Congrats to last.fm
who just announced its first content agreement with a major label.
The deal will let Last.fm's rapidly
growing community have access to Warner's amazing roster of artists through their free streaming radio service and tee up a premium subscription radio service.
is growing like crazy, with over 15m monthly active users
now experiencing the joys of discovering new music through the recommendations of other community members. Making it easy for people to access major label content will only make the service more valuable to its users and easier for labels to promote both new and catalogue product to consumers - so great news for everyone.
This service is particularly close to my heart (and not just because I am a small investor) as I've been dabbling in the entertainment recommendations space for over ten years now.
First with Firefly
, where we launched the web's first music recommendation service (later sold to Launch, now Yahoo Music
) and then again with Video Island (now Lovefilm
) where we applied similar principles to movie recommendations to build Europe's largest online DVD rental service.
There is no doubt that at Firefly we were way too early and the Internet was too immature a medium for the real power of recommendations to take off, but in the last ten years both Amazon and Netflix
have done an amazing job popularizing collaborative filtering and making recommendations a central plank of consumer discovery.
Amazon has elevated the application of datamining
to help consumers decide what products to buy to an art form. Netflix
values the approach so much it's offered a $1m prize
to anyone who can improve their approach to movie discovery.
More often than not the weapons of datamining
have been wielded by companies on behalf of companies - they mined to see how to sell more. Companies in the future will put these weapons to work for consumers.
is at one of the new businesses at the vanguard of taking discovery to the next level.
One thing which is particularly nice about their approach is the fact that through their scrobbling
software (which attaches to your media player), they make it so easy for you to contribute to and benefit from the rest of the community.
We wrestled with the earliest applications of social information filtering
at Firefly and one of the big challenges was always about how to best motivate explicit (ie
. a rating) and weight implicit (ie
. an observed
behaviour) data. There is no doubt implicit data collection is much easier on the user, it takes no time, all you have to do is agree to be observed and feel comfortable that in return your information will get great value and your privacy will be protected. Nic Brisbourne
has an interesting post on this subject.
people trust the service to watch what they are listening to they get discover
new things -- clearly this works beautifully with music, but there is no doubt with the emergence of other digitally based services we will see more and more of this paradigm. My old friend Seth Goldtsein
, as usual, is really pushing the envelope here with his work on Attention Trust and Roots Market.
side note: another cool thing about last.fm is their integration with Skype. All the communications service (Skype, Google, AIM, Yahoo! and Messenger) are now opening up to 3rd parties here are going to be amazing opportunities to build great application on top of platforms which come with presence, contacts, voice, IM and video built in. What an amazing platform for new applications to be built around.
Like with Last.fm
, obviously this can work with people's explicit knowledge with video (think where Joost
can go) and it is already working to some degree without people's knowledge in online advertising and the current vogue for behavioural targeting.
We are scratching the surface
of how we will be able to leverage the computational power now available to us for the analysis of vast swathes of comples data to benefit consumers and help them improve their decisions. One of the best examples of a service helping people make better decisions through the application of hard core math and computation is Farecast
-- delivering an amazingly valuable view of airfare information to help people decide when to buy tickets.
Congratulations to Last.fm
for showing the tip-of-the-iceberg to 15m people. I'm looking forward to seeing what's next.
Labels: amazon, collaborative filtering, datamining, farecast, firefly, joost, last.fm, music, portfolio, recommendations