The Social Web – Have We Arrived?

Description from the Social Media Week New York schedule event listing:

Often labeled a fad, a buzzword or a mystery, the notion of “social” on the Web is at the heart of many misconceptions, and with good reason. The definition of the social web continues to change in fundamental ways. There is already evidence that this year will mark even more change, as people look to connect more seamlessly around Web content – articles, photos, videos and more – no matter where they are on the Web.

These connections around content will define our social experience, and they represent a tremendous business opportunity for website owners, publishers and advertisers . For the first time, the traditional idea of an algorithmic-driven Web experience, where content is primarily found through search, is challenged by a people-centric Web experience, where it is discovered through shared connections.

Meebo will lead a discussion on the changing definition of the “social Web.”  This conversation will explore whether the social Web has truly arrived, how people are currently using it and what website owners and brand advertisers need to consider when they think about the social Web and their target audiences.

Speakers:

  • Martin Green, COO at Meebo
  • Moderator: Brian Morrissey, Adweek
  • Gerard Grech, Global Head of Content Distribution at NOKIA
  • Chris Phenner, VP of Business Development, TBG

Event Recap:

The crowd slowly trickled into the Business, Media & Communications content hub, and quickly moved to the coffee carafes.  Ben Schein welcomed the audience to day two of Social Media Week New York and introduced Martin Green, the COO at Meebo, to open the panel with a presentation.

Social media has helped people come together and created a constant (often too constant!) connection to people that we know.  Green sees the future of the social web as social discovery.  Pandora and Netflix are two examples of current services that suggest new and relevant content to users based on algorithms and user preferences.  What if the web worked the same way?  What if we could filter new content and new information in this same fashion?

Initially, sorting web content could be sorted by people, but the sheer volume of content quickly outpaced the ability for a human to keep up.  The web then graduated to search engine algorithms.  While the search engines can keep up with the explosion of content, they fail at delivering context.  For example, Green as a road cyclist comes at a search for “cycling” from a different angle than a casual biker.  Context has been introduced through social sharing, but this is still not a perfect solution.  Our friends are a limited set who may or may not share the same interests, and even those who do are rarely the experts in the field.  The trick is to find a way to access these similar-interested experts.  If we can connect us with these disparate people, then a real discovery engine could be developed.

Green’s goal is to move from an algorithm-centric web to a people-centric web.  He sees a future where we visit sites that connect us by interests.  Logins for these kind of sites would only need a simple gesture (a Facebook Like, retweet, Pandora thumbs up, etc) and could judge our interests and perception shifts accordingly.  From a marketing standpoint, this would allow brands to build deeper relationships with their customers, and from a social standpoint, it would connect us with new individuals with the same tastes and interests.

Brian Morrissey of Adweek assembled a panel to continue to discussion.  The web has changed from Web 1.0 as it has moved from anonymity to personalization.  While much of the discussion this week is based on social media, it’s important to look at the larger “social web”.  Green, who had joined the panel, spoke about a few challeneges that the development of the social web is facing.  Data is siloed (music on Pandora, movies on Netflix, etc.), technology only develops so quickly, and people need to develop a comfort level with sharing.  Just as consumers have grown comfortable with Amazon making purchase recommendations, it’s likely that online behavior will develop to accommodate content recommendations.

Gerald Grech of Nokia sees mobile and mobile applications as an emerging growth area for the social web.  Some apps, like a “Gig finder” that recommends concerts based on the music on your phone and your current location, offer opportunities that were not possible on a desktop.  Still on the topic of changing paradigms, Morrissey asked Chris Phenner of TBG what happens when Facebook moves from a network to an environment, and what happens when a Google-centric world becomes a Facebook-centric world.  We’re moving to a world of sorting by graphs, be it Facebook’s open graph, Hunch’s taste graph, and so on, but the concept is still developing.

Morrissey believes that the principles of graphing are similar to those in search.  Search is perceived to be more effective than social sharing right now, though this may just be because search has had a head start.  One definite advantage that search has in driving conversions is intent; search requires an active role by the user, so they already likely have a purchase intent.  To facilitate conversions, Green prefers directed advertising on focused blogs to advertising on Facebook, as the visitors of the blog are likely to have stronger purchase intent while browsing.  Phenner sees an advantage to reaching out to consumers on Facebook, because the data sets are large enough to find correlations between behaviors.  This allows marketers target preferred groups for conversions.

One tool going forward that takes advantage of both the segmentation of the targeted blogs and the data of the open graph is the Facebook Connect application.  One Connect implementer that benefits strongly by using this is the new website that’s looking to build an audience.  Letting people authenticate without having to sign up for a new username and password lowers barriers to entry for that consumer.  Another implementer that benefits is one who wants to use the granular graph data to find potential customers to reach out to or upsell.

Analysis and Commentary:

Every conference in this space has panels that cover the move from search to sharing.  I think that the key takeaway from this panel is that the future of contextually-appropriate sharing will borrow from more services that just Facebook, Twitter, and Digg.  As in many panels that we’ll see this week, speaker engagements are as much sales pitches as they are prognostications.  As long as you understand the biases, it’s an excellent opportunity to take advantage of the experience of the speakers.

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