My friends at KeenKong have been busy perfecting their conversational mining platform since my last visit to Montreal in December and have come up with something new, Conversational Metrics including a Net Promoter Score for their conversation meaning platform that includes a semantic analysis overlay. I first wrote about KeenKong’s initial offering at KeenKong – Conversational Analytics last November.
KeenKong asked me to come Montreal to give my opinion about their platform much as Compete.com has (but they didn’t fly me to Boston for that) yet I’ve found my opinion being asked for, more and more – and my friends at KeenKong.com have taken some of my advice – just as my friends at Compete.com have, and you will see some of it (for Compete) on May 15th – as a new feature of Compete that I directly influenced. The same goes for these metrics – though the team at KeenKong went even broader than what I asked for.
First, the Net Promoter Score for Twitter Conversations around a brand – it’s still being tested and in the process of certification but I can say KeenKong is the first to come up with such a metric for conversations on Twitter to my knowledge. I won’t go into the Net Promoter Metric for KeenKong as I was asked to wait on that – except to announce the capability exists – and KeenKong is doing it – contact Frederic Guarino at KeenKong.com if you want to know more about the new KeenKong metrics module – again, this was an idea I floated to them last December – but I’m sure I’m not the only one who asked for it and I did not specify the Net-Promoter score – another of their beta testers did.
For some reason Frederic Guarino compared me with @conversationage – Valeria Maltoni – who is a friend of mine, for this analysis – I’m sharing what Frederic prepared for me. I had no input in this decision but am sharing it as it was given to me.
The first metrics KeenKong supplies me with is total mentions and total reach of those mentions – as you can see, Valeria has a larger following and therefore, more mentions and reach than I do (looks like, for the selected time period, a tweet from her could be seen by 9 times more people than me).
Taking a direct suggestion from me, KeenKong not only publishes it’s metrics but shows the formula it uses to calculate that metric. This is very important to me and something I stressed, I see way too many industry metrics that don’t publish the essential information on derivation – I saw that often with metrics derived from Comscore – and I never liked it. If you can not explain how you derive an number you should not publish it.
Having said that, the Intimacy rate is a metric that you’d need KeenKong’s semantic analysis engine to come up with as you’d have to first define “intimate” conversations (what one shares about oneself) and in this sense KeenKong is showing Valeria and I are about the same in how we talk about ourselves.
Well, according to this, I answer more of my tweets but also talk more about my personal life.
I guess the last metric above shows that Valeria needs to answer more of her tweets – on the other hand, if you have a lot more followers it might be harder to keep up with all the requests. Jeff Pulver (@jeffpulver) has over 350,000 followers, more than 100 times what I have – I wonder what his conversational metrics would be here?
Anyway, we are only looking at two days in this metrics analysis, April 7th/8th – I’m more interested in seeing the metrics over a period of 3 months – I’m sure that KeenKong has a lot of directions they could go with this new offering.
If you want to know about KeenKong as a platform and their semantic conversational metrics capabilities contact Frederic Guarino at KeenKong.com