitter Networks.

The second new study containing numerous graphics and charts is entitled A Quantitative Analysis of the Writing Style of the U.S. Supreme Court, by Keith Carlson, Michael A. Livermore, and Daniel Rockmore, Dated March 11, 2015. This will be published later in Washington University Law Review 93:6 (2016). The story was reported in the May 4, 2015 edition of The New York Times entitled Justices’ Opinions Grow in Size, Accessibility and Testiness, Study Finds, by Adam Liptak. This article focused upon the three main conclusions stated in the title. I highly recommend click-throughs to read both.

The full-text of the Law Review article contains the very engaging details and methodologies employed. Moreover, it demonstrates the incredible amount of analytical work the authors spent to arrive at their findings. Just as one example, please have a look at the network visualization on Page 29 entitled Figure 5. LANS Graph of Stylistic Similarity Between Justices. It truly brings the author’s efforts to life. I believe this article is a very instructive, well, case where the graphics and text skillfully elevate each other’s effectiveness.


To get online then you needed something called a Lynx browser that only displayed text after you connected with a very zippy 14.4K dial-up modem. What fun it was back then! 

New Analytics Process Uses Patent Data to Predict Advancements in Specific Technologies

"Crystal Ball", Image by Christian Schnettelker

“Crystal Ball”, Image by Christian Schnettelker

John Oliver did a brilliant and hilarious takedown of patent trolls on his April 19, 2015 edition of his Last Week Tonight show. He raved about the absurdity of such companies who buy up patents and yet produce nothing much themselves other than lawsuits to enforce theses patents. As he said, this is a form of “extortion” that impedes progress and ends up costing the defendants in these actions a great deal of money. If you did not see the show or have not seen the video yet, please have a look and a laugh.

Then compare and contrast that economic fear and needless cost of using patent data in such a negative manner with the publication of a paper last week about how US patent filings are now being used in an entirely opposite, innovative and productive manner. The contrast could not be more dramatic. Indeed, as presented in a new paper published online on April 15, 2015 on PLoS One entitled Quantitative Determination of Technological Improvement from Patent Data, by MIT researchers Christopher L. Benson and Christopher L. Magee, mining recent filings in the US Patent and Trademark Office’s (USPTO) massive database using their new methodology, can determine which technologies are genuinely advancing and at what relative rate.

This very exciting news was reported and analyzed in an article posted on Phys.org on April 15, 2015 entitled New Method Uses Patent Data to Estimate a Technology’s Future Rate of Improvement. I will sum up, annotate and add a few questions to this. I highly recommend clicking through on both this article for the details of how this prediction tool was developed and the full-text of the PLoS One paper for the granular details of how it actually works.

(For cross-reference purposes, this advancement follows on and partially mixes together the topics of two previous Subway Fold posts, one on April 9, 2014 entitled Comprehensive Visualization of Future Paths of Technological Innovations and another on August 8, 2014 entitled New Visualization Service for US Patent and Trademark Data.)

Benson and Magee have devised an analytical means to sift through the USPTO database for precisely choosing the latest patents that “best represent” 28 specific technological domains. These include, among others,  “solar photovoltaics, 3-D printing, fuel-cell technology, and genome sequencing”. Then, applying their methodology, based upon the number of subsequent citations in other new patent filings, they were able to determine those some of the relevant patents displayed an increased likelihood in predicting “a technology’s improvement rate”. In effect, the higher the rate of subsequent citation of Patent X, the higher the rate of innovation. The equations in their predictive tool also include some other patent characteristics.

Among the 28 technologies, those showing the highest rates of advancement were “optical¹ and wireless communications, 3-D printing, and MRI technology²“, while others with slower rates of advance included “batteries, wind turbines, and combustion engines”.

Benson believes that his prediction method could possibly be useful to venture capitalists, startups³. Magee hopes that it may be applied as a form of “rating system” for investors searching out potential “breakthroughs”. Both developers also foresee the possibility that public and private laboratories could use it to investigate potential new areas for research. Furthermore, Magee believes that their approach can be applied to lower the level of uncertainty about the future of a particular technology to “a more manageable number”.

My questions are as follows:

  • Would the accuracy of the predictions from this new system be enhanced by applying its underlying equations to add in other data sources such as online news, social media mentions, and citations to other relevant industry news publications? (X-ref to the December 2, 2014 Subway Fold post entitled Startup is Visualizing and Interpreting Massive Quantities of Daily Online News Content.)
  • Could the underlying equations be applied to other fields such as law to predict the possible outcomes of cases based upon the densities and propensities of cases cited in similar matters and jurisdictions? What about possible applications in medical research or the financial markets?
  • Can levels of probability be quantified with this new system? For example, can it derive a 70% probability that driverless cars will continue to gather technological momentum and then commercially succeed in the marketplace? If so, how might such probabilities be used by the public, governments, researchers and investors?

 


1Could references to patents for optical technologies also be considered, well, cites for sore eyes?

