Heard on the street: T-Mobile vs AT&T
Being at the forefront of the technology space has its benefits, the best of which is the opportunity to hear about new challenges our clients and prospects seek to answer with social data. It’s fun to collaborate with smart people on solution architecture that serves not only the here and now, but also to address issues they foresee on the horizon. One of the more common topics I’ve heard recently is around drawing correlation between offline and online marketing activities, and the ability to more fully understand attribution as it relates to an actual conversion.
A conversion, whether represented by filling out a form, or more tangibly, an actual sale, occurs as a result of a number of other factors that led to that event. Leveraging social analytics technology to uncover valuable insights related to the events that led up to the conversion is not as hard as one might think, and in fact, drawing a correlation to online and offline activities may seem complex, but it’s something we can effectively address.
Here’s an example that we sometimes use to illustrate how marketers can leverage Visible to more accurately assess the interconnectedness of traditional and social media and tie findings to conversions:
T-Mobile launched its “Uncarrier” campaign in early 2013, and saw massive response (and won over a whole lot of AT&T customers) by changing the model and not requiring a contract. They shifted to a more customer-centric model, which paid off in spades. Fast-forward to Sunday, February 2nd, 2014 … The SuperBowl. T-Mobile launched an epic TV ad featuring Tim Tebow, a popular unsigned NFL quarterback who had no contract with an NFL team at the time … and still doesn’t. Cleverly, T-Mobile used his professional situation to highlight the many flexibilities that came to those who weren’t tied down with a contract, thus was born the #Nocontract Twitter hashtag, and Tim Tebow featured as, among other things, a firefighter, an astronaut and even a bull rider. The key message: “Contracts hold you back.”
So how does this example highlight the effectiveness of Visible Intelligence to draw correlation between the TV ad and online activities to conversions? Take a look at the number of people who were actively talking about switching to T-Mobile one week before the airing of the now famous SuperBowl ad, and the impact on customers looking to switch to T-Mobile when the commercial previewed a few days prior to the SuperBowl, and the week following the big event:
As can be seen, there was a visible increase once exposure of the ad began, both in the preview phase a few days prior to the SuperBowl, and immediately thereafter. In fact, when calculating the average daily number of people displaying switching signals a week before vs. when the ad began airing, and a week thereafter, there’s a mean increase of about 12% per day. The number of people displaying switching signals to T-Mobile didn’t return to pre-SuperBowl averages until mid-April, which highlights the impact and longevity of the campaign. It also reveals the next logical step in the equation, which is to actively engage online with people who are displaying switching signals, perhaps sending them a special incentive to make the move.
This example illustrates how marketers can effectively measure the impact of traditional and social, and establish meaning for how these channels are interconnected, within the context of conversions and, ultimately, attribution. And, in all their effort responding to people displaying switching signals after the commercial, they still made time for me.
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