I’m thinking metrics of any kind are of limited use unless we learn something from them, change behavior as a result. Twitter Friends is a metrics package that does show me what I do well and might want to improve – see the video, below:
One thing I noticed was my conversational style with an above average conversational quotient of 57% meaning I tend to engage in 1:1 conversations on Twitter, perhaps replacing email in some cases; compare that to how @conversationage handles conversation on Twitter – she’s a lot more responsive to fans, @replies, but still ignores some of the other things such re tweets and loyalty quotient. Another friend of mine, @amycrehore, uses Twitter much as I do, but maybe with a smaller number of tweets.
In fact, I wonder if the use of Twitter, in the way Twitter Friends is able to measure – would turn out to be generational – in that, people of a certain age or inclination will use Twitter differently. I bet, for example, Forrester could use their Social Technology Profile Tool – but map it to the metrics Twitter Friends provides and come up with some very interesting findings (though the two approaches are disparate – instead of looking at the large universe of what people do – apply the same approach, but just looking at what people who use Twitter – and what they do).
The other interesting finding from using Twitter Friends is looking at a person’s network for interrelationships – for example there are people in my own close network that were talking to each other via Twitter than I had no awareness off, till I looked at the chart. that’s a signficiant finding for me because – it makes me wonder if these friends communicated, initially, because of me, or if it happened on it’s own.
The part of Metrics that provides “awareness” is significant – you can’t change or modify anything, at least, not deliberately, unless you are first aware of the relationships.
I also think Twitter Friends could be improved – for example my @From replies show who I replied to but doesn’t attempt to go further and analyze the content of what those replies are (and color code them, for example) – even as other tools have attempted such as Twitrratr – at the time of this writing – on my Twitter name, @webmetricsguru
where you can see that 27% of all the communication between me and my followers was positive, while the rest was neutral – compare that to @brett who had 3% of his followers communication that was categorized as negative, at the time of this writing – as seen here (most of the “negative” comments were more about things that @brett had nothing to do with, btw, so they’re more comments about a situation, in this case).
Still, my point is that Twitter Friends could be improved by combining @from and @to and the Network Diagram by using a mashup of Twitrratr, or something similar, to improve not just the number of connections, but the quality of them.
Also, the awareness of how we interact – for example, look at @Dell in Twitrratr and see that there’s a higher number of negative responses (maybe people are using @dell for customer service issues) with nothing positive and 25% negative (as shown here – but with the low number of tweets you have to wonder). Still, if you start looking at major Brands who have Twitter Accounts and compare them, using a mashup of Twitter Friends and Twitrratr, I bet you would come up with some very interesting results that would bespeak of the awareness and effectiveness of Social Media in those Brands – and I’m surprised no one has done it yet.
Anyway, I see a lot of possibilities for this kind of intelligence in 2009, not only inventing new things in this challenging year, but also improving on what we already have.