So amidst all the hype around Bing, I gave it a whirl, to see if it really was all that and a bag of chips. Yes, it’s pretty. And yes, it’s got some nifty little features (although I personally detest the auto-play of videos on rollover – is clicking really that hard?). But few would disagree that Google’s pretty much nailed the issue of effective and efficient search (leaving aside the challenge to its hegemony posed by the likes of Twitter in real-time search). And I can’t see that the most important thing about Bing is the name itself – even if it is a backronym for But It’s Not Google.
Although the exact components of the Google algorithm are notoriously secret, it’s well-known that the number of links to a given site, and the quality of those links, is a core driver of PageRank. Which is great, although the wisdom of crowds isn’t always tremendously wise – it can be gamed and it doesn’t have the intuition to know what you’re after.
Which is the inherent issue with search. You query, it scrapes and brings back the results. Great, but often the real value is in find, rather than search.
As this article in Business Week highlights, we need human filters to find information for us, to add value via recommendation:
The value of most information has collapsed to zero. The only scarce resource is attention.” So how do we figure out where to direct it?
The easiest way is to get tips from friends. They’re our trusted sources. At least a few of them know us better than any algorithm ever could. Little surprise, then, that the companies most eager to command our attention are studying which friends we listen to.
One of my former clients was a well known telecoms enquiry provider, and central to their core proposition was the value of find vs search. But even intelligent search doesn’t have the value of a truly curated find from a trusted source. Google Squared is admittedly seriously bloody impressive. It scrapes the web for “data structures on the web that imply facts”, to structure unstructured data and give you a table of organised results. Companies like Mahalo, and indeed my former telco client, position themselves as providers of human-powered search, whilst Wolfram Alpha describes itself as an answer engine. These are all well and good, but an engine can’t (yet) make truly personalised recommendations the way a likeminded friend can.
Engines like Aardvark are trying to offer personally relevant recommendations – by harnessing your own friends, so it’s essentially a redirection service. Aardvark users add the service to their email or IM buddy list: you can then email or IM it a question, and the engine checks your network of participating friends (and friends-of-friends) to find someone who might be able to answer it. But friends must have signed up with Aardvark to be considered, and they can control whose questions come to them, and when. OK, it’s early days – as of April 2009 they claimed 10,000 users. But at the moment this social search engine is still just a connection service – matching you with someone who’s willing and able to answer your question in real time.
The value of influencers within social networks is huge – hence why the likes of Google, Yahoo and Microsoft are investing heavily in teams of sociologists, anthropologists, and microeconomists to better understand who we trust & pay attention to, how and why. But as research from Facebook’s friendship laboratory shows, the most valuable interactions depend on reciprocal relationships:
To rival the power of human find, the killer engine would have to be able to sift through data to find the most relevant results for us, based on its understanding of our likes, preferences and behaviours. And there’s the rub. To do that we need to engage in a reciprocal relationship. The more data and behaviour we share, the better recommendations we’ll get back. But it’s a very different matter to share this level of personal information with companies – who will ultimately look to monetise their offering – than with our friends. We want to have our cake and eat it. We want an engine to understand what we’re after and provide us with exactly what we’re after – but we’re not (yet) comfortable with giving out the information the engine would need to achieve this. It’s an incredibly fine line, but the company who’s able to crack it and truly harness the power of personalised find will really move search to the next level. Within this context, for all its claims to be a groundbreaking ‘decision engine’, doesn’t Bing feel rather more like a gentle hop in the evolution of search, rather than a revolution?