Revisiting McPhee’s Theory of Exposure and the Long Tail

Ever since Chris Anderson published The Long Tail: Why the future of business is selling less of more (2006) marketers have been pondering the implications of a world where the constraints of traditional brick-and-mortar retailing have fallen away as online stores can profitably carry products that appeal to only a select few. Anita Elberse, a Harvard Business School professor, in Should you invest in the long tail (2008) linked these post-Internet era ideas with McPhee’s (1963) old-school Theory of Exposure to bring balance to the thought-space. McPhee’s theory asserts two principles: (1) the most popular products/services (hereafter just “products”) in the fat head enjoy a natural monopoly among casual users, the majority of users in any product category, because these are the products that they can most easily gain awareness of; and, (2) even when casual users become aware of niche long tail products they tend to prefer the mass-market fat head products because these products have been optimized to appeal to a more diverse set of users, while niche products are generally optimized for aficionados. These two factors (lesser known and less appealing) put long tail products in double jeopardy.

We tested McPhee’s theory against Yelp’s review data and found that his ideas were generally supported, but we made some fresh observations in the process. As expected, we found that the venues (most Yelp reviews are for businesses like restaurants and hotels that are more accurately described as venues than products) reviewed by Yelp participants formed a long tail (Figure 1), where the most reviewed businesses are in the fat head. While some have found the head to be separated from the tail in the classic Pareto 80-20 split (80% of venues in the tail), we used a two-step clustering algorithm and found that 90-10 was a more natural split.

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Figure 1. A two-step clustering algorithm found that 90% of venues reviewed on Yelp are in the long-tail.

The same clustering algorithm was also used on reviewers, where they were segmented based on the proportion of niche venues in their reviews. It was found that reviewers fit into four natural clusters as described in Table 1. How was McPhee right? The pure fat head customers (cluster 1) are the most satisfied (average star rating of 3.82) and loyal (5840 checkin-ins per business) consumers among the main-stream businesses that are 97.3% of their experience.

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Table 1. There are four natural clusters among Yelp users based on the proportion of long tail businesses they review.

What’s new? Our interesting discovery was the cluster 2 consumers who are almost as happy (3.77 stars) as the mainstream cluster 1 consumers, but are responsible for a much larger number of reviews that have a monopoly on the readers’ assessment of review helpfulness. It seems that experiencing roughly 25% niche venues may be some kind of novelty sweet-spot that most inspires consumer-generated media, and most enriches consumer knowledge in general. Therefore, McPhee’s theory seems correct but may not tell the whole story of consumer experience in the long tail. Does experience with this mix of venues empower cluster 2 consumers to make better comparisons between the niche and mainstream? Is there something about the personality of cluster 2 consumers that make them more skillful review writers? Are they more allocentric? Many unanswered questions, but a fascinating phenomenon nonetheless.

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