Apple and Personality-Based Marketing/Publicity in the Music Space

Apple Computer Logo
By Apple, Inc. [Public domain], via Wikimedia Commons

I was on Facebook earlier today and came across the comment below from Tim Quirk. It’s apparently about Apple’s new streaming music service, which is slated to launch later this year. Tim’s a musician and has also spent time working at Rhapsody and Google Music, amongst other places.

WHO’s telling you to listen is far, far less important than WHAT they tell you to listen to. Also, GETTING you to actually listen.

Reading the comments underneath Tim’s post, I came to understand that it related to his criticism of what he asserted was the personality-based approach that Apple seems to be using with its new service.

One commenter, Jamie Dolling, asserted that the new service was as much about “personality as it is about music,” and worried that this approach couldn’t help but “poison the water.”

Subsequently, Jon Maples, a digital music consultant formerly of Rhapsody, indicated that it was the same..old…’human music curation’ approach without any understanding of what the listener actually wants.”

I started adding my own comment on that post, but as its length ballooned it seemed to be morphing into a blog post. So I moved over here.

Anyway, here’s my take on this stuff.

As Tim correctly points out, getting listeners to break out of their default is the challenge, because most listeners just want to keep listening to the stuff they are already familiar with (and consume the same products over and over again as well).

To my mind, personality-based approaches to marketing and publicity can be one way to accomplish that goal. Even if there’s an element of bullshit, snake oil to it, they wouldn’t still be using it if personality-based publicity and marketing didn’t sell shit.

For many people, who is telling you to listen/buy is inextricably bound up in what they are telling you to consume. That’s the whole point. It’s a gestalt experience.

The further you move to the right in the diffusion curve on anything new, the less likely consumers are to use their own research and judgment when making buying decisions. These people are much more likely to look to trusted people (opinion leaders) for signals about what choices to make.

This is not a new thing. It’s as old as consumer capitalism (or actually even older still). And while I pride myself on doing my own research on lots of stuff and making my own decisions, there’s lots of other stuff where I just don’t care enough to do that. I want somebody else to point me to an answer that is good enough (or better still, great). The whole point of doing that is that I don’t know what good is, so I can’t really effectively evaluate the quality of the thing being recommended. If I could, I wouldn’t need somebody else’s advice.

So the personality/trustworthiness of the person making the recommendation is extremely important. It becomes a proxy for the knowledge I lack about the thing being recommended, because, rightly or wrongly, I do feel comfortable evaluating what I think about the person doing the recommending.

The logic goes something like this. I don’t trust my judgment about what cool clothes are. This person over there seems to be a person who I think is cool and has on cool clothes (or at least a person who I understand from their reputation is supposed to be cool and wearing cool clothes). Therefore, their judgment about cool clothes is probably better than mine. So I’ll see what they think I should wear, and moving forward I’ll look to them for more clues and cues on that subject.

Unlike data driven metrics, this isn’t just about figuring out what I want. It can also be about creating a new want, because while I may know what I think I want, I may not actually know what I want all the time. Data driven metrics may do a good job of figuring out what I think I want right now or even what I might want based on what I have wanted in the past, but they don’t do such a good job of determining what I don’t know that I want right now but what I might nevertheless want in the future if it was put in front of me in the right way. The right sort of charismatic curator/opinion leader has the ability to do that.

For many people, music is something they are unsure about. It’s also something where they don’t want to have to filter through all the noise to get to the signal. They like having music around. They also know that what music they like says something about them, so there’s something at stake there beyond just the hedonistic experience of consuming the music.

But in many cases, they just want to be pointed towards some good stuff. If liking this good stuff also seems to help make them seem a little bit less uncool, well, even better. Because in 2015, nobody wants to seem uncool, not even middle-aged people like me. Indeed, seeming/feeling less uncool may be just as important–or even more important–than liking what has been recommended.

So yes, Apple’s new music service is a publicity/marketing platform. And yes it appears to be personality-based. That’s because the biggest objection that the music industry seems to have about many of the other streaming platforms is this:

They may deliver a good user experience to certain users, but despite many assertions to the contrary, they have not yet proven themselves to be particularly good marketing/publicity platforms for companies trying to focus demand on a limited slate of new releases (the only way to generate the kind of cash they need to stay in business long-term). They can service demand when it arises. But they don’t drive demand or significantly shape it.

Moreover, to the extent that these services create new wants in people, the want pattern is much more diffuse than in the old system. So the old-line music industry is still trying to find a marketing/publicity platform that looks and works more like terrestrial radio did in the glory days, because that was a great platform for focusing demand on a limited slate of new releases. It had a focused want pattern.

It’s a fair criticism to say that trying to find that sort of platform is a pipe dream. That we’re in a new reality now, and the desire for that sort of platform reflects an unwillingness to get with the times. But there remain very practical reasons why that sort of platform would still be useful to the music business. So it makes a certain amount of sense that its members continue to chase it.

