I was inveterately tweeting the other day – as is my wont – and I came across this tweet by Dave Naylor. If you type “Google Ireland” into Google.co.uk – the Google.co.nz site shows up as the top result (click to enlarge).
The same happens if you type “Google South Africa” into the Google.com search engine.
Clearly the Google Algorithm is a bit confuzzed. Alternatively Google New Zealand have a back door into the global algorithm.
TechCrunch put up a brief post about this.
This reminds me of a post Danny Sullivan wrote last week. At SMX East they had a discussion with Google’s Sergey Brin, regarding “bad search results” being served up by Google in its SERPS. "Bad search results" here referring to search results which are not relevant and do not correlate to the searchers’ intent.
The most telling example they referred to was Google’s own ranking for certain keywords. For example, when you search for “Search Engine” on Google.com you get this result:
It suggests that Google rates older search engines (like Dogpile) as more relevant for the term “search engine” than it does the largest and most dominant search engine in the west: Google Itself.
This points to a larger issue though. To quote Danny:
“…much of Google’s algorithm seems to reward sites that have gained trust over time, regardless of how relevant they seem to a particular query.”
We can agree that any search engine results are probably going to present – at best – an approximate response to a searcher's intent. Google – so far – has done a very good job of guessing relevance and presenting relevant results.
However, going forward, if Google is going to respond effectively to the emerging search challenge presented by social networks (and their real time search engines) – it’s going to have to untie its algorithm from what seems to be an unhealthy dependency on time-based history. Instead, it will need to rate results increasingly on a truer approximation of relevance, based firstly on search intent and secondly on here and now realities.
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Very interesting. I'd love to see more info on how they rank importance vs relevancy vs usage data...
Posted by Tim on 2009/10/16