Several weeks ago I was participating in Dabney Porte's Friday evening #Slumberparty on Twitter. The sponsor was Michelle Bucaro @1DeVineGal who markets Lip Shimmers. This chat has a lot of virtual slumber party engagement activities such as pillow fights, Twister, silly string, DJ music, and generally a scavenger hunt involving the sponsor's products on the Internet. I did not participate due to personal usage of lip gloss, but I do enjoy the social engagement and fun in the event.
As a quick background, Dabney provides a comprehensive 3 day awareness campaign that generates Twitter Follows, Facebook Likes, and Website registrations for SlumberParty sponsors. The sponsor is trained on Social Media and has great engagement with an audience that generates large Twitter impressions. From what I have observed, this engagement continues weeks after the slumber party is over providing additional economic benefits. The sponsor receives a comprehensive analysis package after the event ends.
What is interesting about this specific Twitter Chat session is a tweet made by Miles Austin. I wish I saved the tweet, but what I recall was that "I am giving a presentation and all I see is @DabneyPorte talking about lip shimmers". It struck me that Miles, was likely making a presentation that was supported with a big screen. I responded back with several tweets about Social Media ROI and what this Twitter party was about.
I followed up with Miles after the chat session to learn more about what he was doing. Miles hosts a "Master Mind" group of executives that meets monthly on Friday evenings. They generally meet in a private room in a restaurant or bar for social networking and learning. He provides a forum where executives can comfortably learn about social media, social media metrics, and social media tools in a safe environment where they can ask any question. This helps the executives to discuss Social Media in their companies.
During this session, Miles was demonstrating Tweetchat as a tool for twitter and he recalled that Dabney Porte's #SlumberParty was the happening event on Friday nights. So he entered SlumberParty as the hashtag to demonstrate how to use the tool. He went on to his next topic, but SlumberParty was streaming away on the big screen behind him while he was talking. He noticed some giggling several minutes later. After checking to make sure his fly wasn't down, he asked the group what they were laughing about and they pointed to the flying SlumberParty chatter. Miles turned around, saw the stream and entered his tweet. He explained how this was creative marketing on Twitter generating economic returns. While he was talking on this, I was tweeting away on the economic benefits to the sponsors. So his audience received a double presentation on Social Media Return on Relationships. It was as if I was in the room tweeting his presentation.
The bottom line, is that you never know where your tweet will go.
You can read more about #SlumberParty written by Jean Parks @GeekBabe on her blog post: Dabney Porte brings you a Twitter Slumber Party — The Shoppinqueen and check out Miles Austin's "Fill The Funnel" here where he provides great insight on a lot of social media tools.
If you haven't done so, please give #SlumberParty a try. The actual party starts Friday at 10:00pm ET and lasts for an hour. This party does have a lot of pre and post party activities that are just as engaging. The Twitter stream moves so fast a hashtag monitoring tool like Tweetchat is recommended. You can learn about Slumber Party events on Facebook.
Did you know that Empire Avenue provides LinkedIn network scores? As of the date of this post, Klout and Peer Index do not have LinkedIn factored into their influence scores while Empire Avenue does have a network score for LinkedIn. Klout states that they are working on it. (On June 14, 2011 after this post was written Klout implemented LinkedIn Scoring)
Empire Avenue states that Connections, Recommendations, and Activity are factored into the Linkedin Score. Connections and Recommendations are easy metrics to derive once the LinkedIn account is hooked up in Empire Avenue. Activity measurements can be a challenge given the nature of Linkedin. Activity that shows up on a status update timeline are: Status Updates, Discussions, Shares, Polls, Group Activity, Question and Answers. There are also secondary activity measures such as likes and responses made to your questions and discussions. I started looking at the LinkedIn Scores when I noticed that Stacy Zapar, the #1 connected woman on Linkedin had an EAv LinkedIn network score of 68 and she is one that engages. At the time, I was scored a 32 and wondered what the highest EAv LinkedIn scores profiles looked like. Empire Avenue provides the capability to evaluate scores across a variety of dimensions including networks.
Comparison Chart
The following shows the Empire Avenue LinkedIn network scores and LinkedIn metrics as of 6/2/2011.
EAv Score Connections Recommendations Activity
Steve Cassady 34 1,200 10 1 Day
Stacy Zapar 68 30,000 11 1 Day
Jason R. Martin 75 16,240 30 .1 Day
Viveka von Rosen 82 16,000 61 1 Day
Neal Schaffer 88 26,000* 55 1 Day
Lewis Howes 91 20,000* 147 .25 Day
Laura Levitan 95 11,000* 226 None
Shally Steckerl 100 30,000 173 .33 Day
Data Methodology
Linkedin connection counts were provided to me by the users. For those accounts* that I didn't have the actual connection count, I derived the connection counts from relative positioning of LION accounts that state connections counts in geographic searches sorted in connection order. Recommendations are listed in the Summary section of the profile. I used LinkedIn signal to determine LinkedIn network activity over a two week period to be consistent with Empire Avenues two week activity averaging methodology. I removed Twitter based status updates from the LinkedIn activity since the scoring systems should be removing those duplicitous activity measures.
Observations
Bottom Line, is that it appears that the highest Linkedin scores are those users that have recommendation accounts in the mid 100's and above. The highest is Shally Steckerl who is connection count capped out with 173 recommendations. The second highest score is Laura Levitan with over 220 recommendations, but with "only" approximately 11,000 connections. Neither of the two are "active" linkedin users during the past two weeks (being consistent with Empire Avenue's measurement period) as measured by Linkedin Status, Sharing, and Group activity found through LinkedIn Signal. Although their usage may be more like Stacy's for recruiting searches, those activities aren't as "measureable"
It looks like that every 5 recommendations gets you "1" change in the LinkedIn network score. From a broadness of LinkedIn network scoring, I think Stacy Zapar's engagement with her 30,000 base should carry more weight than Laura Levitan's smaller base and less activity even with higher recommendations.
I have a better appreciation of why it may be taking Klout so long to roll out their LinkedIn logic especially with the challenges of LinkedIn's API and variety of ways to use it. How do you factor in poll activity and responses, responses to questions, likes of your shares, comments on discussions you initiated, etc.
My current thinking is that there should be a minimum level of recommendations for a decent LinkedIn network score as a sign of connection validation, but there should be some level where recommendations have diminishing returns. Especially in the past there have been "Top Recommended Contests" on Linkedin and the range of recommendations from being "substantial involvement" to more "thanks for answering my questions, you must be smart". I wouldn't go out to get recommendations just to raise my #EAv stock price since that could dilute the personal branding and the quality of your profile on LinkedIn. You should focus on real authentic recommendations on LInkedIn that have real meaning to clients or prospective employers.
As @Dups, cofounder of #EAv states "We do say we talk about Network Value, and in fact at Empire Avenue, the scores are the algorithmic measurable layer that any API gives us which is fraught with human assumptions, algorithmic issues and technical nightmares, but they do add value, they do give an idea of what's happening in a network."
What do you think about the weight of recommendations in LinkedIn network Empire Avenue scoring?
Image via Wikipedia
