The social graph has brought new meaning to social search and marketing. Your contacts and friends are certainly one source of search relevance and subject authority, but are they the best source?
Last week, in “The Evolution of Social Networks,” we described some of the challenges facing web publishers and online advertisers, considering the proliferation of social sites. We also introduced the notion of attention communities, or circles of people that implicitly share the same interests through their actions and content consumption. Both explicit and implicit user activity could drive better search results, recommendations, and ad targeting on social networks and on destination sites.
Today, we will cover how different flavors of social search work, and the implications for publishers and advertisers.
Why Search Wasn’t Always Social
Search has evolved from a way to address the fundamental challenges of finding a particular item, to become a method of finding the most relevant content out of a sea of possibilities. In the early days of web and site search, the focus was on guaranteeing that “all content” was searchable. The focus started shifting to relevancy as more and more results arrived on the search result pages and spam content found its way to the head of the results.
Until recently, search technologies considered the relationships between pages and content on a site and among sites – and the human factor was left out. That’s beginning to change, as we recognize that even in the “linkage” era, we all know that search page results are driven by people who have linked to sites – and they are influenced by whoever markets or provides link love as well.
Additionally the huge SEO practice around web sites and affiliations add another semi-social element into search. These SEO efforts and automatic discovery of link topology aren’t about true authority, but about the publishers who have optimized specific topics and categories to attract the search engines best.
Find What People Like and Value
Some companies have identified the people factor and offer more human-driven search engines. One approach is to let experts find results and classify content for every possible answer. There are scalability challenges inherent in this approach, and it is not clear if it will yield better relevancy in the result set. Some argue that this approach could be valuable for specific verticals or content segments, but even there it is not clear how publishers and advertisers would benefit from it.
Another approach deploys the social graph as part of the search. The assumption is that if I rely on the searches and their content consumption of my friends/contacts, I will get better search results and recommendations. This approach has many drawbacks: your contacts are not experts in all subjects, they are not exposed to all possible content and sources, and they are limited in number!
A third approach adds the implicit interaction of people with content as the foundation of social search. This approach leverages the benefits of the intelligence and knowledge that people implicitly show when they select content – without adding any burden on the users and without invading their privacy. Leveraging implicit communities with similar interests has many merits to all parties involved:
- Web visitors enjoy connecting to a pool of interests that could be either their expert advisors, or a pool of like-minded people that share content they have selected before.
- Publishers can now optimize their content based on the formation of these attention communities.
- Advertisers can target anonymous segments of visitors based on their true interests.
Real Opportunity is More Organic
An important assumption behind the “implicit communities” approach is that when people are able to share interests without explicit sharing, it becomes more effective. Implicit communities are organically created, based on the way a web site’s visitors interact with a site. Studying these implicit communities can lead to new ways of surfacing the right content to the right people.
Community is a term that’s loosely used when publishers think about their site visitors – or when they think about social environments where they want to target potential visitors. Some publishers understand they have multiple communities and they make work very hard trying to gauge them and define them through site taxonomies. Other publishers think of their sites as having core personalities and visitor attributes, defined by demographics and categories.
Publishers should understand they have many communities. There may be some common attributes, but a surprising range of dynamic and evergreen interests as well. Social search helps to uncover and tap into these communities more easily, using collaborative filtering and other technologies.
We’re all familiar with Amazon-style recommendations, where your history is known, and related products are shown to you. With current implicit communities, what’s different is that effective results don’t require registering or identifying the user and thus are relevant on more types of web sites.
Why Implicit Communities Matter for Monetization
Web publishers often create simple profiles about their destinations for ad sales purposes. However, the real monetization opportunities will come from making all their implicit communities useful to both site visitors and advertisers. In reality, many different attention communities exist in harmony on each site – and the footprints can be found throughout the web in implicit social circles.
Even on social sites with explicit memberships, there are common and implicit interests among people who share the same music video or other content interests, but don’t know it because their circles don’t cross. Implicit communities are based on actions, rather than on declarations or any explicit social graphs. They add an important and new dimension of opportunities for web publishers and online advertisers. On a practical level, let’s consider some potential monetization opportunities based on these circles, or attention communities:
- Serve behaviorally-based ads, which harness implicit circles already present on your site. That way, you’ll be able to drive far higher content consumption and clickthroughs.
- Improve your search marketing by using the intelligence of your site attention communities. Instead of endless query streams, check what keywords appeal to specific social circles and use them to make your buys more efficient.
- Refine your web publishing strategies. You’ll know what appeals to your circles, and be prepared for some surprises. From there, it’s possible to make far more informed decisions about which content to create or products to offer or promote.
- Examine content consumption patterns. If you know what appeals to specific attention community or circle, then it’s possible to recommend other articles, videos or products that appeal to them. Before, it’s been an expert guessing game.
- Syndicate your content to social sites or other sites. Remember these sites also have their attention circles, too. They are a great targeting opportunity to match content with the right audience, anywhere the audience lives.
We’ve discussed several possible approaches for general web or site social search. We explored the competitive advantages from leveraging the implicit communities that form on any site. Also, we showed how you might benefit as a web publisher or an online advertiser.
Next time, we will further discuss how you can use social search technology to maximize all types of ads, and revenue too.
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.