2.  X-ref a September 3, 2014 Subway Fold post entitled Applying MRI Technology to Determine the Effects of Movies and Music on Our Brains.

3.  There are currently 22 Subway Fold posts on a broad range of startups in many industries.

 

Is Big Data Calling and Calculating the Tune in Today’s Global Music Market?

music-159870_1280-1The extraordinary degree to which big data apps and analytical services are now affecting the marketing, economics, talent development and the popularity of new tunes, has just been thoroughly and expertly explored in an article in the November 2014 issue of The Atlantic entitled The Shazam Effect, by Derek Thompson. This report covers this phenomenon across a multitude of musical genres and commercial venues. I highly recommend checking out this piece in its entirety for a true sense of this ongoing revolution in terms of the leading participants and the fascinating issues concerning business and creativity.

The following is my own summary, annotations and commentary upon just some of the key – – forgive me – – players, market data and open issues worth, well, noting.

I.  Today’s Key Music Business Data Players:

  • Shazam on its surface is an app that helps users to identify a particular song or melody. To date, it have been downloaded half a billion times and is searched 20 million times each day. It can identify emerging songs with breakout potential months in advance. While users enjoy its ability to readily identify a song, the music industry engage it as and early radar array. As well, it assists in identify unknown performers for talent scouts and agents.
  • Pandora and Spotify data sets are used by concert promoters and performers to shape touring venues and set lists. (X-ref to this August 14, 2014 Subway Fold post entitled Spotify Enhances Playlist Recommendations Processing with “Deep Learning” Technology.) One of Pandor’s executives, Eric Bieschke,  is quoted that his online service is not driven by a singular algorithm, but rather “a meta-algorithm that directs all of the other algorithms” to enable users to select songs and artists from the vast  troves of music across the Web.
  • Next Big Sound is a dedicated music analytics firm that gathers, blends and assesses relevant data streams from Spotify, Instagram and other online sources. In turn it sifts through this to identify 100 possible music stars to emerge during the next year. They are currently achieving a success rate of twenty percent. The company also offers a subscription based customizable search tool called “Find”  that will gather and assess selected data flows from Twitter, Facebook and other social platforms. They have found performers’ Wikipedia pages to be valuable predictors.
  • iHeartMedia (previously known as Clear Channel¹) uses Shazam to gauge the virality of new songs and Nielsen Audio deployment of tech called Portable People Meters to track individuals’ radio listening, (X-ref to this July 31, 2014 Subway Fold post about Nielsen’s data and analytics work entitled New Analytical Twitter Traffic Report on US TV Shows During the 2013 – 2014 Season.) HitPredictor, a subsidiary of iHeartRadio, accurately forecasts hits prior to their release by playing them for a large online test audience in order to solicit their feedback.
  • Billboard Top 100 (BT100) combines point-of-sales sales data, download music numbers and Nielsen’s listening metrics. One result is that songs remain on the BT100 longer. As a result of this “the relative value of a hot has exploded”. Thus, the top 1% of recording artists earn 77% of all recorded music sales, while the top 10 selling songs have increased their capture of the market by 82% during the last decade. This is indeed a market where the revenue rich continue to get richer revenues.

II. Current Market Influences and Trends:

  • Wisdom of the Crowds:  Before the advent of big data, music company execs largely relied on their own instincts in choosing artists and products to promote. Now with the advent of these sophisticated apps and services, they are relying on upon a group f principles known as the wisdom of the crowds². Very simply stated, large and diverse groups of people, such as the web-wide millions using these services, is more likely to make more accurate decisions and forecasts than smaller groups and/or experts in the relevant field(s).
  • The Long Tail Effect:  As noted above, there is an intense and very small concentration among artists for whom big data and analytics is producing economic rewards.³
  • Social Media:  Some, but not all to the same degree, of these platforms are now the major drivers in marketing new artists and their new music. They might even be more influential than the tradition of drawing audiences to live concerts.
  • Radio Airplay:  This mainstream media, while maintaining its ongoing relevance in the music business, likewise replies just as heavily on all of the social media and data analytics in order to “connect all these dots”. The Wisdom of the Crowds also plays an integral part of radio programming.*
  • Overproduction of Repetitive and Bland Music:  Music industry people whom Thompson approached for this article expressed concern that the data-driven nature of today’s market is producing a “clustering” of music in different genres and, in turn, noticeable levels of sameness and copycat acts. Nonetheless, he further writes that research shows that listeners very often seek out familiar music they have heard many times before.
  • Effects Upon Musical Artists: Notwithstanding the prior point, musicians and composers are aware of this phenomenon but generally have limited its effects upon their creative output. As well, some will add variations and imperfections to their live performances in order to keep them sounding fresh. (X-ref to this August 11, 2014 Subway Fold Post entitled The Spirit of Rock and Roll Lives on Little Steven’s Underground Garage about how, among other things, this is one of the basic tenets of  Garage Rock.)

