One of the interesting aspects of social media is that there is plenty of room for innovation. A big part of the innovation is in the area of analytics and insights. By using sophisticated models, one can use the vast amounts of data and provide valuable information for businesses. The big change from the past is that the access to this information has been accelerated dramatically. The information which used to take months can now be available within days. As this article from MIT Solan Management Review points out, brands are still learning how to best utilize the near real-time information.
A recent article in MIT Technology Review talks about a new approach to predict social media success. This approach attempts to analyze social media data from a marketing campaign to predict if that campaign will reach its goals within the target time. This is a common practice for those who use the power of analytics for strategy refinement and to drive business results. Of course, there’s a lot more to social media impact than what is covered in this story.
However, it is encouraging to see that a) there’s active research in the area of social media analytics and b) there’s attention from media and businesses on measurements and modeling.
Assigned to Chrysler’s Jeep and Dodge Ram truck accounts, Harper had to figure out how to correlate whether TV commercials were driving website visits, Twitter conversation and Facebook brand page activity. He also had to calculate whether all that online activity was leading to an increase in test drives at dealerships. “The biggest question with social media is ‘what’s the value?'” he says.
To gauge the predictive powers of tweets and Facebook sign-ups, Harper borrowed the concepts of velocity and acceleration from the world of physics. To come up with those numbers, Harper had to collect data during three phases of a campaign: the baseline, or the number of Tweets or Facebook fans before an ad campaign starts; The Hot Zone, or the main surge of activity during the campaign, and the Fallout, the inevitable decline when the campaign is finished.
Under Harper’s model, which he calls Velocity & Acceleration, the idea is to constantly measure the number of related tweets, blog mentions, and Facebook fan sign-ups during the campaign. By using calculus to compute the velocity, or rate of change, of the tweets and sign-ups, Harper can easily compute any acceleration, the rate of change of velocity over time. Using these two metrics, Harper says he can predict whether a mass marketing campaign will reach its overall goals within the first few days it begins running. The resulting curve typically takes a steep upward slope before leveling off, a pattern known in the industry as “the kick-ass curve.” Says Harper: “The idea is to predict the height of the plateau.”
Picture Credit: The illustration above is from the Sloan article.