You can vote up listings you like and leave comments, and vote up or down other peoples comments. All your edits can be tied to an account profile, which provides some level of protection against the Bot-people.

I think the biggest flaw in this type of system is the need for the user to stop what they are doing and then do something else. So most people will not be providing feedback. Google really need to collect that data as people are going about their business, and with personalisation that is happening.

Having said that, like Digg, there will be certain community experts who will take it upon themselves to police their areas of expertise, and you don’t need many of these to provide another valuable signal.

In the Financial services sector at least, I’m seeing Google placing different sites at position 4 for anything from a few hours to a day. These are usually sites that are normally outside the top ten, and in one case outside the top 30.

Position 4 is usually reserved for News results – almost like a place holder, and now it looks like Google may be using it to test user reaction for sites Google want to know more about.

It was inevitable that Google would increase reliance on user data – in areas like Financial services, especially car insurance, where it would be very difficult to differentiate based on the usual on-page and link factors – user data seem to be the only logical evolution.

I believe all this is not entirely new, the reason for the success of aggregators can be credited largely to how sticky they are. A Good aggregator can command a conversion rate of 30-50% which makes them very sticky, when you think how long it takes to fill out a insurance/mortgage quote form.

But position 4 testing is definitely something relatively new. The next few weeks should tell us how/if they use this test data.

Last week a friend asked me about lijit – a kind of social search engine based on Google custom. So, I started reading about it and the next thing I know I’d installed it on my sidebar. Wow! It was like a spiritual experience in user experience. I was reading one minute bought into the whole idea the next and a couple of clicks later I was there.

So how does it work – lijit enables you to search this blog and if what you seek is not here it’ll pull in content from other places I’ve contributed – Digg, delicious etc… If it’s not there, it’ll then look at the blogs I link to and the places they’ve contributed. You can even upload an RSS reading list. Fantastic!

The principle is based on ask a friend or friend of a friend – and relies on mutual trust within these mini circles. The depth of search is limited to your immediate friends, but things could get more interesting if this caught on with more people installing it creating deeper searching.

And unlike the doomed Wikia search launched last month, this doesn’t require me to do anything different, other than install it and carry on with business as usual.

Might not be a Google killer, but a simple idea well executed and I’m finding it more useful than a regular blog search box.

Nice one!

For any commercial searches (You know, the ones with lots of spam) nearly all the top 10 are littered with keyword rich hyphenated domains. On a search for ‘cheap flights’ it even pulls in a picture of some bloke, just cos he said he’s interested in cheap space flights.

The ‘search engine marketing’ SERP was like a journey back in time. There were sites in there that Google, hell even Yahoo kicked out years ago.

And no real sense of Geo targeting or localisation – guess we won’t be using it to find loans or mortgages or any local business
Ok I’ve got it – this IS like a very basic search engine and indeed it is based on the open source engine nutch. Great at basic on-page relevance.

The clever bit comes once the user base start to provide their expertise. This may yet do something useful or at least vaguely interesting but I’m not holding my breath. I love the idea of using social signals to drive search, but this is not going to fly anytime soon and I’m guessing never. No wonder Matt Cutts was happy to welcome them into this space

But during this year, one thing that seemed to have stayed stagnant is search. At a time when people power dominated and shaped everything from how we communicate to make purchase decisions, to most people search engines seem to be lagging behind – leading some ‘experts’ to declare the death of Google.

So did Google stand still? Well I’m confident they didn’t. But before we can look at where Google is at and where they’ll likely end up – it’s worth looking at some Google history and some of the barriers to social search.

Most people think that Google’s primary contribution to search was the use of linkage data to judge reputation. But a bigger contribution, the one I believe is the reason that I’ll still be Googling to my grave is the technology and methods they developed to scale and efficiently deliver information to where ever you are. Add to this a ranking method which can be swapped in and out like a removable hard disk – and you have the infrastructure for longevity. Oh and let’s not forget Spam – not something to be taken lightly.

What’s up with the algorithm
Link reputation has served us well, but letting the published community define reputation and relevance over the people that consume that content has limited appeal. More about that here – From link spam o user data

As reputation dominates other factors in the ranking game – Is Google constantly pointing us into the ‘head’ of content on a given topic. As Chris Anderson pointed out in his groundbreaking book The Long Tail, what’s the point in having a tail if you can’t get to it?

User driven recommendation engines like Amazon and Last FM do this very well but can Google really reach those parts – or maybe that’s not what we want out of our reputation system? A navigation aid and nothing more.

Developments this year
People write search algorithms not computers. So you could argue that Google like all search engines were already influenced by people. It’s just that those people worked with the data available to them.

Personalisation ramped up
Using search history and other signals from user data such as bookmarks and content saved in your Google home page is a move towards employing more user data to judge relevance and more importantly query context or intention. But the use of data is confined to the individual.

