Reading beyond the obvious

As a regular user of Google Reader, I was happy to see that a couple of weeks back, Google deemed it important enough to carry out a few changes – a ‘like’ button, the ability to follow specific people (using Reader Search), and friend groups (with customisation options of who sees what content). The public nature of the ‘Like’ button meant that sharing on reader got a lot more social, though it had its share of detractors too.  Many complained about not wanting to see “likes from the unwashed masses”, Google corrected it by adding an option in the Settings, so that if you so desired, you could only see the ‘Likes’ by people you followed.

As a regular user, I’d say that people who give only partial feeds stand to lose out a bit on the ‘Like’ part. It would also be great if the time lag between publishing and the post appearing on Reader could be reduced. As a publisher, I wish Google would tie these social features in Reader with Google Analytics, so that I can know who shared/liked my posts. One way to know the number of ‘like’ is to subscribe to your own blog, but I’m sure that Google can make it easier if they want. Then maybe a plugin that can show these details on my post (at the site). Much like the Tweetmeme plugin I have installed on my other blog.  Speaking of Tweetmeme, according to Venture Beat, the button is now shown more than 50 million times a day across the web. It has its share of competitors, and is even threatening to sue one.

That number gives a rough idea of why Google want a piece of the sharing pie. In fact, this chart, created by AddtoAny (the same guys who gave us that awesome widget at the bottom of my posts) shows how sharing happens on the web. Facebook leads, followed by email and Twitter. Google, though dominant in search, would be looking closely at specific competition – the Yahoo-MS deal and how Bing’s interesting games shape up. But more importantly, it also has to keep an eye on how generic search and sharing (social) are changing and shaping each others’ future. Twitter just got itself a new homepage, and ““Share and discover what’s happening right now, anywhere in the world”  clearly shows the intent. I thought it even answered, to a certain extent, the oft heard question – “But what do i do on Twitter”. Call it discovery/recommendation/trend, but it is just a different perspective on search. And its not just Twitter, Friendfeed recently added a feature – ‘recommend friends’. No, silly, not the Orkut/LinkedIn type, if you feel your subscriber would also like the feed of someone you subscribe to, you can share it easily. Though its nothing radical, its helpful for new folk.

The Nielsen Global Online Consumer Survey shows recommendations (from known people) as the most trusted source of advertising, at 90% and consumer opinions posted online at 70% next. Among Indian audience, recommendations top, but editorial is placed second. A post on Six Pixels of Separation blog talks about how the next ‘Google’ will be a referral engine, which ranks website not basis text optimisation, but basis what people have said and done there, and how the information there has been used by people. But there are challenges there too as such a system needs to incorporate relevance, immediacy, trustworthiness and have an interface that will display it in the most intuitive, easy manner possible. This post on RWW discusses the concept of Social Relevancy Rank, with five layers, where search results on streams (like Twitter, which already have real time) will be arranged basis relevance to your social graph. Friendfeed does this and provides more options in Advanced Search. The post also suggests ‘friends of friends’ as the next layer of results, and a concept of ‘taste neighbours’ (a mining of ‘people who liked this also liked’) after that. The last two layers are made of influencers and the crowd aggregate. In fact, I thought, maybe a possible visualisation would be to actually have all five layers arranged vertically side-by-side and a thumbs up/down button by the side of each search result, so that each user can contribute to filtering. Is this a perfect method? No, but then neither is Google’s Page Rank, as the author says. Which perhaps is why Google, while it is master of the algorithmic search, needs to experiment with Reader and see if it can create a social layer on top of its Page Rank search system. A new system that also incorporates the data from likes and shares beyond the optimised keywords, and is able to operate in real time too. Possible? That would be fun, and would even take Ad Sense to a whole new level. 🙂

So what does this mean for brand and marketing? Beyond mastering the algorithm, optimising all the queries, mining all the data and connecting it, how does differentiation happen, other than the obvious product possibilities? This very interesting article (via @vijaysankaran) discusses the battle between art and algorithm. Amidst the quest for perfect targeting, and the smoothing out of our search experience, we might be losing out on serendipity. The  author goes on to say that in this ‘end of surprise’ is the opportunity for marketing – to deliver revelation along with relevance. The perfect  of left brain analytics and right brained creativity and emotions, which seemed to have been lost somewhere in between.

until next time, search and socialise 🙂