Apple seems to be taking a stab at trying to provide that sort of platform with a more personality-based approach. But just because Apple may, in part, be trying to solve a problem for the music industry, that doesn’t mean their solution is inherently at odds with the user/audience.

After all, terrestrial radio has often been a personality-based marketing/publicity platform both for labels and all the advertisers that subsidize it. But it’s also beloved by many users, because they value both the curation and the personalities they find there. Often, those things cannot be separated.

That doesn’t mean that human curation is always good. Indeed, on average, algorithmic approaches may now be better at delivering a good-enough experience that is more personalized than the average human curation experience.

But when human curation is good, I think it remains the gold standard for curation, even when it is less personalized. Maybe I’m showing my middle-age here, but that’s how it seems to me. That sort of curation is inherently personality-based. That’s a big part of its appeal. You trust the curator enough to give up control and let them take you on a journey of discovery.

In the process, you bond with them, for being associated with a cool personality has the capacity to make you feel cooler and a part of the world they have created around their personality. That experience creates a want in you.

An algorithm rarely makes you feel cooler like this, because it’s a tool. You might use it for the purpose of doing your own research and discovery.  It might even show you some things about yourself that neither you nor other people readily see. That, in turn, might allow you to feel cooler when you deal with other people, because of the knowledge you’ve gained. But even when the algorithm is doing a good job delivering quality suggestions to you, it still makes you feel a little bit more like a data point and less like a human.

A friend of mine recently started a Spotify mix-tape group on FB. Each week a different member delivers a 90 minute playlist to the group (a virtual mix tape). So far, this experience has been infinitely better than any algorithmic experience I’ve ever had, because each group member actually takes into account what other people have done and who the audience is.

So if somebody included a track last week, that track isn’t likely to be in this week’s mix and more than likely neither would that artist. Although if it made aesthetic sense in the context of the mix to include the same artist or track two weeks in a row, maybe it would be in there anyway. But in any case, these mixes have a much richer sense of the many contextual factors that contribute to creating a good mix. The same is true of a great show on a non-comm radio station like KEXP. As a result of this, these kinds of mixes reinforce a sense that the group members are part of something bigger than themselves.

Of course, if that mix tape group was me and 25 kids who are under 15, the quality of the curation probably wouldn’t seem as good to me, although I’d probably still hear an occasional great tune I would have missed otherwise. I’d also feel more like an interloper in that group. Maybe that distinction is actually demographic rather than personality-based. But to me, issues of demographics and psychographics are embedded in the idea of personality-based branding. You are buying the gestalt experience that you associate with that person or company.

This is why an anonymous human curator is less valuable than a curator with a personality/reputation that is known and trusted by users, even if the choices of the anonymous curator are objectively just as good as or better than those of the known curator. The lack of an identifiable personality makes it harder to evaluate the utility of the suggestions. And once you’re dealing with that problem, you’re pretty much right back where you started. The curator is no longer solving a problem for you. Now, you need a curator to sort out the anonymous curators for you.

Don’t get me wrong, it’s not that I don’t use algorithmic radio ever. I do. A group of my college friends made a playlist that encompasses many of the songs that were on the jukebox in the coffee house that was in the basement of our dorm at the University of Michigan (the Halfway Inn). Spotify generated a radio station based on that playlist, and it works pretty well, although it still does a poor job of managing repeats of the same song and multiple related songs by the same artist or by related artists (e.g,. Velvet Underground and solo Lou Reed).

A good human curator does not do these things. That’s part of the artistry. They take those things into account. Like I said above, they have a better and richer contextual awareness. Also, part of the reason that particular Spotify station works as well as it does is because it’s based on a playlist that was human curated. So it’s bootstrapping on the contextual awareness of the people who compiled that list.

If enough people trust a guy like Zane Lowe, some of that is his personality. But his personality and that trust is also a function of his talent for curation.

Grunge/Alternative rock broke on commercial radio back in the ’90s in no small part because of Seattle DJ Marco Collins. The relationship that people had with Marco at that time was very much personality driven. They liked him. He was a dynamic on-air personality, and they thought he was cool. But a big part of the reason why was that they came to trust his taste.

If Marco said something was cool and played it on the radio, people gave it the extra listens they needed to appreciate why it was worthwhile, even when their first impression might not have been great. Twenty years later, his impact is clear enough that somebody recently made a movie about him.

Some people have that intuitive gift for knowing what new stuff people will like if they just give it a chance. Computers are also getting better and better at deducing that information based on prior user behavior. But I’m still not sure those two approaches always lead you to the same place.

What’s that term? “Filter Bubble,” where your perceived options keep getting smaller and smaller as the search algorithm feeds back based on your previous choices. At its best, human curation seems less prone to the filter bubble (although it has its own problems and risks–e.g., it’s probably more prone to personal politics and lobbying, which can create a bureaucratic capture problem that undermines trust–See e.g., payola). But human curation only works if people trust the human curators and don’t have to invest too much energy vetting them.

Apple is a high profit-margin, gold standard brand. That’s why people pay extra for it. Its whole message is grace, ease of use, and quality (even if these things are not always actually true). Historically, it’s been about finding the spot where technology and people align. You know, a mix of art and science.

