Long before modern technology, conversations were monitored to gain insights on popular trends. The conversations around various French university pubs and cafes in the 1780’s forewarned the pending revolutionary changes about to take place. During the industrial revolution, privileged men in country clubs shared information about up-and-coming companies for stock tips. Anyone can be an accurate prognosticator of future trends by listening to the right conversations.
Unfortunately, access to these conversations has always been limited to a privileged few throughout most of history. That was until the recent advent of social media. Now, billions of conversations are accessible through technology. The problem no longer is about getting access to conversations, but finding the relevant ones amid the enormous clutter of noise. The late 18th century French university pubs were obvious places to hear the ideas of a revolt. Within the social data set how can you find the “country club” conversations if you are a hedge fund manager looking for sentiments on different stocks?
Social media is a universe of unstructured data that can be overwhelming. Understanding the general sentiment of conversations or changing daily volumes are only superficial information compared to what social media has to offer. Moving forward, the industry will introduce better ways to structure the social media data set for deeper insights. We will better understand the right “places” within social media to uncover leading indicators on any particular topic. That is why the social media data set offers such promise of predictive capabilities.
Currently, the social intelligence/analytics industry is still immature with only a few new compelling concepts reaching the market. Our social intelligence group at SDL has just launched a framework by which you can measure the customers’ commitment to a particular company’s product(s), brand(s) and content. By measuring the social conversations within this framework, we can provide data-driven insights that help marketers be more effective.
No doubt others will follow and come up with their own frameworks and algorithms. Meanwhile we will continue to try to lead the market with improvements and innovations of our own.