III. Ongoing Issues:

  • At the very heart of all of this activity is, as precisely framed by Thompson “What do people want to hear next?”
  • While the music business is significantly benefiting from the accuracy of all of this data and calculation, is it likewise producing “better”, more diverse and imaginative music for audiences to consume?

My own additional questions include:

  • Despite the Long Tail effect, are artists is the much longer end of the curve still accruing some demonstrable benefits from big data insofar are being heard by larger audiences online and in concert?
  • Based upon the monumental amounts of past, present and future data about music and the music industry, could deep learning and other artificial intelligence (AI) methods be used to produce genuine hit songs in multiple genres, without any human intervention? Alternatively, is the human touch always needed in the musical arts? If the answer ever turns out to be “not always”, what are the implications?
  • Could analytics and AI produce a new genre of music that is not necessarily a hybrid? That is, are there sounds, rhythms, arrangements, styles, tablatures and so on that have not yet emerged and can be entirely machine synthesized?
  • The article mentions that Led Zeppelin’s iconic Stairway to Heaven was never played much after its initial release and that it never landed on the BT100. As an experiment to test the validity and accuracy of today’s music data apps and services, what would happen if many such great hit were retroactively tested? Would any be proven to be hits that never should have occurred according to today’s tech and, conversely, are there obscure songs from years ago that would produce results indicating they should have been hits? Could or even should, such results be used to further fine tune, if not develop new musical data methods and metrics?
  • What other new opportunities will arise, based on this merger or art and science, for entrepreneurs, artists, talent scouts and agents, established music companies, and concert halls?

December 19, 2014 Update: 

Adding to the big data strategies and implementations for three more major music companies and their rosters of artists was a very informative report in the December 15, 2014 edition of The Wall Street Journal by Hannah Karp entitled Music Business Plays to Big Data’s Beat. (A subscription for the full text required a subscription to WSJonline.com, but the story also appeared in full on Nasdaq.com clickable here.) As described in detail in this report, Universal Music, Warner Music, and Sony Music have all created sophisticated systems to parse numerous data sources and apply customized analytics for planning and executing marketing campaigns.

Next for an alternative and somewhat retro approach, a veteran music retailer named Sal Nunziato wrote a piece on the Op Ed page of The New York Times on the very same day entitled Elegy for the ‘Suits’. He blamed the Internet more than the music labels for the current state of music where “anyone with a computer, a kazoo and an untuned guitar” can release their music  online regardless of its quality. Thus, the ‘suits’ he nostalgically misses were the music company execs who exerted  more controlled upon the quantity and quality of music available to the public.

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1Right Off the Dial  (Faber & Faber, 2009), by Alec Foege, chronicled the causes and effects of the company’s rapid rise in the commercial radio industry. I found this to be an eye-opening and very informative account of rapid consolidation within a specific sector of the mainstream media. I recommend it to anyone interested in this company and topic.

2.  For a well reviewed and highly readable treatise on this, I also very highly recommend The Wisdom of
the Crowds by James Surowiecki (Doubleday, 2004). Also here is a Wikipedia page summarizing some of the main points of the book.

3.  The definitive and superlative book on one of the most interesting outgrowths of online commerce is The Long Tail by Chris Anderson (Hyperion, 2006). Furthermore, I also highly recommend his incredibly diverse and entertaining show on NPR called Studio 360.

*  I still that think Bruce Springsteen’s take on the state of music radio in 2007, Radio Nowhere, deserves a click and listening here. Besides, it’s an exhilarating rocker.

 

New Visualization Service for US Patent and Trademark Data

A new startup call Trea has just launched a new visualization tool that establishes a dynamic user interface to all of the patent data available on the US Patent and Trademark Office’s (USPTO) massive public database. The full details of this appeared in a July 30, 2014 report on Gigaom.com entitled Powerful New Patent Service Shows Every US Invention, and a New View of R&D Relationships.

Trea’s UI not only illustrates whom is patenting what, but also types of fields (for example, data processing, telecom, chips, and so on). It is expected to be useful to inventors, corporate competitors, investors, journalists, academics, and I would also venture to say lawyers specializing in intellectual property practice.

The features described in this article along with accompanying screen captures include:

  • A “unified knowledge graph”, a networking representation of relationships between and among inventors.
  • A means to further zoom in on a single inventor and his or her collaborators.
  • A “notary feature” that permits inventors to encrypt and submit “diagrams and ideas” and receive a time-stamped receipt.

I suggest a full read of this story for the details of Trea’s business plans and the sampling of three highly informative graphics their product generates.

The visualization of government data sets continues to draw the interest of such entrepreneurs. Just to provide an initial sense of the breadth of governmental data available for these efforts, have a look at the categories and the data sets made publicly available by the US government can be viewed and downloaded at Data.gov. Similar data sets are available elsewhere online on the state and local levels across the U.S.

Furthermore, I once again recommend reading Smart Cities by Anthony Townsend as I wrote about in my April 9, 2014 post about the developers involved in transforming the availability and analytics of civic data.