What’s social media good for? Marketers see it as a new way to engage with consumers. Economist turned advertising executive Jason Harper sees an additional function: as a real-time laboratory for measuring how multimillion-dollar ad campaigns are succeeding or failing to drive product sales.
Armed with a master’s degree in applied economics, Harper was hired three years ago, at age 30, by the Detroit office of Organic, a leading digital ad agency, to crunch campaign data for car companies–with the goal of seeing whether digital marketing efforts were helping move vehicles off lots. Assigned to Chrysler’s Jeep and Dodge Ram truck accounts, Harper had to figure out how to gauge whether TV commercials were increasing website visits, Twitter conversation, and activity on Facebook brand pages. He also had to calculate whether 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.
Instead of waiting to measure the value of social media after the marketing campaign was over–akin to looking in a rear-view mirror–he saw a way of using social media to foresee turns in the road ahead, to predict whether a campaign was on target to meet sales objectives. The approach caught the attention of Harper’s new boss. “We needed some predictive tools,” says Steve Kerho, senior vice president of analytics. “To hit [Chrysler’s] sales objectives, we needed to see this many site visitors, this many key activities, this many scheduled test drives.”
To gauge the predictive power 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, he 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 and 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 calculate any acceleration–the rate of increase in 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.”
The model came about during his work for Chrysler. Harper homed in on how Jeep’s TV commercials were driving traffic to the “Jeep Experience” website, as well as the rate at which the website was triggering sign-ups to Jeep’s fan page on Facebook. Then he tried to see if the social-media activity had any effect on the number of test drives. Using statistical-analysis software from SAS Institute, Harper came up with a correlation: consumers who engaged with one of Jeep’s online touch points were about twice as likely to schedule a test drive at a dealership. Since the auto industry is so focused on increasing test drives as way to reliably boost car sales, this was a promising start.