Turning the Tables on the Elf on a Shelf

Dan Grady's picture
 By | December 19, 2013
in Business Intelligence, Magnify, Social Analytics
December 19, 2013

The dashboard for Elf-on-a-Shelf's Facebook page. Click to enlarge.

Last December my wife introduced our two girls to two very important individuals, Buddy and Snowy.  They are our Elves. 
If you have small children of your own or are connected to anyone with small children on any social network you are most likely aware of the phenomenon known as Elf on a Shelf.  If you aren’t aware, the Elf on a Shelf is a special scout elf sent from the North Pole to help Santa Claus manage his naughty and nice list.  Buddy and Snowy are constantly watching my kids and then, every night, reporting back to Santa. 
It’s been a very effective strategy for us, but also quite intrusive, very big-brother like.  These elves are popping up everywhere watching our every move.  I thought it was time to turn the tables on the elves and analyze the conversations on their Facebook page using the Social Media Analytics capabilities at my disposal – to find out how Naughty or Nice this elf is when he’s killing time on Facebook while the girls are at school.
I used WebFOCUS’s Social Media Analytics capabilities to access and analyze not just the activity on his page, but more importantly the text within the conversations themselves with techniques like word frequency and sentiment analysis.  Here are a few of the things I learned about our friend the Elf on the Shelf. (You can see some of them, too -- just click the image above to see an expanded version of the dashboard.)
  • He appears to be a bit of a Ladies’ Man.  Of the 7,687 posts and comments we analyzed from his page, 89% of them were made by females.
  • He appears to be a very positive elf. Only 359, or 4.67% of the posts and comments got scored negatively by our sentiment analysis engine.
  • On December 12th he got a little rowdy and started toilet papering peoples Christmas trees.
  • Based on the a poll run on his page it appears his favorite movie is “How the Grinch Stole Christmas.”
  • His favorite song appears to Miley Cyrus’s “Wrecking Ball.”
  • Apparently, he also has a thing for Barbie.  There were 48 posts that reference her. Some of them can be seen in the gallery at the bottom of the post.
Unlike the elf, I don’t have time to sit here and read all 7,687 posts and comments on his page, but using those advanced text analytics techniques I was able to quickly see those trends and patterns in the conversations on his page. 
This is a playful example, but this type of analysis has real value when applied to the conversations your customers are having about your brand or product, or the public’s reaction to a new government policy, or recently run marketing campaign.  That value is magnified when you start taking those insights and merging it with your organization’s more structured data to see if those trends and patterns in the conversations had any positive or negative impact on other areas of your business or organization.
The Elves that live in our house – and are constantly watching, analyzing, and reporting back to Santa on all they hear and see – have had a measurable impact on our household.
Sometime soon, when the girls aren’t around, I’m going to let our elves know that Santa has access to this type of analysis, and see how they like being watched all the time.