First, they took a look at the kinds of news stories that were being shared by the 2300 participants in the study. What they found was that people shared stories in order to “impart knowledge,” which is kind of a given, isn’t it? Only 19% of shared stories were considered breaking news. The 65% majority was ongoing stories with what CNN called “quirky” stories making up the rest. But it’s not crime or politics that is lighting up the virtual airwaves. It’s science, technology, human interest and money-related new stories. Technology is a given seeing as that’s the vehicle we’re using to drive this herd in the first place but I was a little surprised by the others. They also mention “visually spectacular” news, which I take to mean things like fires, floods, snowstorms and UFO’s in the skies around China.
Not so surprising is the fact that 27% of all sharers account for 87% of stories shared. 13 stories a week was the global average for sharing and 26 stories on the receiving end.
Here’s the important part for advertisers. CNN used biometrics and eye-tracking to measure engagement and they found that shared news stories resulted in higher engagement with not only the content but the advertising embedded on the same page. They did this by comparing the results of participants looking at random content. 19% of those surveyed were more likely to recommend a brand that was advertised along with a news story sent to them by a friend. 27% said that they were more likely to find favor with that brand.
This is all well and good but how useful is it really? No matter how much we study it, there is no way to predict what people will share on the internet. One day it’s a serious story about unemployment and then it’s cats wearing tutus dancing on a piano. We’re a fickle lot. And the study talks about the types of stories but what about the types of ads. Does an insurance ad do better than a GAP ad if it’s placed next to a story about a house fire?
The Guardian quoted CNN’s senior vice president of research, Didier Mormesse on this point.
“Though recommended news seems highly unpredictable, we’ve have identified a number of key drivers and key motivations, so we do have some ways of understanding what people share and why they share.”
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