Why Marketers Should Aim for “Ordinary” Influencers
For all the attention devoted to “influentials,” consumers with merely average influence may offer a better investment for marketing dollars, according to a study of Twitter data coauthored by network science pioneer Duncan Watts.
Watts, a principal researcher at Microsoft Research, will present the keynote address at MSI’s December meeting on “Social Media and Social Networks.” He will discuss new insights on network diffusion enabled by platforms like Twitter, which provide scale and granularity in data that was unimaginable just a decade ago.
In a 2011 study, “Everyone’s an Influencer: Quantifying Influence on Twitter,” Watts, with Eytan Bakshy, Winter Mason, and Jake Hofman, examined the attributes and relative influence of 1.6 million Twitter users by tracking 74 million diffusion “events” (URL retweets and reposts) that occurred over a two-month period in 2009.
Twitter “presents a promising natural laboratory for the study of diffusion processes,” they write. Since users “follow” the broadcasts of other users, multi-step diffusion processes can be reconstructed by crawling follower graphs. Further, the use of URL shorteners (e.g., bit.ly) allowed the researchers to track all diffusion patterns, not just those that were successful .
Not surprisingly, the Twitter dataset revealed that the largest cascades tended to be generated by users who were influential in the past and who had a large number of followers. However, most individuals with these attributes were not successful in generating large cascades. The vast majority of URLs did not spread at all and even moderately sized cascades were extremely rare.
In addition, a sampling of 1000 URLs showed that, while URLs that spread widely tended to be more interesting and elicited more positive feelings, content characteristics didn’t distinguish diffusion success from failure either.
Overall “predictions of which particular user or URL will generate large cascades are relatively unreliable,” they conclude. Thus, to consistently harness word of mouth influence, marketers need to target large numbers of potential influencers, thereby capturing average effects.
The researchers consider a number of marketing strategies to target potential influencers. Under a wide range of acquisition/compensation cost scenarios, they find that most cost-effective strategies are those that target users with approximately average influence and connectivity.
The notion that special individuals can create social epidemics promoting a message or product is intuitively appealing. But the empirical work enabled by data platforms like Twitter points marketers away from the extraordinary toward “ordinary” consumers. Everyone’s an influencer, and many small cascades of information sharing are more likely to add up to marketing success.
Watts discusses the Twitter study and other research on networks and social influence in his book, Everything Is Obvious: *Once You Know the Answer.
Influence and Attention on Twitter
Duncan Watts (2013) [Video]
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