Social networks have grown from small, local offline groups of people with common interests, to larger online groups spread across the world. Even the ease of communicating via the Internet can't remove the limit on people's time and attention to maintain multiple networks, though. What's next?
There’s plenty of attention paid towards social networks today, especially due to the visitor volumes achieved by MySpace, Facebook and other newer entrants. As the social networks become even more popular, they change the typical user “web behavior” and the demographic makeup on certain social network sites.
It’s not all about the youth demographics or early adopters anymore. If traffic and time spent on social sites continue to grow, these destinations will compete for the time and attention of visitors on other sites.
The major challenges for both web publishers and their advertisers come from the expected traffic losses as visitors spend even more time engaging with their social networks around specific interests (i.e. business, culture, friends, etc.). Simply put, there are changes underway in the web experience due to social sites.
As a web publisher, it will become imperative to engage with your potential and existing visitors when they are on social sites, and not only on your site. It will also become extremely important to close the gap between traditional web experiences and what people experience today on social network sites.
Online advertisers need to look at their current targeting around destinations and revisit these basic questions: Where will they find their target segments? How will they approach them, when they are on social networks sites? What is the new advertising model and experience? While there’s plenty of exploration lately, these questions haven’t been answered in any disciplined way.
In the very beginning of the social sites phenomenon, advertisers and publishers looked at ways to leverage the social graph of connections found on every social network site. The social graph has brought new meaning to social search and a new challenge to targeted advertising. The impact of various levels of human influence on search has always been present, but the latest developments incorporating the social graph and friends’ actions are creating a buzz:
To answer these questions, we need to discuss how social networks function and how publishers and advertisers can expect to benefit from them. We can begin by exploring social networks, their impact on publishers and advertisers, and where they exist — whether at social sites, your own destinations, or elsewhere online.
Let’s start with a Wikipedia definition: A social network is a social structure made of nodes (which are generally individuals or organizations) that are tied by one or more specific types of interdependency, such as values, visions, idea, financial exchange, friends, kinship, dislike, conflict, trade, web links, sexual relations, disease transmission (epidemiology), or airline routes. The resulting structures are often very complex.
Social networks are driven by people with common interests or affiliations. When we think of our so-called “social circles,” they are typically based on families, neighborhoods, schools, professions, employers, religions, sports teams, or shared hobbies.
Offline social circles are somewhat limited; one may have many diverse interests, but there’s no easy way to connect with others who share them. Generally, those circles are based on live meetings, interactions or gatherings. Once online, however, our networks have changed dramatically.
A decade ago, we began expanding our networks by joining list serves, forums, chats and specific destinations where sharing tools were available. Our connections could happen whenever we wanted and they also became bi-directional. The very act of joining interests groups was born back then.
When web publishers tried to insert these kinds of sharing elements on their own sites, they were sometimes successful. More frequently, however, publishers created unused and abandoned functionality as everyone jumped on the bandwagon to create their own sticky features. It turned out that people didn’t want to participate on multiple sites, at least at a high level of engagement. Social circles were about people first, and not every single and unique interest they had.
Eventually, social networking evolved through connections based on people first and their interests second. What’s different from the earlier networks is that you start by connecting with people first and foremost – and you expect to find them on these large sites. In addition, you have control over people whom you select to join your circle.
These socially-driven spaces created, in effect, a parallel universe that imitated the offline social circles more successfully. While you can connect to affiliate or interest groups too, the purpose of joining is to widen your social connections. What you actually do in these places is share, communicate and understand each others’ interests.
Social scientists are fascinated by the network effects of these explicit social circles, and what kind of influences your circle has on your preferences and interests. Even if that means playing a game or knowing where someone is going for the weekend, these circles are used for all the different reasons we did so offline. Of course as marketers, we are interested in where we should tap into these trusted connections, and what type of marketing method should we apply here.
Social networks like Myspace, Facebook and others gained momentum and critical mass, and as a result they enabled developers to propose applications on their site and new standards like the Open Social have emerged. Open Social initiative will enable services to move more easily among social sites that are proliferating, and generally aims to make connections easier among all the networks. However, as there are finite numbers of social circles anyone wants to join and maintain we are reaching a saturation point. Deja vu?
Implicit social circles are groups of people who are connected and share particular interests, but don’t know they are actually connected to each other and don’t actively maintain their implicit circles. Implicit social circles add a new dimension to the existing social networks, and also solve some inherent deficiencies found in social networks.
Instead of relying on the inherent laziness of people to join and actively share what they are doing, it’s possible to rely on all the navigational and usage streams on websites instead. Through implicit collaborative filtering technology, streams of interactions between web visitors and content help surface the most relevant content and interests for a given cluster of web visitors. What’s more, these visitors or attention communities don’t even know each other, never identify themselves, and never explicitly say what they want.
There are far more attention communities on a given Web site than commonly perceived. By capturing all the clicks on a site, there could even be hundreds of different interests expressed and shared – and these create the underpinning of social circles that get created dynamically.
Web publishers and online advertisers should leverage these networks to optimize awareness, offer content, and drive traffic back to their site. Interestingly, these circles have always been present on web site destinations and should be used to drive better connections and experiences among the site visitors.
Next time, we will cover how social search works, by relying on the intersections of people and interests. Just tapping into the searching that people you have actively connected with isn’t enough. You should be able to key into expert and like-minded people when you are even thinking about or browsing specific interests. And this knowledge should also be the foundation for ad targeting.
Levy Cohen is CEO of Collarity, a community-based search technology company based in Palo Alto, Calif. He has founded several successful software companies, including RightOrder, which addressed fundamental challenges related to structured and unstructured data for enterprise applications.