That’s the value proposition it is selling. The personalities are at least theoretically in the service of that. They are supposed to be part of the art that interfaces with the science and tech.

Part of the art is also the fashion sensibility. Undoubtedly, that’s part of what must have attracted Apple to Beats. I have mixed feelings about that. My feathers get ruffled thinking about paying hundreds of dollars for a pair of headphones that may be fashionable but ultimately aren’t very good sounding headphones for the money.

But at the end of the day, I guess I’m a bit of an engineer at heart. I value function over fashion, and I especially hate the idea of paying a premium for something just because it is perceived as being fashionable. Nevertheless, I also recognize that many people are not like that, and that these kind of people are more than willing to pay a premium for something they perceive as fashionable. Indeed, in many cases they are the highest margin consumers.

The personality-based approach also dove-tails with Apple’s history and culture. Before the death of Steve Jobs, it was a personality driven company. It’s also an opinion leader brand. So while it collects plenty of experience data from users, it has not historically solicited explicit input from the public about what it wants. It doesn’t have the same sort of beta-testing developer blogging, two-way conversation that many other companies have as they develop their products.

I once had conversation with a Boeing IT guy in a bar here in Seattle. He said they loved Microsoft, because they were much more open with his department about what they were working on and where it was going.

Typically, Apple hasn’t shared where it’s going until it releases a product for the public to see. It’s not looking for that sort of approval and feedback. When it releases something, the message is this: “Here’s our new thing. We’re cool. We think our thing is cool, and if you try it, we’re confident that you will think our thing is cool too, even if you don’t understand right this minute why it’s cool.”

Over the last decade, it’s had a pretty good track record doing that. So even when it does something that other people have arguably already done, it typically re-contextualizes it in a way that makes it sit differently with the public

We’ll see if Apple’s new music service provides that sort of bold leadership and delivers on the idea that theirs is a place where art does a better job meeting science than at other places. We’ll also have to wait and see whether their approach resonates in the market.

If it just ends up being a re-branding of the Beats music service, then I think the answer will be “no.” While there was nothing really wrong with Beats and it looked cool, at the end of the day, I didn’t find it qualitatively different from its competitors, either in terms of user experience or curation.

So to succeed, imho, Apple will need to extend things considerably on the personality front and keep their curated playlists and other personality-based offerings far more dynamic than they were on the old Beats service. Otherwise, it’s just the same wine in a different bottle.

 

 

Now I get it: Self-Driving Cars are the Spotify of Auto Travel

I just read a pretty useful article on the Vox site about self-driving cars. It could turn out to be wrong in many ways, but a few things clicked for me after reading it, like a better understanding of why Apple or Google might want to get involved in the automobile space, and why their expertise might make sense there too.

Picture of a Google Self-Driving Car
By Steve Jurvetson [CC BY 2.0 (http://creativecommons.org/licenses/by/2.0)], via Wikimedia Commons
I’m not a huge fan of Uber for a variety of reasons, but if you think about Uber-like companies deploying driver-less cars on a broad scale, that would mean a huge shift in the role of cars in our society and how we interact with them.

It’s a move from car as a widget that a car company sells you to car as a service to which a service provider sells you access. Repairs? That’s their problem. Gas or electricity? It’s baked into the price. Parking? Don’t need as much of it, because like a taxi, these cars don’t sit still most of the time. They move on to a new user who needs a ride. So those are some potentially cool features. On the other hand, if you want to jump in the car on two minutes notice and go somewhere, well, that may not always work so well.

At the end of the day, a self-driving car service like that would be very similar to a service like Spotify in the music space (or Netflix in the movie space). Instead of buying the hard product CD or DVD widget, people buy the right to access the same music or video from the service provider.

We’ll see how it all plays out, and I’m not sure if I’m totally sanguine about that outcome, particularly if Uber is a big player. But it is interesting to see how the success of services like Spotify, Netflix, and Office 365 have started to expand the adjacent possible of this sort of business model outside of the realm of intangibles, like digital music files, and into the realm of large tangible things, like cars.

Obviously, technological changes are driving some of this shift. But to a certain extent, it’s also about changing people’s cultural expectations around the value of “ownership” of a thing vs. access to the service that the thing has historically provided to us.

In the final analysis, the project of 20th-century, consumer capitalism was about extending the possibility of widget ownership as broadly and as deeply as possible. But as the Internet continues to link more and more people and information together, it’s those intangible linkages that provide much of the innovation and the power, rather than the widgets themselves, which are much more conduits for those linkages (i.e., more commoditized).

So more of the value is in the service itself rather than in the widget that delivers the service. And particularly if the service is delivered via centralized cloud servers, it’s much easier for a service provider to control access to the underlying service. As a result, digital piracy is much harder for the average user to accomplish. It also makes it easier for the service provider to roll out updates and security fixes. On the other hand, individual privacy rights may suffer when everybody’s information lives on a central server (self-driving cars would be no different–it would be much easier to track people’s movements if most travel happened in self-driving cars).

