Best Guess was announced some time ago by Google. I have to admit, it was an announcement that I initially missed; but having now seen the result in UK SERPs, it begs the question of just how far aggregated data can be used to populate SERPs.
It’s not often that I perform a search as generic as “Manager of Arsenal” ,”Capital City of Venezuela” or “President of the United States”. It would probably be safe to assume that many of you are much the same. However, if you were to do so on Google, you could well be presented with a ‘Best Guess’. This is essentially an answer that the search engine has mustered by pooling information from authoritative sources.
I’m reliably informed, thanks to a quick Google search, that this feature has in fact been in operation since April (more fool me). However it has taken a full two months for me to actually stumble upon it, operationally speaking, and I would assume that I’m not the only one. This isn’t a confession of ineptitude, simply a preamble to the more important aspect of what Best Guess could signify moving forwards.
Google SERPs updates are ten a penny, most are far more important than a simple Q & A box. However, what I find interesting about Best Guess is the fact that it uses website data to provide an answer. This means that it shows an understanding of the question, the intention and the authority sites within that sector.
For instance, I searched for “Arsenal FC Manager”. Using four sources, Google ascertained that it was Arsene Wenger; on the money there then. The sources in question were a mixed bag. One was Wikipedia, which is only to be expected. Another was a high profile newspaper, The Telegraph and the other two were football-related websites Goal.com and Caughtoffside.com.
Over time, these sources change, as the search engine appears to seek the latest information – helping to avoid embarrassing inaccuracies. This is evidenced by the fact that the three news sites are all reporting recent stories which include the phrase “Arsenal manager Arsene Wenger”. The interesting aspect therefore is just how far this type of search could possibly expand.
Wolfram Alpha is a great example of an information/data portal that provides the most accurate answer to a search query. However, it is very much an internalised platform. Therefore all results come from equations and data that has already been fed in. This means that you can perform complex calculations, work out the population of a specific location or just ask silly questions (as I’ve done below).
Bing teamed up with Wolfram Alpha back in 2009, helping to bring a more diverse range of organic results compared with Google. So rather than forcing a searcher to go off and explore other sites to find out the capital city of Iceland, it could highlight the answer. This is essentially what Best Guess now offers.
Essentially the search engines are trying to become more adept at understanding the nature of a query and are increasingly attempting to provide a decisive answer themselves. Now whether they could begin to aggregate data even more effectively and define authority beyond simple indicators (I can imagine Google uses analytics data or PageRank), is another matter.
Best Guess is exactly that at the moment. It is reduced to remarkably basic questions and may not be entirely accurate, based on how recent the data was collected (as evidenced below). Search engines can’t learn all there is to know about every single subject, but they can effectively use the resources available to them (other websites) to gather the necessary information.
This should become more advanced in the future as Bing and Google push the boundaries of a semantic web – as they have been mooting quite heavily in recent weeks. Whether initiatives like Schema.org [see: What is Schema.org Video] may make it easier to understand content, which can then help the engines to provide better results instantly. Best Guess is a small step, and some way behind Bing, but it could certainly lead to bigger things.