Rethinking the Long Tail Theory: How to Define ‘Hits’ and ‘Niches’

Using data on movie-rating patterns, new Wharton research challenges current thinking on the Long Tail effect — a widely publicized theory that suggests the Internet drives demand away from hit products with mass appeal, and directs that demand to more obscure niche offerings.

In a working paper titled, “Is Tom Cruise Threatened? Using Netflix Prize Data to Examine the Long Tail of Electronic Commerce,”Wharton Operations and Information Management professor Serguei Netessine and doctoral student Tom F. Tan pull information from the movie rental company Netflix to explore consumer demand for smash hits and lesser-known films. Netflix made its data available as part of a $1 million prize competition to encourage the development of new ways that will improve its ability to introduce customers to lesser-known titles they might find appealing.

The Long Tail theory suggests that, as the Internet makes distribution easier — and uses state-of-the-art recommendation systems that allows consumers to become aware of more obscure products — demand will shift from the most popular products at the “head” of a demand curve — as charted on an xy axis — to the aggregate power of a long “tail” made up of demand for many different niche products.

The Wharton researchers find that the Long Tail effect holds true in some cases, but when factoring in expanding product variety and consumer demand, mass appeal products retain their importance. The researchers argue that new movies appear so fast that consumers do not have time to discover them, and that niche movies are not any more well-liked than hits.

According to Netessine, the Long Tail effect may be present in some cases, but few companies operate in a pure digital distribution system. Instead, they must weigh supply chain costs of physical products against the potential gain of capturing single customers of obscure offerings in a rapidly expanding marketplace. Companies, they add, must also consider the time it takes for consumers to locate off-beat items they may want.

“There are entire companies based on the premise of the Long Tail effect that argue they will make money focusing on niche markets,” says Netessine. “Our findings show it’s very rare in business that everything is so black and white. In most situations, the answer is, ‘It depends.’ The presence of the Long Tail effect might be less universal than one may be led to believe.”

The Long Tail theory was developed in 2004 by Chris Anderson, editor-in-chief of Wired magazine. Anderson is also author of The Long Tail: Why the Future of Business Is Selling Less of More. The key difference between the opinion of the book and the study by Wharton researchers is how they define “hits” and “niches.” In the book, Anderson focuses on the definition of hits in absolute terms such as the top 10 or top 1,000 products, while Netessine and Tan argue that, to take growing product variety into account, one has to define popularity in relative terms, such as the top 1% or top 10% of products, to properly assess the presence or absence of the Long Tail.

In an e-mail, Anderson says the Wharton paper and other academic evaluations that are critical of the Long Tail theory are not relevant because they take a percentage approach to evaluating the power of the head and tail of demand.

“Although academics are free to do all the relative analysis they want, it is incorrect to apply it to my theory,” he writes. Anderson argues that defining the head and tail of demand in percentage terms is meaningless in a market with unlimited inventory, such as a retailer with digital distribution. For example, take a company with 1,000 different items in which the top 100 — or 10% — account for 50% of sales. If 99,000 more items are added to the catalog and sales of the top 100 fall to 25% of the total, it may take another 900 items to make up the next 25%. In this case, Anderson would argue that sizable demand has shifted down the tail toward more people selecting fewer products.

In relative terms, however, 1% of the products now constitute 50% of the revenues, which would make it appear that there was a greater importance of the hit products. But since real people experience the world in absolute numbers, not percentages, this is a statistical illusion, he states. The truth is that people are choosing a wider array of titles. “Nobody in the business world is confused about this, thankfully,” Anderson adds.

Netessine, who shared drafts of the paper with Anderson, says the Long Tail theory is “fascinating” and he notes that he recommends Anderson’s book to incoming MBA students.

Nonetheless, he and Tan contend that Anderson’s focus on absolute demand can be misleading. “One has to be careful about defining hits and niches in the Internet era,” the paper states. “In a brick-and-mortar world, where product variety is relatively stable and all products are consumed at some rate, hits and niches are typically defined in absolute terms (e.g., the top 10, the bottom 100 movies). However, product variety has been skyrocketing in the Internet age, and therefore more and more products can be left unnoticed by consumers, or are being discovered very slowly, even though the customer base is also expanding.”