That doesn’t mean there is no money to be made making and selling certain classes of widgets (e.g. smartphones), but as more and more classes of activities are being mediated through the same widget, the markets for a lot special-purpose widgets have started going by the wayside.

We’ve already seen that process starting to play out in the context of things like music, books, and movies. But if it continues into things like cars, that’s going to mean some disruptive long-term changes that dwarf anything we’ve experienced thus far. It’s not quite the Jetsons. But it’s getting closer.

Anyway, nothing really profound in this post. Just some quick thoughts that came clearer for me. So apologies in advance if this is some Captain Obvious stuff.

Update:

A friend asked me the following question today after reading this post:

What about taxis? Don’t they already provide the service-based model for auto travel I’m talking about above?

Of course, the answer is “yes,” up to a point. With a taxi, you are buying the service instead of the vehicle, but the proliferation of the taxi is far more limited than the proliferation I imagine if the driver-less car were to really take-off. At best, at least in most American cities and towns, Taxi service is currently an adjunct to private cars and transit.

The networked nature of the driver-less car also makes it more easy to imagine the viability of a subscription plan for driver-less car service rather than the metered fee-for-service approach of taxis. This is what would make such a service the Spotify of auto travel, either a capped or all-you-can eat subscription within a given geographic area.

In this regard, the driver-less car might be more like public transit, where you buy a monthly pass. Indeed, it might work as a sort of compliment to public transit, ferrying people to and from trunk lines where it’s not efficient for them to provide service. This would mean less space needed for parking and less traffic on the roads, particularly if there was a way for multiple people to easily arrange to share a driver-less car to a shared destination (or where it’s efficient to hit contiguous destinations in the same trip).

 

Five Reasons The Music Industry Hates Pandora The Most

pandorahate

Note 1: I’ve been chipping away at this post for about eight twelve months off and on. I finally managed to bring it in for a landing yesterday night. File it under #slowblogging and #longreads.

Sam Lefebvre’s recent cover story on Pandora in the East Bay Express overlaps some of what I discuss here, and it’s well worth reading. That said, as our respective focuses aren’t the same in every regard, I’m hopeful that this post will serve as a useful compliment to Lefebrvre’s piece.

Note 2: This post was updated on December 8, 2014 with a bit of new content based on some comments I received when it first went up. I expect there will probably be more substantive updates as time goes by, and if that happens, I’ll let you know right here.

Note 3If you’d rather read this post off-line, feel free to download a copy of it in pdf, MOBI, or EPUB format. Apologies in advance for any formatting anomalies. I’m not yet a wizard at doing ebook format conversions.

***

Of all the dedicated digital music streaming services to come on-line since 2000, none has drawn the ire of the music industry quite like Pandora.

On its face, this may seem peculiar. After all, Pandora is a legal, royalty paying service. It has passed 250 million registered users in the U.S. Moreover, despite loud protestations to the contrary, there’s a credible argument to be made that, on a per listener basis, Pandora actually pays more royalties per spin to both songwriters and master rights-holders than does terrestrial radio.

So shouldn’t Pandora be a win for record labels and music publishers? Aren’t they being irrational in hating Pandora more than all the other services?

Succinctly, no. Pandora has been more disruptive of established music industry practices than any other major legal streaming music service. So the music industry has some very real reasons–both financial and aesthetic–to hate Pandora.

This post is a deep dive into five of those reasons. I’ve tried to keep my thoughts in plain English. But fair warning: I do get into some technical legal stuff towards the end. You can’t grasp the full picture without it. Continue reading “Five Reasons The Music Industry Hates Pandora The Most”

Recap: the Beastie Boys Vs. GoldieBlox–A Drama in Four Acts

Back in March, the Verge reported that the Beastie Boys had settled their lawsuit against educational toy company GoldieBlox. That suit alleged copyright infringement, trademark infringement, false advertising, false endorsement, and unfair competition, stemming from GoldieBlox’s unauthorized use of the band’s song “Girls” in the company’s popular Internet promotional video.[no_toc]

Photo by Masao Nakagami

According to the Verge, “[a]s part of the settlement, GoldieBlox will no longer be able to use its parody of the Beastie Boys song “Girls” and will publish an apology to the band…The toy maker will also make a donation based on a percentage of its revenues to a charity selected by the Beastie Boys that supports science, technology, engineering, and mathematics education for girls — the very subjects that GoldieBlox’s toy lines try to promote.”

Until recently, the specific amount of GoldieBlox’s donation was unknown. But on May 12, 2014, Digital Music News reported that the amount of the donation had recently been detailed in court filings from the Beastie Boys’ copyright infringement lawsuit against Monster Energy drink: To compensate for its unauthorized use of “Girls,” Goldieblox will donate 1 percent of its gross revenue to the Beastie Boys’ specified charity until it has paid a total of $1 million.

With this final piece of the puzzle in hand, now seems like a good time to offer a little recap commentary on the GoldieBlox drama, highlighting a couple of the important story lines and the lessons they offer for content users and content owners.

