Twitter Friends – Google Analytics for Twitter
Despite being as good as dyslexic when it comes to numbers; monitoring, metrics and analytics are massively interesting topics to me, especially when talking to so many clients who express an interest in social media and want to know one thing:
What is the ROI?
This is at best a challenging question. At worst, it can make us look foolish, as if Social Media is a passing fad with little concrete foundations or measurements.
Now, as I have written before, bringing the success of social media activity down to one metric is [feel free to insert an appropriate personal analogy for measuring the immeasurable here], so the more metrics we DO have at our disposal to understand the conversations taking place, the better.
With Twitter attracting almost 3 million users who (and according to Benedikt, post an average of 10 posts per day) there is an enormous amount of conversations taking place. So how do you get any measure of what you are doing and who you are and aren’t talking to – enter Jason’s fantastic video of Benedikt’s Twitter Friends – a tool that allows you to see essentially, who you interact with most, and what habits you use on Twitter.
The Power is in The Networks
As per the video, it’s pretty much widely accepted that Twitter consists of 3 main types of networks (some people say 4)
- Your network – the network of people you follow and who follow you
- Your network’s network – those people is following your followers
- The @ crowd – the people you reply to most (who may not in fact be following you, but with whom you converse the most)
So what if we could dig deeper into these networks to find something of value? If we could see into our networks, would we behave differently, use different language, would we share more, link less, re-tweet less (which wouldn’t be such a bad thing for some people)?
Take a look at the list below and see what Twitter Friend measures:
- Size of relevant net (outgoing) : Number of Twitter users, the submitted Twitter user replied to more than once the last 30 days
- Size of relevant net (incoming) : Number of Twitter users that replied to the submitted Twitter user more than once within the last 30 days
- Fans : Number of Twitter users that replied to a user within the last 30 days
- Stickiness : Number of people who replied at least twice / total number of replying users
- Twitter Rank : This is the position of the submitted Twitter user in the ranking of Twitterers receiving the most replies
- Ratio of outgoing to incoming contacts
- Overlap of outgoing and incoming net
- Tweets sent / day 50 Average
- Follow cost in milliscobles
- Replies sent / day
- Conversation Quotient (CQ) : Share of Tweets by the submitted Twitter user that were replies
- Conversational Rank
- Replies received / day
- Links posted by the submitted Twitter / day
- Link Quotient (LQ) : Share of Tweets by the submitted Twitter that included links
- Replies with Links by the submitted Twitter user’s friends / day
- Link per friend
Here’s my analysis: who I most talk to.
The split of my activity:
And finally, my stats:
Overwhelming some might say, but this provides a REAL boon for brands operating on Twitter (and leads to my point at the top about finding metrics which can help determine an ROI or at the very least provide sound metrics on which to monitor branded Twitter activity).
So what if you were a brand on Twitter. How could you use this kind of tool to understand your behaviour in the market?
Would understanding that you spend 60% of yor time talking to only 10 influencers change your habits if you are a global brand? What would happen if you noticed that you never re-tweeted people who were talking most favourably about you? Would you talk to them more, re-tweet them more?
Let’s take a look at 2 big brands to see what their behaviour looks like to see where their opportunities lay:
In Starbuck’s case, the most glaring problem is the lack of @replies. It is worrying that a brand which craves our feedback through mystarbucksidea, has so few outbound comments to punters on Twitter – especially when you see how high its Twitter Rank and conversation quotient is.
Looking at Dell Outlet, there is no surprises that their link quotient is high, their @replies is low, their re-tweet quotient is low. They are a vehicle for dumping links of special offers onto Twitter with as little fuss or involvement as possible – who’s to say it is right or wrong, but $1m+ dollars can’t be wrong.