If you've been keeping abreast with social media, there is nearly an infinite number of ways to leverage all the data in new and interesting ways. One of those uses is
in the personalization of the Web search experience based on the social graph.
But what does this mean and why should we care?
From the days in which Google started the paradigm shift in the search market, the refinement of search has been driven by the growing amount of global information. From graph mining, to deeper text analytics, to user search patterns, all of the mechanisms have improved our ability to get acceptable results quickly.
But with the advent of social media, there are new and interesting ways to take search to a
personal level. Your social networks provide personalized views of what's contextually relevant to you, based on what you and your friends have expressed as interesting. Relevance to you
and your friends can be recommendation-driven based on your Likes, +1s, Shares, and Retweets. Or, it can be mined directly from the conversations and discussions you carry.
Will this mean the Web experience becomes fundamentally different?
The way that Amazon has personalized your buying experience is similar to the future possibilities of a personalized Web. Not only will we have the choice to search for information in the way we've grown to love, but we'll have a Web-scale recommendation engine to enable new ways for us to discover and surface information we might not know we should be looking for.
What I find exciting about these possibilities is its extension of how we can interact with the growing content that's out there. Search has always, and will always, give us the capabilities to look for information that's out there. We will always need the flexibility to extend beyond ourselves and our friends' interests, ask new and novel questions of the Web and find information independent of our social network.
Social search takes us down new paths of answering the question "What
should I be looking for?" and "What don't I know to ask?" By applying context derived from our local networks, we can be more confident that social search-driven recommendations of content not
expressly asked for will be interesting, engaging and often serendipitous.
What is the impact on brands?
For brands, this brings up a unique and difficult question. If everyone has a personalized view of the Web, how do we actually assess the impact and visibility of owned, earned or bought media? Especially when our consumers are presented with an ever-changing and highly dynamic localized context.