Superbowl Ads and Big Seed Marketing Theory
In this article and podcast, Yahoo! Research scientist and Columbia University professor Duncan Watts explores an alternative to the volatile “viral marketing” model. He argues that reliably reproducing viral hits such as Star Wars Kid, Numa Numa, and the like is extremely difficult. In order to become huge, viral hits must have an extremely large “infection rate” – i.e., one person tells 10 friends, who each tell 10 more friends, etc. More often than not, this type of exponential growth fails.
There is a better alternative – what Watts calls “The Big Seed.” A marketer using the Big Seed model distributes content designed with a moderate infection rate across a wide channel. If this channel reaches 100,000 people, 50,000 of whom forward it to a friend, of whom 25,000 forward it to a friend, etc., at the end of the process, 200,000 people will have seen the content – with additional distribution of 100,000 for free. The key for maximizing ROI with this strategy is starting with a big enough “seed.”
Case in point: modern Super Bowl ads. Take E*Trade’s “Trading Baby” campaign, which was distributed via the biggest seed known to man, the Giants/Patriots Super Bowl LXII. According to AdAge, more than 5mm people viewed the ad online, and in the week after the Super Bowl, newly opened and funded accounts leaped by 32%. The return didn’t come from wide distribution or viral growth by themselves, but the interaction between the two.
In the latest iteration of this strategy, marketers are beefing up sharable content that will only be available online. Take, for instance, Miller High Life’s 1-Second Ad campaign, and E*Trade’s Trading Baby Outtakes campaign, both of which springboard off the Super Bowl big seed to facilitate infectious, and free, growth.
To sum up, marketers looking to optimize distribution and cost need to take advantage of the intersection between large channel distribution – whether it’s the Super Bowl, Hulu, or MySpace – and social distribution to maximize ROI.
