Tuesday, March 14, 2006

 

The Long Tail Phenomenon

The network era brings into sharp relief the phenomenon of long tail. many of you have heard of the statistical distributions such as Zipf, power laws etc. Chris Anderson of Wired Magazine popularized it in the context of business models in the digital, networked world. He has a blog on this. A book is expected later this year, I believe.

Amazon and Netflix have been used as prototypical examples. I liked the quote by a former Amazon employee that best describes the Long Tail: "We sold more books today that didn't sell at all yesterday than we sold today of all the books that did sell yesterday."

Clearly, there are many companies in the network era that reflect the Long tail phenomenon:

1. Amazon (compare to Barnes & Noble or Border's)
2. Netflix (compare to Blockbuster or local videostores)
3. Apple itunes or yahoo music (compared to Tower Records or physical stores)
4. ebay (compared to retail stores and department stores)

It appears that the logic can be applied to software as well. There is a good discussion and analysis posted in 2005 here. a powerpoint file is available here.

On Sunday, March 12, NY Times carried an article about specialized television channels on the Internet. a variety of niche television programs seem to be available. Then, there is Google video aiming to be the hub between content creators and viewers with differential pricing. Then there is You Tube.

It is worthwhile taking a look at this in some detail to understand the emerging concept of service platform. what principles can we derive from these different cases and examples? how do they apply in settings that have not yet been touched by this phenomenon so far?

Thoughts?

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