|Query Deserves Freshness and Other Temporal Tales|
|Written by David Harry|
|Wednesday, 27 October 2010 05:03|
A Google 'History' Lesson
If there is one area that all SEOs really should know about, it's about how search engines deal with 'document freshness'. In the world of Google, we'd know this in terms of real time/social search and of course, the not so often discussed, query deserves freshness, (a.ka. the QDF). We all know the interest in timely content in the SERPs, but does it end there? Is it all about first to market? Not at all... so let's take a close look.
While going through the latest patent awards recently, I came across a familiar Google offering;
System and methods for determining document freshness
It was interesting as it was previously filed/awarded and this was it's second appearance on the radar. Previously we looked at it's sister document, also a re-release, back in 2008. It was curious that these both had been re-worked. Ok, fine, maybe that part is only interesting to me. A distinct possibility. We can get back to that later.
This became more interesting in that near completion of this post, Ol Matt mentioned one of the series in a GWC video. (He worked on one of the patents in this line - links at the end);
How temporal data plays into search
At first glance I am sure you might be thinking, ooooooh this is gonna be about Twitter and realtime and Caffeine right? But that's not the real deal here. Yes, they have been adapted, but this ride started in 2004, well before the current social onslaught. Let us first take a refresher in what types of data they might be looking for.
What is important to note is that beyond the simple historical publication knowledge, they might also use these types of signals to better understand links, fight webspam and even for personalization. It is certainly no one trick pony.
As an example, let us consider #3 and #9 from above, (Query & Ranking data). For one potential scoring element, we might look at the query history of a term, the ranking history for your page is that space and related click data. We might then ask;
But Dave, WAIT! - I hear you say? That this model of simple collection is totally spammable? Most certainly. Maybe we latch on #4, (link based) and cross reference some data to ensure it's a good match. Obviously link velocity and decay would tell a story as well. You see where we're headed here?
The main point is to always consider how a group of signals such as these might interact together. It also highlights how fast, with so many systems, one can get up to the mystical 200+ (or so? or 300? meh) ranking factors at Google.
Determining freshness of a page
Which of course brings us back to the recent (re) award. How exactly does Google try and determine what is an isn't new out there? To expand on Bill's original round up, items of interest in determining freshness include;
As with any approach we have to consider other elements and inherent scoring mechanisms that may be in play. From what we can see here, there is certainly a likely combination of discovery, crawling (internal site equity), citations and link (velocity). Keep in mind, this is about temporal data. This is about discovery. It doesn't ensure a 'fresh' page is indexed, never mind it ranking for anything of meaning.
The Social Connection
And of course we're all left to wonder; how does social play into this? Right? Of course. We live in a world of wonders (for the old dog SEOs) where getting the content out there is easier than ever. Thanks to the social web. If you're looking to break the latest news, be first to market with a product, launch a new service, social can rock.
What's great about it all is these sites often have some pretty good link equity (Twitter = lots of links in + very few going out). This of course means they are heavily crawled as fresh content + equity means minty fresh crawl rates.
But not only can we increase the temporal discovery rates we can also develop (non link) citation velocity and even hit aspects related to user behaviour. Yes, in theory, this system can use the Google Social Graph to watch various user type interactions for search personalization.
There is even mention of explicit feedback with 'user generated data', (bookmarks etc..). Personalization is an interesting potential use for this... Anyway, yes, there is certainly some ways it can be used for social (makes you wonder why Google's realtime search isn't better... huh..)
Other handy SEO tips
At the end of the day, we want to learn something from all of this. Before we get to some tips, let us consider again the QDF. It is important to understand that some query types/spaces are going to react differently than others. Sometimes it can be obvious (historical documents, past events etc..) that haven't had fresh activity. Other times, not so much. This will be part of the art of SEO. Getting intimate with a query space to understand the dynamic.
Some spaces are more prone to the QDF than others – know the differences. Beyond that, here are some simple take-away items from this or any related approach;
More than meets the eye
As always, I am passing along these tidbits to get the gears in motion. To help SEOs think beyond myopic thinking of links, links, links.. Yes, this area as with most, has link relations, but there one can see the rest of the forest as well. Take all that we can learn from this and put it back into the SEO stew. A deeper understanding of temproal elements in search can only help you build smarter programs.
I hope you enjoyed the ride... leave any questions/thoughts in the comments and we can continue the dialogue.
Past Google Patents of Interest;
|Last Updated on Thursday, 28 October 2010 05:40|
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