So I give you the Beastie Boys vs. GoldieBlox–A Drama in Four Acts. Continue reading “Recap: the Beastie Boys Vs. GoldieBlox–A Drama in Four Acts”

Trichordist Claims 45% Drop in Working Musicians. BLS Data Tells a more Complicated Story.

Please Note: An earlier version of this post attributed the blog post discussed below to David Lowery. Subsequently, I have learned that Lowery is not the author of this post. I have revised this piece to remove references to David Lowery, and I sincerely apologize to Mr. Lowery for any misunderstanding.

A recent post on the Trichordist quoted data from the Bureau of Labor and Statistics (BLS) indicating that the number of working musicians has decreased by 45% since 2002. It included the following graphic to illustrate this point:

The Trichordist’s statistics seemed shocking. Could they really be right?

An employment drop of 45% in a ten year period is pretty extreme, even given the current state of the music business. Therefore, I thought it might be worth a visit to the BLS website, to dig a little deeper into the Trichordist’s numbers. Fortunately, the Trichordist was kind enough to cite its sources in the image above. Unfortunately, it did not include hot links to these sources in its blog post, and I’m kind of lazy. So rather than hand-typing those links into the brower,  I first did a web search on “BLS musicians” to see if that would take me to the right place. I ended up at a page titled “Occupational Outlook Handbook” (http://www.bls.gov/ooh/entertainment-and-sports/musicians-and-singers.htm).

This page did not contain the data that the Trichordist used to make the chart above, but it did indicate the following:

  • that there were 176,200 jobs for musicians and singers in 2010.
  • that the number of musician and singer jobs was expected to grow 10% by the year 2020.

At this, point, I was getting confused. Why were these numbers different than the Trichordist’s?

Not only were the numbers from the “Occupational Outlook Handbook” completely different (and significantly larger) than the Trichordist’s numbers, they also indicated job growth over the next 10 years, not job shrinkage (which is what the Trichordist had asserted was happening). So I bit the bullet and hand-typed in the links from the Trichordist’s chart above, which are as follows:

http://www.bls.gov/iag/tgs/iag711.htm#about;

http://www.bls.gov/oes/2003/may/oes272042.htm

When I got to those pages, the numbers were the same as those cited by the Trichordist above. But I was still left wondering why the BLS website had more than one set of musician employment numbers.

It turns out that the Trichordist’s numbers and the Occupational Handbook numbers were drawn from different surveys that used different methodologies.

The 176,200 figure comes from the Industry-Occupation Matrix Data, by occupation (the “Matrix”). You can find that here. The Matrix data is further broken down by industry, and you can download the raw data for an industry in .xls spreadsheet format. (The raw data for musicians and singers is available here: ftp://ftp.bls.gov/pub/special.requests/ep/ind-occ.matrix/occxls/occ27-2041.xls.)

The BLS has this to say about where the Matrix numbers came from. The methodology of the Matrix is explained here. This paragraph from that discussion seems particularly instructive (especially the last sentence):

Base-year employment data for wage and salary workers, self-employed workers, and unpaid family workers come from a variety of sources, and measure total employment as a count of jobs, not a count of individual workers. This concept is different from that used by another measure familiar to many readers, the Current Population Survey’s total employment as a count of the number of workers. The Matrix’s total employment concept is also different from the BLS Current Employment Statistics (CES) total employment measure. Although the CES measure is also a count of jobs, it covers nonfarm payroll jobs, whereas the Matrix includes all jobs.

So where do the Trichordist’s Numbers come from and how do they relate to the numbers from the Matrix?

The numbers from the Trichordist’s chart were drawn from the Occupational Employment Statistics program (OES) (http://www.bls.gov/oes/), a data source that seems to share some methodological similarities with the CES (which was referenced in the paragraph above).

The OES FAQ explains the methodology underlying the OES. For our purposes, the most salient information is as follows:

“Employees” are all part-time and full-time workers who are paid a wage or salary. The survey does not cover the self-employed, owners and partners in unincorporated firms, household workers, or unpaid family workers.

It appears that the numbers used in the Trichordist’s chart exclude both self-employed workers and owners of unincorporated firms (i.e., the partners in a partnership or the members of an LLC).

It’s not trivial to omit self-employed workers and owners of incorporated firms. Of the total musician and singer jobs in 2010, the data from the spreadsheet I linked to above indicates that 75,000 (42%) of those jobs stemmed from self-employment. I don’t know about you, but it definitely makes intuitive sense to me that this percentage would be pretty high, as lots of musicians are self-employed/sole proprietors or operating in a partnership or LLC (i.e., an unincorporated association).

Update: In a Facebook comment thread on this blog post, I gave some more concrete examples about common situations for working musicians and how they are captured by the BLS data I looked at. One of the commenters suggested that it would be useful to have it in the main blog post as well. So I’m adding it here.

(a) Let’s say we have a band. They make their entire living from music. The core group is two people. They are organized as a member-managed, LLC with two members. The LLC is taxed as a partnership. They don’t receive a salary. They get their money in the form of distributions from the LLC. This money flows through to each of their 1040s on a k-1 and is treated as self-employment income.

