The popularity scale behind web content is difficult to quantify. There are things that get more popular than they probably should:
(Rick Astley: 66,000,000 views)
Then there’s the stuff that sputters and dies after its 15 minutes:
(Lynsey Dyer: 296,000 views)
So what exactly differentiates how these things happen? There is a huge amount of money and research poured into researching this and it doesn’t always seem to turn up answers.
Facebook’s definitions of viral are based purely on the analytics behind posts:
Virality is the number of people who have created a story from your post as a percentage of the number of people who have seen it.
Most posts are given a ‘virality’ rating of 2.5% or less. Facebook indicates that 85% of posts are shared or interacted with by less than 5% of their viewers, and it measures viewers as someone who may just breeze by an item in a newsfeed. The numbers collected on the back end of sites are an incredible indicator of why Rick Astley can be substantially more popular than all of the women who ski for us are. I’m sure my dopey face at the start of Lynsey’s video helped it out though....
The numbers we look at on the back side give a much better indication than my instincts about my online popularity can. As an example, I have some information below from a campaign Rossignol ran on January 7 on Facebook:
Over the course of a week we managed to gain over 100,000 views on a new product launch, a reach that beats out many of our ski industry publications, and we did it for free. The entire campaign was accomplished by doing a significant amount of research on what experts suggested through extensive analytics usage. Some interesting things we learned through studying Facebook’s numbers included:
· Video is a huge traffic magnet
· Facebook will push content with links harder than just text
· Photos and videos will also find their way into more newsfeeds than just text
The information we gain off the back end of our posts ends up allowing us to refocus them regionally to make sure we’re keeping our fans interested in what they’re seeing. This is critical on our main page, where we have over 200,000 fans globally with dramatically different language and content preferences.
The back end of Facebook delivers some information on posts but does not begin to touch the amount of information necessary to truly understand what users are doing. The site’s APIs allow applications to build extensive profiles of users and their friends to improve the targeting we do, something that is intriguing but we do not currently hold the resources to properly implement.
All of this is much more interesting to us than print advertising, which we were never able to use to see customer habits. We could never run an ad and see viewer response; today we can see on the back end of our website that four times as many customers are interested in all mountain skis than are in carving skis. It is actually possible to put price tags on this type of data and it can be used not only to shape the site but to make adjustments in product mix. It goes past figuring out what makes a post viral; it can make our businesses much more efficient.
Our master plan includes building better customer profiles and using them to deliver better, and more relevant product information in the future. The shares that we get on Facebook are allowing us to see what types of information our customers find interesting. Analytics can allow us to translate that into better advertising placement and hopefully more sales, even if they don’t bring us 66,000,000 views.