Word-of-mouth literally occurs all around us. According to the Keller Fay Group, a projected 3.5 billion brand-related conversations occur every day. These conversations influence the brands we buy, the restaurants we try, the books we read, and the movies we see. If you are like most consumers, odds are you asked a friend or neighbor for their opinion on everything from the dentist you use to where you get your car repaired and your hair cut. In fact nearly 80% of consumers say they trust recommendations from family and friends over all other forms of advertising and marketing.”

While the importance of social influence in marketing is clear, the fleeting and random nature of word of mouth communications has made it difficult for word of mouth to scale beyond an individuals personal network of relationships. Consequently, over the last half century, mass media has aggregated ever larger audiences. As a result,  the one-to-many, mass marketing model has largely replaced word of mouth as the most prevalent source of information and advice in shaping purchasing decisions.

However, with tens of millions of consumers now participating in online social networks, the potential exists for word of mouth to scale in ways not previously thought possible. According to an October 2008 Forrester Research report by Josh Bernoff, “three in four US online adults now use social tools to connect with each other.” These social networks allow word of mouth to be amplified far beyond its traditionally limited audience.  The implication for business is significant because customers will now have the ability to share their experiences with millions of consumers.

We are all part of many societal groups (e.g. friends, co-workers, neighbors, schools, religious, family etc) and within these groups there are both influencers and connectors who facilitate the exchange of information. Today, these conversations are both unstructured and fragmented which makes sharing them on any scale difficult. Technologies, like those being developed by Buzfactor,  will not only increase consumer access to to this highly valuable content but also dramatically increase the likelihood these recommendations will be shared well beyond our personal network of relationships. The impact this will have on traditional media will be profound because, very simply, we trust our friends and neighbors more than we do advertising.

Billions of word-of-mouth conversations happen every day but less than 10% occur online and only 1% (see “Word of mouth goes far beyond social media“) are currently exchanged via social media such as blogs and social networks. The nexus of real-time search and social networking is about to change things and, as a result, we are going to need new ways of storing, searching, and sharing word of mouth as it is increasingly captured and exchanged in the form of online recommendations and reviews. As Greg Sterling points out in a recent post, “the ability to efficiently ask many people for advice or a local business referral at once online is new.  Reviews were step one; the combination of quasi-real time answers and social networks is an evolution of that phenomenon.”

The search interface today is simple, powerful and effective, however, the “one size fits all” approach is beginning to show its limitations. For example, modifiers such as “best” are often included in search queries, however, depending on the situation, “best” has many different meanings.  Using restaurants as just one example, the search for the “best” choice is simultaneously influenced by many factors including time of day (lunch or dinner), occasion (business or social), group dynamics, or even weather (outdoor seating hardly works in Boston in January).  And while search engines have made great progress toward localizing information, it’s important to remember localization is not personalization. This is where our individual social networks will come into play.  Moving forward, I believe our personal network of relationships will help create new, more meaningful ways to organize and filter content and provide the context that search lacks today.