Let’s say that two other musicians also regularly play in this band (perhaps they are the drummer and bass player), but they are not members of the LLC (i.e., they don’t hold equity in the company). These musicians may also pick up work playing gigs with other people when the main band isn’t active. Both in the context of their main band and on any other jobs they do, these musicians get paid as 1099 contractors. So all their income in a year is also from self-employment.

None of these musicians are counted in the OES data the Trichordist has cited, but these musicians are apparently counted in the Matrix data. The scenario above is a very real scenario, especially for the so-called middle class of musicians (i.e., people who are making enough money from playing music to subsist without another job). As the Matrix data shows, the median income of the musicians in their survey was around $22/hr. That works out to a yearly gross income of around $42k (40 hours a week for 48 weeks a year). So half the musicians in the Matrix data made more than that and half made less. I suspect that a lot of full-time musicians in the $20k-$40k range fit the scenario I’ve spelled out above (either co-owner of a partnership or LLC or a sole proprietor receiving living mostly from 1099 contractor income).

(b) Now, let’s think about a more successful band. I don’t know anything about the particulars of Wilco, but I get the sense that Jeff Tweedy is the only equity holder in Wilco, Inc. (or Wilco, LLC). So all the other guys are likely hired guns from a legal and financial standpoint.

In a situation like that, where a band is successful and has more predictable cash-flow, there’s a much better chance that these hired guns won’t be 1099 contractors anymore. Instead, they will be salaried employees of Wilco, Inc., benefits will be paid, exclusivity may be required, etc.

Musicians in the Wilco situation would likely be counted in the OES numbers that the Trichordist cited. And to the extent that the OES numbers say that these kinds of musician jobs have shrunk significantly since 2002, that’s no small thing. For those kinds of jobs are good jobs, and we should all probably be fighting for a world in which there are more jobs like that for musicians. But that’s a different issue than the one the Trichordist has put on the table (i.e., the changing character of musician jobs vs. a change in the absolute number of musician jobs).

Where does that leave us?

I’d love to get a more nuanced picture of things than I have now. Even with the additional info from the Matrix, a lot of important questions remain unanswered. But based on the info I found on the BLS website, I will say this: If the goal is to understand how many working musicians and singers there are over time, the job numbers used must include self-employed workers; otherwise, they aren’t suitable to that task. If we had, say, Matrix data from 2000 that could be compared to the 2010 Matrix data, maybe we would find that the trends in that data are the same as the trends in the OES data that the Trichordist used for its chart.

But absent that sort of data, it seems like the broadest claim one can make based on the OES data is that payroll-based jobs for musicians have shrunk since 2002. However, once we narrow things down to that claim, it significantly muddies the causal link that the Trichordist is trying to make between the rise of digitial music and fall of musician jobs.

The loss of a payroll job doesn’t necessarily mean that the person in question was unable to find a nonpayroll job as a musician. Indeed, a lost payroll job might well be replaced by a new non-payroll job in the economy. Therefore, the absolute number of musician jobs may not have shrunk at all. Instead, it may be that the character of musician jobs has shifted.

Having said that, the loss of payroll-based musician jobs may still be significant. As in other industries, the loss of such a job can mean that a musician is exchanging a job with benefits, etc. for an independent contractor situation, where pay and benefits are not as good. So there may well be economic losses involved. But it seems highly speculative to draw conclusions about the nature or cause of these sorts of economic losses from the BLS data cited in the Trichordist’s blog post.

Perhaps the Trichordist will dig further into this question, find more data, and then share what it has learned with the rest of us.

RIP Steve Jobs: This One Feels Personal

I’m not sure I’ve ever mourned the passing of a big corporate CEO before. I don’t expect I’ll mourn the passing of another one anytime soon either. But I am mourning the passing of Steve Jobs today. Apple Computers has always had a different sort of relationship with its customer base than most other large companies. Indeed, many Apple computer users are more like acolytes than customers, especially those of us who have a multi-decade relationship with Apple and its products.

I have a vivid memory of my first encounter with the Apple II, at the house of a friend of mine in around 1980. I had more computer experience than most people at that point, having logged many hours on the PLATO mainframe system at the University of Illinois during 8th and 9th grade in the late 1970s. My dad was a professor at U of I, so he was able to get a sign-on for PLATO. He let me and my brother use it, and use it we did.

The PLATO system was very advanced for its time, with powerful graphics and multi-player games that didn’t see the light of day in the mainstream until years later. The Microsoft flight simulator was a direct descendent of a simulator developed for PLATO. Ray Ozzie, most recently the technology guru at Microsoft, was a computer science student at U of I during this time and developed a notes program on PLATO. Later, it became Lotus Notes. Looking back on it now, most of the central attributes of the modern Internet were already in place on the PLATO system in the 1970s. But I’m digressing. Sorry. Just trying to establish some context. Let’s get back to the Apple II.

