Last.fm is a music website that takes note of the music you currently listen to, and uses a technique called scrobbling to provide you with recommendations of similar music that you may also enjoy.
Headphones Smiley [Image] (n.d.). Retrieved from http://jekhinji.deviantart.com/art/Headphones-Smiley-60513279
Last.fm is a great example of Chris Anderson’s theory of the Long Tail and follows Tim O’ Reilly’s best practice recommendations in one of his patterns of Web 2.0, Leveraging the Long Tail.
Leveraging the Long Tail is all about taking advantage of the connectability of the Internet to reach smaller markets that were once not economically viable to exploit. Production and distribution costs are much lower, and your users can do a lot of the work for you, in terms of recruiting new users and contributing content.
The clip below features two classmates discussing the Long Tail theory – I’m not sure why one of the characters is dressed as a ninja though!
So now that you have an understanding of Long Tail theory, here are some of the ways that Last.fm Leverages the Long Tail.
1) Build on the driving forces of the Long Tail
a) Democratised tools of production
Last.fm aggregates its products by encouraging artists and labels to upload their work. More importantly than that though, Last.fm heavily relies on scrobbling and its API to provide its service, so really, it wouldn’t exist without its users’ contributions!
b) Decreased cost of consumption by virtue of democratised distribution.
Last.fm’s users play an important role in sharing what they’re listening to on the site. There is the option to log in with a Facebook account which will share your Last.fm activity for all on your friends list to see, and you can share sounds on Twitter, Google Plus and by email.
c) New forms of connecting supply and demand
I personally think that this is the area in which Last.fm particularly excels and distinguishes itself from other music websites that are taking advantage of the Long Tail phenomenon, eg. SoundCloud. Last.fm already knows in great detail what type of music you as an individual are listening to and their recommendation system strategically connects product to user. This level of personalisation is completely necessary as there are so many musical genres and such a vast amount of content on Last.fm.
2) Use algorithmic data management to match supply and demand
So, as I just explained, scrobbling is a great data management method but Last.fm uses other ways too. The most popular genres being listened to at any given moment are listed on the homepage, showing exactly how many people are listening.
(3) Use an architecture of participation to match supply and demand
Users can leave comments on every track and can also write and edit summaries of artists. This is an example of harnessing collective intelligence. In order to control the wisdom of the crowds, users need to log in to their account to contribute to the site and are able to flag inappropriate content.
(4) Leverage customer self-service to cost effectively reach the entire web
Everything on Last.fm is pretty much self-service, from setting up and managing your profile, to troubleshooting your problems. Users even answer each other’s questions on the help forum! The site is available in a number of languages as well, so anyone, anywhere, with an Internet connection can connect with Last.fm!
(5) Leverage the low-cost advantages of being online
Last.fm saves on customer service by providing a great search and filtering service, they save on advertising because their users are spreading the word, and they save on production and distribution costs… now that’s what I call smart money!
I’ll end this post with an ethical dilemma. Saskia Korsten mentions on her blog that Last.fm users are providing a ton of useful marketing information to get that level of personalisation I was talking about earlier. But this is true of many Web 2.0 applications. Has anyone been aware or bothered about this in their experiences with Web 2.0?
Untangling Web 2.0 