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What The Long Tail Of Search Actually Looks Like

Much has been written about how savvy search marketers can exploit the long tail in both organic SEO and for paid search campaigns. The formal definition of the long tail refers to the statistical property that a larger share of population rests within the “tail” of a probability distribution than the “head.”

In search marketing terms, keywords are the literal key to reaching the long tail, and there are two approaches to long tail keyword selection. The first is to optimize for or bid on less popular or relatively uncommon words. The idea here is that anyone using these words as search queries likely has a very specific idea of what they’re looking for, and may be more likely to click on a search result or ad and ultimately convert. What you lose in volume with this strategy, you may make up in volume—this approach is what has made companies like Amazon and Netflix so successful because they don’t have physical inventory limits and can offer literally millions of options to customers.

The second approach to long tail keyword strategy is to optimize or bid on multiple word keywords (some call these keyphrases). The idea here is similar, but rather than using uncommon words, multi-word keywords may use virtually any words—but when combined in a phrase or exact match are again likely to be relatively low-volume but highly intent-oriented indicators of searcher needs or wants.

Some search marketers are skeptical that searchers actually use multi-word queries. But new data from Hitwise reveals a classic long tail distribution for multi-word queries. Measuring U.S. search queries in March 2010, Hitwise found that single-word search queries were the most common—but just barely:


Here’s what this distribution looks like on a graph:


This is nothing less than empirical proof that the long tail exists—and that it spells huge opportunity for search marketers willing to do the work to take advantage of it by digging for the multi-word queries visitors and customers are using on search engines.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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