Honestly, compared to PLATO, the Apple II seemed pretty weak. It had a grid based Star Trek/Space War game similar to one I’d played on PLATO. But this was a really basic game compared to some of the games on PLATO, like “Empire” or “Avatar.” Nevertheless, the idea that a computer was now affordable enough that you could have it in your house, well, that was still really cool. I wished we had one at our house. It was also clear that the Apple II kicked ass on the computers I had seen in the Radio Shack store in the North Randall Mall. Everything about the Apple II seemed better: the way it looked, the Apple logo, the advertising. It was all cool, and it definitely made Apple seem like a club you wanted to be a part of.

By 1983, IBM was starting to steal Apple’s thunder with its “Personal Computer” (“PC” for short). Not long after that, Asian PC clones starting coming out, running Microsoft’s MS-DOS operating system. The personal computer stampede was on. My dad bought a Sanyo PC clone at Christmas time in 1983. It had a single 5.25 inch floppy drive and maybe 128K of RAM. It came bundled with MS-DOS, Wordstar (word processor), Calcstar (spreadsheet), and Datastar (database manager). He bought a daisywheel printer to go with it. So all the printed output looked just like an IBM typewriter.

While I was home on holiday and summer breaks, I learned how the Sanyo PC clone worked. The lack of games was a drag, and the thing did not scream fun. But the word processor was a revelation. I had a lot of writing to do for school, and this was just the utilitarian tool I was looking for. All of a sudden, I could write with ease. No more left-handed pencil smudges, illegible script and multiple cross-outs. Suddenly, the writing process had a heretofore unimaginable level of plasticity. I could write and edit at the same time (just like I’m doing right now). This was huge.

In the fall of 1984, when I headed back to University of Michigan, that Sanyo machine came with me. My dad got a newer Sanyo with two floppy drives. At that point, I was pretty much the only person I knew who had a computer. My housemate, Bill Potter, had studied computer programming in high school, and he was much more technically inclined than I was. He dug right into the manual and figured out things that were beyond me, like batch files and using Datastar and Calcstar. I definitely learned a lot of stuff from him. But mostly I just wrote numerous history papers and my senior honors thesis, feeling very technology forward.

Up to this point, I only had a rather dim awareness of the Apple Macintosh. I had seen the big 1984 commercial during the Super Bowl and perhaps some pictures in magazines. But it wasn’t until late 1984 or early 1985 that Macs started appearing in increasing numbers on campus, both in computer labs and in student dorm rooms. I think Apple may have instituted favorable education pricing around this time to try and jump-start sales of the Mac amongst college students. Or maybe this new innovation was just finally arriving in the midwest.

At first, I dismissed the GUI of the Mac, much like command line junkies before and since. But then one night, I found myself in the dorm room of Phil Dürr (later a guitar player in the band Big Chief of Detroit, Michigan and SubPop Records fame). He had a Mac and he was playing with the program MacPaint, drawing on the screen, typing text, changing font sizes and doing all kinds of stuff I’d never seen a computer do before. Creative stuff. Fun stuff. This was not just a utilitarian writing tool. It was clearly a lot more. It was like PLATO, only it had even more to offer, especially its grayscale graphics.

My Sanyo was a generic “Personal Computer.” Phil’s computer had its own personality. It wasn’t just a “PC.” It was a “Mac.”

Notwithstanding that reality, I stuck with my utilitarian Sanyo for quite a while after that encounter with the Mac. First and foremost, I didn’t have the coin to switch. Moreover, while MacPaint was cool, I didn’t have much of a use for it, beyond thinking it was cool. MacWrite was certainly a functional word processor, but it wasn’t a huge step up over Wordstar in terms of functionality (indeed it might have been a step back in many ways). My daisywheel printer had better quality output than the dot-matrix ImageWriter printer that was bundled with the Mac. Nevertheless, the seed of Mac had been planted in my head.

When the Mac II came out in 1987 or so, my dad picked one up. It had a then unheard of 40MB hard drive. He had to drive down to Columbus, Ohio from Cleveland to pick it up. Some electronic music students from Ohio State loaded an ass ton of different software onto the hard drive of the Mac II. But it was in no discernible order. Home on a break, I spent hours exploring all the stuff on that hard drive. Yeah, I know it’s smaller than the size of 10-15 average length mp3s. But at the time, it felt like a massive, almost infinite library of stuff. Subsequently, he also got some early MIDI sequencing software (Professional Performer), an early two-track Pro-Tools editing system, and a 500MB external SCCI hard drive to store digital audio on. That was some mind bending stuff in its time.

About a year after my dad got his Mac II, I stopped working on my Sanyo at home and started writing papers on the Mac SE/30s they had in the computer lab at the University of Wisconsin (where I was in law school). I really started digging into Microsoft Word and appreciating its GUI and WYSIWYG layout. They also had a laser printer in the lab, and I really liked the typeset looking output you’d get with it if you used Times font. At that point, I’m not sure I would have said that MS Word was better than Wordperfect 5.1 on the PC. But it was definitely growing on me.