Blended results – Google universal
On the face of it blended results seem more an aid to navigation than anything else. I.e. save people having to explore vertical indices to find what they’re looking for by attempting to understand and deliver vertical results into regular Google. Danny Sullivan introduced this concept more than five years ago and called it invisible tabs.
But the really interesting development her e was the ability to use popularity data in verticals in order to be able to identify when a vertical result is relevant for the masses. Google can identify if a news story is relevant for regular result in less than an hour of publication.

So we’re starting to see the use of user data in quite a big way already within Google.
Search 3.0 – blended and vertical http://searchengineland.com/071127-091128.php

Google Knol

http://searchengineland.com/071213-213400.php

Of course, Manber did say that Google could better tell which of the Knol pages were of high quality by looking at signals such as ratings.

Going all the way
So what stops Google from using user data to refine search results in a more direct way – Spam (remember the Direct Hit Algorithm) trust in everyone’s opinion is just one of the issues.
However Google is already using popularity data to determine search quality. All clicks on a results page are tracked and high recall rate can be used for further tweaking.

Toolbar data and even ISP data could be used to determine the relevance of a site to a given query. But if Open standards like OpenSocial and OpenID are adopted on mass then many of the Spam and trust issues could be overcome through the use of personal reputation scores like personal Pagerank. APML will no doubt play role in enabling people, content and behaviour to be connected in one seamless network or as Tim Burners Lee refers to as The Graph.

One thing is for certain, we are unlikely to see a set of open standards designed by committee and adopted by everyone to take us to the next generation of the web (Semantic web). We are more likely to see adoption based on the need for attention and economic growth. Until one day we’ll find that we’ve arrived. Just like when O’Rilley coined the phrase web 2.0 – no one planned it or named it – things just emerged that way.

2008 will be one of the most interesting years, not just for search but for the internet. Technology was never the limitation – people will ultimately decide how, why and who they wish to connect and engage with – marketing can only follow.

guns don’t kill people, rappers do

The last time I felt that Google was this open to abuse was probably ‘just’ before the Florida update of November 2007. Though, I’m sure this isn’t likely to happen anytime soon, the time seems ripe for a major shift in thinking.

Using connectedness to judge reputation and relevance was a revolutionary concept in 1996 but things have to move on. The problem with this approach is that relevance and reputation are defined by the published community.

A few years ago, a Google engineer pointed me to a problem – a Google results page for a search on ‘Table’. The first few organic results were about HTML tables, followed by a premiership football table followed by a periodic table and more html tables. Unlike the paid listings which were entirely dominated by furniture, the natural listings didn’t contain a single result about regular tables.

The reason was obvious, there are no published communities discussing furniture. Looking at the same SERP today, things really haven’t moved on.

A recent post by Dave Naylor considers the possibility of using Google ditching link data and factoring user data instead. I think he’s onto something. There is nowhere left for the algorithm to go other than to consider the user. And that’ll be a hard algorithm to Spam.

As Google continues to rollout Google Universal, the search industry is starting to wake up to major shake up. The placement of content from other Google products within the main natural search results creates a host of issues – all of which is yet to unfold.
So, what are the main concerns

• For commercial queries, insertion of media and image listing will push your rankings further down the page. And if the searcher was really looking for ‘shoes’ and not the YouTube video, the top results are likely to get even more clicks.

• Google get’s to push more Google content.

• Increase adwords revenue

• For a brand – a brand search is going to expose a lot more about your brand than the affiliate listings. Having a search strategy which looks to owning your brand space across the Google network becomes even more important.

• Affiliates and anyone bottom feeding on brand traffic is going to find the going getting tougher.

So what about the end user? Depending on the type of query which triggers Google universal, you could have a great user experience or a very poor one. Many of the other engines do offer related content for specific queries, but these are generally kept out of the way. This is a very bold move by Google, and guess we’re all going to have to wait and see till it’s fully rolled out.

Wales doesn’t know how his search engine would combine human intelligence and technology. “We really haven’t determined how all of this is going to work,” he said.

The idea of using people to refine relevance is nothing new and isn’t something that has gone unnoticed by nearly everyone invloved in search. Afterall, there’s only so much you can do with link analysis. Yahoo! has already ventured into social search with MyWeb, where people can tag and save results.

But are the Wiki-guys best placed to develop a search engine – I’m not convinced. Even if they were able to develop the ranking method, execution on scale is not easy. Google’s success is largely due to solving that problem. There’s been many search engines with good ranking methods, which simply failed due to poor scalability. And I just don’t see these guys building a search engine in a couple of years that has the same crawling and indexing capabilities as Google.

A better way forward would have been for them to collaborate with one of the majors. Yahoo! has already started to play with social search, and I’m sure Google have their plans. Social search is one of the most exciting things waiting to happen, but I really doubt that the Wiki-crew is going to deliver that promise anytime soon.