We all are intimately aware of how fast the tech industry moves. Breaking news from six months ago feels like years – it’s out of date and thus probably obsolete and irrelevant. So with great trepidation I chose to read and report on The Long Tail by Chris Anderson for my first blog post. Not only was this book about the Internet, but it was published back in 2006. That’s like, the Middle Ages in technology terms! But like the great Nostradamus, Anderson’s writings still ring true today, and the web analytics industry at large would do well to heed his claims. In short, The Long Tail describes the rapid rise of the niche and the decline of the blockbuster, and how we as consumers behave when faced with infinite variety as opposed to scarcity. Yes, this sounds like a bunch of big ideas, but what I aim to explore is how web analytics exists in the forces of the Long Tail.
For the uninitiated, let’s get a look at what the Long Tail looks like:
Figure 1 - The long tail in all its glory
This graph depicts both the 20th century attitude towards consumer behavior (the green area = “blockbusters”) and the sheer opportunity to capitalize on the “non-hit” business that was once considered unattainable (the yellow suggests the minimal but constant demand for less popular goods).
Hopefully you can figure out why it’s called the “Long Tail” – the yellow shaded area depicts a diminishing yet infinitely long area under the curve, and if you follow it along it will eventually rival and even exceed the area occupied by the green area (known as the Short Head). Besides instilling a sense of nostalgia for your high school Algebra class (Anderson reminds us it’s called a powerlaw curve, or what you get when you punch in “1/x” into your graphing calculator), this curve represents both the behavioral and economic state of affairs for any and all of the content available on the Internet. From the author’s own original blog post (which spawned the book), Anderson describes the Long Tail in the context of the retail book industry:
What's really amazing about the Long Tail is the sheer size of it. Combine enough non-hits on the Long Tail and you've got a market bigger than the hits. Take books: The average Barnes & Noble carries 130,000 titles. Yet more than half of Amazon's book sales come from outside its top 130,000 titles. Consider the implication: If the Amazon statistics are any guide, the market for books that are not even sold in the average bookstore is larger than the market for those that are…In other words, the potential book market may be twice as big as it appears to be, if only we can get over the economics of scarcity. Venture capitalist and former music industry consultant Kevin Laws puts it this way: "The biggest money is in the smallest sales."
Anderson lists three market forces that encourage the emergence of Long Tails:
- The democratization of the tools of production (i.e the negligible costs of publishing music/videos/books to the Internet)
- The lowered costs of consumption due to democratized distribution (think of eBay or the Amazon Marketplace, the sellers are spread out over a larger area than any distribution center could hope to cover
- The increasingly precise connection of supply and demand (this is everything from the ‘recommendations’ section of iTunes/Amazon/Netflix to a general Google search)
Web analytics also influences how filtering works within the Long Tail, and this is equally important to connecting supply with demand. Anderson explains how traditional retail functions as a sort of “gatekeeper.” Due to physical shelf space limitations, retailers are forced to predict the blockbuster hits – in other words, only the Short Head of the curve. The consumer conforms to whatever the gatekeeper deems worthy of stocking on their shelves, and if their taste deviates from the hits, then they leave the store empty-handed. But in the Long Tail, where “the safe bet is to assume that everything is going to eventually be available,” why should any filter act as the gatekeeper? Rather than “predicting taste” Anderson recommends we use web analytics to measure taste. Much of the work in web analytics revolves around this endeavor to become a better “post-filter” – gathering and responding to feedback after it’s already hit the web.
I’ve only covered a few of the big ideas contained in The Long Tail, but hopefully one can appreciate how web analytics fits into its framework. Just as the curve continues to extend into the far reaches of the digital world, so too will the web analytics space expand with new and innovative ways to connect supply and demand. On a more general note, I would recommend Chris Anderson’s book to anyone curious about how we got here (in terms of technology and the Internet, anyway).