The queries we type into Google can be broadly classified into two groups: head queries, or general keyword searches of less than three words; and long tail queries, or specific searches using a phrase or several words. The latter long tail queries account for a significant portion of the searches on Google (with many sources claiming as much as 70 percent).
Google’s search algorithms are excellent at surfacing relevant content for basic keyword style head queries, but when we search for something specific using a long tail query, the answers aren’t consistently relevant. I would submit that this isn’t so much an issue with Google’s search algorithm as it is a content problem; that is, a large number of content sources that attempt to service long tail queries simply do a poor job of it. For Google to improve its search relevance for long tail queries – which it must, as those continue to become a huge chunk of its searches – it should integrate a high-quality QnA service like Quora with its search.
To better understand the differences between the two types of search, and the dilemma Google now faces, do a quick search using any or all of the following, pretty straightforward long tail queries and check the quality of search results:
“diet plan for diabetics and high blood pressure”
“how to get rid of acne”
“what do turtles eat as pets”
“how to train your parrot to talk”
“important things to consider before purchasing a house”
You will quickly discover that the results are mostly identical or slightly rehashed versions of other articles scraped from multiple sites across the web, many of them originating from content farms like Demand Media and Associated Content. Those sources are among many that specialize in trying to corner the market on servicing long tail queries. However they all suffer from two major problems:
Poor quality The army of low-paid freelancers who manufacture the “content” for these sites get paid essentially by volume. They are almost never experts in a given topic (or even passingly familiar, one could argue). They simply crank out 500-word article as quickly as possible so that these networks can embed three adsense ads in between and then move on to the next topic.
Bias toward popular keywords Despite intending to service long tail queries, in fact many of these services tend to produce content around keywords that are popular enough that they can reliably generate advertising revenue.A source of reliable long tail query content
Clearly there is a demand for reliable long tail query content queries. Now consider a practical one like “how to get a passport faster,” and how massively helpful it would be to get the answer from a person who has actually gone through the process, rather than the person who designed the process. Wouldn’t it be logical for Google to implement a source of content that is produced by generally passionate, informed people – a source like Quora?
Unlike Wikipedia, which is best at answering head queries, Quora is all about long tail. So integrating Quora with search would provide Google’s users more reliable and useful results for long tail queries. It would also contribute to a virtuous cycle by allowing users to help produce reliable content, too, as searches prompt further contextual content that may need answering. This will help Google get knowledge from content sources (such as those who contribute to Wikipedia) who do not own a website but have valuable knowledge.
As another example, for a more task-based query like “how to file taxes,” you might also end up with relevant contextual content in the right pane of the search results:
Integrating Quora will enable Google to serve far more relevant answers for a much broader range of queries even though a smaller percentage of people will be actively producing the content. And it’s worth noting that in the process, Google will be effectively replacing dollars other networks pay to content churners with upvotes and follows to passionate users instead (talk about virtuous cycles!).
This is social search, where content will be produced in the context of social, but consumed in the context of search.
Narendra Reddy is chief product officer for the educational software developer Wignite. Follow him on Twitter @naren.
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