For the longest time, I’ve wondered what brings the extraordinary success of some user-generated content. Consider, for example, the top ten most popular YouTube videos of all time. The #1 video on the list is a simple one-minute clip of a little baby biting his British English-accented brother’s finger. But it has received a whopping 155+ million views, while your average YouTube video probably doesn’t get much more than a dozen passerby’s attention. Why such a huge difference?  I asked.  When I spoke with my friend Michelle Rogerson, she expressed the same curiosity.  So we decided to set out to answer our question.

To do this, we collected a random sample of slightly more than 100 videos from YouTube over the course of a week. These are all fresh new videos just uploaded onto YouTube, so that we can study their rise to popularity from scratch. We traced each video for a period of two months, recording the number of views and the average user ratings each day. We also collected a large number of characteristics for each video (see the figure below), including those related to the video content, to the video author, and to the network of users connected to the video author. We further recruited a group of individuals to rate each video on its production quality, educational value, and entertainment value, which are the three components of what we call “innate content quality”.

Equipped with all these data, we then used a technique called recurrent events analysis to see how these video characteristics affect the popularity of a video. Below are some of the main things we found:

• Authors with a large number of subscribers who each has only a handful of friends are in a better position than authors with a small number of subscribers who in turn may have a large number of friends.
• Once past an author’s direct network of subscribers, influence rather than simple reach becomes critical. We attribute this to the large amount of user-generated content (UGC) being passed around everyday and as a result our tendency to ignore most sharing unless they come from someone we are really close to or someone whose opinion we respect (opinion leadership is not dead!)
• What proportion of an author’s subscribers know each other also matters. A totally segregated set of subscribers does not help get the words out, but a group of subscribers where everyone knows everyone else is not optimal either. We found that the ideal connection ratio (termed connectivity or density in network analysis) was about 38%. Below this ratio, diffusion rate increases with connectivity up to the maximum, and then decreases after this threshold.
• Of the three innate quality components, entertainment value and educational value are equally important in determining a video’s popularity. Production quality, on the other hand, did not matter.
• But the biggest impact did not come from innate quality but from what we call “manifested quality”, which is quality information publicly available through other users’ ratings (i.e., the little stars underneath each YouTube video). Increasing the average rating by 1 star can lead to as much as 13.5% gain in diffusion rate.
• Age has a negative effect on diffusion rate, meaning that younger users’ contributions are more likely to be popular.
• An author’s past experience and success also carry over to the new content. More prolific authors and authors whose past contributions were more popular are more likely to see their new content popular.

Of course, with only one study, we are far from completely answering our initial question.  But what we found here suggest that there are indeed systematic differences among videos and authors that can help predict the success of future content. Carrying this over to other types of user-generated content such as tweets and consumer blogs, these findings and findings from future studies should help companies pour through the overwhelming amount of user-generated content available online and selectively invest effort in the ones that are most likely to become popular.

What do you think?  I’d love to hear your thoughts.  Is there anything important that we are missing? If you are interested in more details about our study, you can download our working paper at http://www.yupingliu.com/files/papers/liu_rogerson_ugc_diffusion.pdf.

I just attended a talk by Debbie Millman on branding. One idea that I found very interesting from the talk was discussion on the current wave of tribal branding since 2000. Ms. Millman made the point that in this wave of branding, a brand that builds/facilitates connectivity is likely to be successful. She enlisted statistics that show 1 in 3 households in America now consists of a single person, in contrast with only 1 in 10 households as a one-person household in 1950. As traditional communion places like the household downsizes to be a single’s cave, our need for connectivity as human beings has to be channeled through other places and other objects such as brands.

This association between brand and connectivity is very interesting and is consistent with the evolution of contemporary marketing. So I’d like to elaborate on this idea a little further. The marketing discipline is witnessing two interconnected trends: an increasing emphasis on building customer relationships (i.e., relationship marketing) and a perception change of consumers as objects/targets of marketing efforts to consumers as collaborators (see Vargo and Lusch 2004). Both of these are manifestations of connectivity and how marketing may play a role in building connectivity.

So to use some concrete examples to illustrate the concept, a brand can build or contribute to connectivity in two ways: physical or infrastructural connectivity; and psychological connectivity. Brands in the former category build infrastructure for people to connect with each other, such as T-Mobile, MySpace, and Facebook. These brands derive their value not necessarily from consumers’ emotional connection with the brands per se but rather from the value of relationships that are built on these infrastructures. For example, the popularity of a social networking website such as Facebook is dependent on the people that we as users can connect to through the website and how satisfying that connection experience is. Consumer collaboration dominates in this setting as a demonstration of connectivity.

Brands in the second category aim more toward establishing actual psychological connections between consumers and the brand and between consumers and consumers. While the connection between people is still essential to the connected nature of such brands, each individual’s connection with the brand is an essential ingredient to this type of connectivity. For example, Harley Davidson or Apple owners identify among themselves because of a mutual connection with the brand. In this type of situation, rather than functioning as an underlying platform for connectivity to occur, the brand becomes an indispensable bridge in the connection process. Relationship marketing and CRM become key strategies for enhancing connectivity in such cases.

It is possible for brands to crossover between categories. An example of crossover from psychological connectivity to infrastructural connectivity is the online communities that many CPG companies have established, such as Kraft community. Consumer interaction in those communities may no longer be brand-centric and may broaden beyond the brand to other realms of life. An example of crossover in the other direction is Second Life, where devotees who have been able to build meaningful relationships in the virtual world come to love SL as their virtual country, no less than the feeling of patriotism that we feel as citizens of a country. By crossing over or occupying both realms of connectivity, these brand names build a stronger hybrid form of connectivity that is valuable to today’s single-dominant world.