This link has been bookmarked by 34 people . It was first bookmarked on 27 Jun 2008, by Roger Chen.
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My point is not to suggest that Elberse is wrong and that I'm right, it's only to point out that different definitions of what the Long Tail is, from "head" to "tail", will generate wildly different results.
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I think you're being way too generous on the author! It shouldn't even need pointing out that looking at percentages misses the entire point of what the long tail is about. In markets where the barrier to entry for content producers drops to zero, percentages are not a meaningful way to measure *anything*, let alone head and tail.
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When you do a 'statistical' analysis, you should never forget about the context of the data collection. In the case of data for product purchases, you should never forget that, in most cases, the data collection process is biased by the quality of the recommendation engine (and measuring this quality in a formal way is a very tricky and open problem). A poor quality recommendation engine will allow only 'hard core' users to find out what they are looking for, and, guess what, statistical counts will show you that only hard core and heavy users buy both blockbusters and niche products. If your start using a better (choose your metrics here...) recommendation engine, you may very well see that the relative weight of the long tail increases, and the purchases distribution will be shifted to the tail.
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going long tail without a proper recommendation engine is useless (and potentially harmful)
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For example, in the Rhapsody data, the top 1% account for 32% of the sales, and the bottom 90% 22% - leaving 46% for that 9% jammed in the middle. Might this group be interesting to look at in their own right?
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The Harvard seems to ignore the point that consumers are naturally attracted to stores with a large inventory. Moreover, this is not an Internet-era phenomenon. For example, consider how the "supermarket" led to obsolesce of the neighborhood grocery store. Another example is the impact of Barnes & Noble and Borders on the neighborhood book store.
Essentially consumers are drawn to the stores with a wider variety (longer tail) of merchandise even though the bulk of the money they spend might be on the most popular items. They choose to go to the store with the bigger inventory because it permits them to also get the hard-to-find items. This applies to Internet retailing as well. We may spend most of our money on the popular books at Amazon.com, but we choose the store (partly) because we know they will have most any book that might be on our shopping list.
http://insidedigitalmedia.com/a-new-twist-on-the-long-tail/#more-127
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Michel Bauwensblockbusters are not losing share to the long tail of niche products in those markets; indeed, they're gaining it.
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27 Jun 08
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Andy BrudtkuhlAnita Elberse, a Harvard Business School associate professor, has a really interesting article in the new Harvard Business Review that analyzes some Long Tail data and challenges some of the theory's predictions.
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