Good news fellow Mac users. A new and improved Shazam client has been released for Mac. For more on this, let’s go to the App Store description.
Shazam is about to teach your Mac a few new tricks.
(Nothing gets me more pumped for an app than copy reminiscent of a terrible buddy comedy trailer.)
Download Shazam, and bring the magic home.
The app you’ve come to rely on as your go-to music expert has been given a major upgrade for your Mac. Catch the music and TV playing around you without ever digging a phone out of your pocket. Go nuts, match it all.
Shazam runs quietly behind the scenes, but springs to life when it finds a song you should know about, creating playlists as it goes. You can now effortlessly find it, share it, and buy it. Now that’s magic.
2. How do we use your personal data?
We may use your personal data for the following purposes:
(i) to provide you with services and the display of customized content, integration to our partner apps and targeted advertising both on our apps/websites and on other apps/websites that we advertise through,
We may also encrypt and/or aggregate your data with other users’ data in order to create statistics about the general use of the Shazam apps and websites, which helps us to develop new products and services. We may also share this aggregated data with our business partners and third party advertisers.
3. Sharing data with third parties – key facts and how to opt-out
In the event that ownership of Shazam changes as a result of a merger, acquisition, or transfer to another company, your personal data may be transferred. If such a transfer results in a material change in the use of your personal data, then Shazam will provide you with appropriate notice.
Who’d have guessed? Shazam, like many other free services, generates revenue by selling user data and not just any kind of user data either. Shazam’s acoustic fingerprinting technology has the ability to give advertisers a particular kind of data that they’ve coveted for decades—better insight into television advertising. Information about television audiences has traditionally been comically opaque, if not outright dubious. Take this criticism of Nielson data from Wikipedia, for example:
Another criticism of the measuring system itself is that it fails the most important criterion of a sample: it is not random in the statistical sense of the word. A small fraction of the population is selected and only those that actually accept are used as the sample size. In many local areas of the 1990s, the difference between a rating that kept a show on the air and one that would cancel it was so small as to be statistically insignificant, and yet the show that just happened to get the higher rating would survive. In addition, the Nielsen ratings encouraged a strong push for demographic measurements. This caused problems with multiple-TV households or households where viewers would enter the simpler codes (usually their child’s) raising serious questions to the quality of the demographic data. The situation further deteriorated as the popularity of cable TV expanded the number of viewable networks to the point that the margin of error has increased due to the sampling sizes being too small. Compounding matters is the fact that of the sample data that is collected, advertisers will not pay for time shifted (recorded for replay at a different time) programs, rendering the ‘raw’ numbers useless from a statistical point of view. Even in 2013 it was noted that Internet versions of TV programs were still not counted due to them either having no ads (like Netflix) or totally different ads (like Hulu) than their TV counterparts effectively skewing the raw data on how popular a show really is.
Unlike on the web, where impressions are easily counted, analyzing the reach of television advertising is as much faith as it is science. A device with acoustic fingerprinting, however, can accurately identify when (and often where) an ad is being played. Assuming it’s on a device is attached to a human, Shazam can potentially provide advertisers with far more accurate viewership data which can be then used to negotiate future media buys. Users logged into Shazam (or connected via Facebook or Google+) sweeten the pot further by providing even more lucrative demographic data.
Not only does demand work in Shazam’s favor, but also supply. Relative to the droves limited to online data, only a few companies exist with both the capabilities and will to record users’ television viewing habits. Shazam competitor Gracenote is already in the game as are some TV makers such as LG. It’s also hard to imagine that Microsoft and Google aren’t competing in this field as both have always-listening products. (Side-note: The above Microsoft article includes a comment from a Microsoft rep claiming that they “don’t transmit personal data in any way, shape or form that could be personally identifiable to you.” The key term in that denial is “personally identifiable,” which doesn’t include data such as viewing habits.)
Shazam’s disadvantage has traditionally been that their app had to be running in order for the “magic” to happen. Users that exited out quickly after identifying songs left Shazam with only tiny slices of data. To solve that challenge, last year Shazam introduced Auto Tag. Auto Tag enables Shazam to listen even while in the background. While the feature is disabled by default on my iPhone, the Mac version has it on at launch. The Mac version also asks kindly to allow launch on startup to better ensure uninterrupted Shazam listening.
Consider for a moment how many people you know who might install Shazam out of the sheer novelty, never mind its very practical use. Now consider how many of those people would happily (or absent-mindedly) okay launch on startup or toggle the convenient Auto Tag feature on their smartphone. Lastly, think about just how often you or people you know surf the web while watching television.
Finally, it’s worth nothing that the cost of user data may be entirely worth the service provided for some, but that transaction with services such as Shazam is almost never transparent to users. Instead these novel and sometimes useful tools are presented often with patronizing marketing-speak simply as free with whatever cost obfuscated in some privacy statement.