I finally got my first mac in 1991. It was a used Mac II, purchased from Pre-Owned Electronics, in the Boston suburbs. Like my dad’s, it had a 40MB hard drive. When I moved to Seattle in 1992, I purchased a Personal Laserwriter NTR at Ballard Computer (now a Thai restaurant). Having my own laser printer was, of course, a revelation. Like most Apple hardware, the printer was very well built. I used it for well over 10 years. Even after Apple discontinued the Localtalk standard, I bought an adapter that allowed me to hook it up via Ethernet. It just kept on chugging through a series of new Macs. There was a Mac IIvx (100MB hard drive), a Performa 6230 (1GB hard drive), a Beige Powermac G3 (10GB hard drive), a Powermac G4/400 tower (40GB hard drive), which I’m still using, and the Macbook I’m typing this on (250GB hard drive). I also got an iPod Touch 16GB when I bought the Macbook. This handheld device probably has more computing power than my first three or four macs combined.

That’s 20+ years of personal computer use in one long paragraph (almost my entire adult life): 20 years of writing, reading, making music, listening to it, drafting contracts, watching video, and so much more. Steve Jobs played a huge role in shaping the technological contours of all that. His work empowered me to do my work. So his passing definitely feels personal to me.

Where most other people in the computer industry somehow never seemed to get things quite right, Jobs usually did.[1] He seemed to have this innate sense of what good is. I don’t know why this sense is so hard to come by. But it is.

I’ve interacted through the years with a whole lot of musicians, artists, and other creative people. Many of them are very skilled. But only a few of them also seem to have this innate sense of “good.” These are usually very special people. If they make or record music, you want to hear it. If they do interior design, you want to spend time in that space. If they build something, you want to use it. If they cook something, you want to eat it.

Often, I think, these kinds of folks tend to work in smaller, more individualized environments, where they can do their thing and avoid butting heads with people who don’t get it and never will. That Steve Jobs didn’t do this makes his accomplishments even more impressive. He somehow managed to imprint his sense of what “good is” onto a large, global organization.

Was Jobs often an asshole? The public record would indicate that the answer is “yes,”  Was he a hard guy to work for? That answer also appears to be “yes.” Was he a bad manager of people? At least as a young man, yes. Did he get better at this with age? Perhaps.

But that’s all inside baseball stuff, and as consumers most of us aren’t amateur business ethicists (even if we should be). We’re concerned with outcomes, not process. We don’t usually spend a lot of time examining how the sausage is made. We just eat it, evaluate it, and enjoy it when it’s good.

The Jobs sausage was very good indeed. It will be missed.


  1. There’s at least one major thing that Jobs got just as wrong as everyone else in the computer industry: the labor practices in the Chinese factories where Apple builds its products. This is a significant black mark on Jobs’ legacy and the legacy of the computer industry more generally.

    Of course, most of us consumers in the West are complicit in this as well, placing outcomes over process, and tacitly accepting the Faustian bargain of modernity, that visionary leaders like Steve Jobs invariably carry out their grand utopian projects on the backs of abstracted, anonymous little guys.

    As Marx and Engles put it so eloquently in the Communist Manifesto, “All that is solid melts into air, all that is holy is profaned, and man is at last compelled to face with sober senses, his real conditions of life, and his relations with his kind.” In short, this modern world is a dirty business. (See the work of Marshall Berman for a more thorough and eloquent discussion of these matters.)  ↩

Reclaiming the Old Style “Most Recent” Feed in Facebook: a Workaround

If you’re like me, you may not be super excited about the recent changes to Facebook’s home page. I have simple needs. I just like seeing the most recent updates from all my friends in chronological order with the newest posts first.

I don’t need Facebook telling me what posts it thinks are most important and putting them at the top of the feed. I can figure that out myself. I don’t need that ticker either, with it’s crazy pop-up windows.

After a little tinkering tonight, I think I happened upon a workaround to address these annoyances and reclaim much of the “Most Recent” feed functionality of the old Facebook layout.

It’s not a perfect solution and a bit of a pain to set up, but it gets rid of the ticker, puts all your friends’ updates in the feed, lists them in chronological order, and doesn’t require installing a browser extension, Facebook apps, or anything.

Here’s what you do:

1. Go to the list menu in the left sidebar and create a list.

2. Call it “everybody” or something like that.

3. Add all of your friends to the new list (this will be pain in the ass if you have a lot of friends–that’s where the time and elbow grease come in).

4. In the left sidebar under the lists heading, click on your new “everybody” list so you see that view.

5. Note that there is no ticker on the right hand side. You should also be seeing a chronological view of all your friends’ updates in your feed.

6. Click on the upper right hand corner of that view where it says “manage list.”

7. Select “Choose Update Types.” This will allow you to decide what kind of stuff you want in the feed. I chose everything except game notifications.

8. You might consider bookmarking this view. Then you can use it as your replacement FB home page, since you can post updates, etc. from this view just like the default home page.

Anyway, I hope this is helpful. I guess we’ll see how long it lasts before the overlords at FB change things up again.