With winter winding down and marketers coming out of hibernation, the fresh air means one very important thing: It must be conference season!
Along with South by Southwest and a variety of vendor conferences, you'll find me gearing up for Forrester's Customer Intelligence Forum, being held on April 18th and 19th in Los Angeles. The Forum theme is "From Cool To Critical: Creating Engagement In The Age Of The Customer," and we will explore the ways customer-obsessed marketers will win in the next digital decade. This will be an excellent opportunity for data-driven marketers to connect and learn about industry best practices and future trends.
One trend I find most fascinating (and this will be no surprise to regular readers) is the abundance of new data sources for customer intelligence. As a result of my interest — and of course, attendees' interest — this year, I'm leading a track about identifying customer insights from emerging data sources. With help from my awesome colleagues Tina Moffett and Roxie Strohmenger, we're going to host four interactive sessions around new data, how to evaluate the various channels, and how to harness data from these sources to uncover actionable insights.
Although most of my Cambridge-based colleagues don't want to bring it up, last night's Super Bowl was exactly the spectacle we've come to expect from the nation's most-watched event. We saw hundreds of new commercials (some good and many bad), a crazy half-time show (with a random tightrope walker), and one other thing . . . what was that? Oh, yeah, a football game.
In the weeks leading up to the game, I noticed a trend around the game itself. Dozens of blog posts and news articles claiming they could predict the Super Bowl winner using social media. Although most of these were fluff pieces to fill a slow news week and capitalize on the nation's renewed interest in the NFL, my research skepticism kicked into overdrive with some of them. Not to call anyone out directly, but with all of the PR teams sending me press releases about "predicting" the outcome, I just can't let this slide. So, can social media predict the outcome of the Super Bowl? No.
Each of these predictions came from collecting and analyzing social data. Some predictions came from simple metrics like the volume of mentions around one team against the other. A few of the predictions used the sentiment of mentions — such as a positive mention for the Patriots versus a negative mention for the Giants. And some predictions even used influence calculations to understand how different market segments discussed their favorite teams. In the end, this means that some of the predictions were right and some were wrong. But hey, it was a 50/50 shot anyway. Even with coin-flip odds, it seems that more than half were wrong . . . but that actually distracts from my argument, because even if they guessed right, they were wrong to do so.