The 80-20 Rule

Indeed, at Netflix the number of rated movie titles increased from 4,470 in 2000 to 17,768 in 2005. If this product variety is taken into account so that product popularity is calculated relative to the total product variety, Wharton researchers do not find any evidence of the Long Tail effect. The authors also performed an analysis taking an absolute approach to the Netflix data, like Anderson, and found that the Long Tail effect is only partially present: Demand for niches decreases over time — rather than increases — although demand for hit products also declines.

The Wharton researchers also disagree with Anderson’s theory and its implicit challenge to the Pareto principle, or so-called 80-20 rule, which in this case would state that 20% of the movie titles generate 80% of sales. Anderson argues that as demand shifts down the tail, the effect would diminish. Using Netflix data, Netessine and Tan show the opposite — an even stronger effect, with demand for the top 20% of movies increasing from 86% in 2000 to 90% in 2005.

Anderson did his own analysis using the Wharton data and found lower demand for the top 500 products and more interest in the middle part of the curve. He also points out that a Long Tail adding up to 15% of total demand came from titles beyond the top 3,000 — the amount typically stocked in a video store.

While the Long Tail theory focuses on the revenue potential of selling many individual products, Netessine says it is important to acknowledge that cultivating this revenue comes at a cost — including expenses associated with operating its distribution centers and stocking thousands of DVDs.

When applying the Long Tail theory to companies, Netessine says, a relative analysis is more meaningful because it takes into account the costs involved in maintaining a supply chain to feed demand for many obscure choices. He points to Amazon as another example of an Internet distribution company that still has substantial costs involving warehousing and shipping.

A business model based on the Long Tail effect might work for a company based on pure digital distribution, such as the music website Rhapsody, according to Netessine. “For Rhapsody the cost of stocking the extra songs is zero,” he says. “As a result, it doesn’t cost anything to offer unbelievable product variety, and the consumer can go into the Long Tail and consume songs that were previously unavailable.”

For any company marketing a physical product, such as Netflix’s DVDs or Amazon’s books, managers must weigh the costs of stocking an item against the likelihood that it will generate revenue. “If you stock a lot of products that nobody consumes, then you have a problem,” says Netessine. “You have to start worrying about products not having enough demand and consumers not discovering the products fast enough. That’s exactly what we find in the Netflix data.”

Netessine points out that Netflix reported 55,000 movie titles in its 2005 annual statement, but, based on the data, only 18,000 of them were rated by the customers. In all, the researchers based their observations on an examination of 480,000 users, 17,770 movies and television series, and more than 100 million ratings representing a 10% random sample of all Netflix ratings.

The Wharton paper also explores how consumers branch out from hits to discover more obscure products. Netessine says the research indicates that “primitive” recommendation systems are likely to blame for the delay in lesser known products becoming available and consumers finding their way toward them. “Many recommendation systems are not terribly smart,” Netessine states, adding that recommendations about films are made to Netflix subscribers who view similar films. But in order for a film to be recommended, it must be viewed in the first place. “If you want to see the long tail effect — consumers going into those obscure products — you have to be sure consumers learn about them, and that’s not easy. Current tools may not be good enough.”

Indeed, Netflix made its data available as part of a $1 million competition to develop an algorithm that would lead to a 10% improvement in predicting user ratings. The company is now in the process of determining the winner.

The researchers also investigated the Long Tail theory premise that consumers will gravitate to more obscure products because they will find them more satisfying than mass-market hits. Contrary to Anderson’s suggestion and independent of how popularity is measured, Wharton researchers find that consumers tend to be less satisfied with niche movies than with hit movies. Moreover, it is mostly heavy movie watchers who venture into niche movies. Since only a small fraction of consumers constitute heavy movie watchers, it is not surprising that there is weak evidence of the Long Tail effect, Netessine concludes.

The paper argues that the research findings have important implications because the Long Tail theory has gained momentum in the business world. “Whether or not the Long Tail exists is a fundamental question for decision makers in marketing, operations and finance who face the prospect of further penetration of the Internet channel, which offers expanding product variety and new recommendation systems to help manage it,” the paper states.

According to Netessine, the research is likely to generate controversy because of its findings that contradict the popular Long Tail theory. Nonetheless, Anderson is the first individual acknowledged at the end of the paper for “his encouraging comments and constructive advice.” Says Netessine: “We have agreed to disagree.”

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