Research at Lithium Lab Part1

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Lithium is hosting the Social CRM Virtual Summit on Nov 11, 2009 (you can sign up here), and I was asked to hold a live-chat with the audience at the summit. This will be a great opportunity for me to talk to practitioners and get a sense of what kinds of analytics people want from their communities. To get the conversation started, let me tell you a little bit about what got me into social analytics and what I am working on now.

As some of you know, I was a computational neuroscientist (my bio is here). So what got me interested in social analytics? Honestly, it's all about the data! As a SaaS company, Lithium has recorded a huge data set over the 10 years of its business operation. The data at Lithium is very rich and diverse. Besides the 200+ metrics that Lithium records, there are also loads of conversation data between real people. This is what got me excited about social analytics.

You may ask why I didn't go to some place like Google or Facebook then? Certainly they have also collected a lot of social network data, probably a lot more than Lithium if we are talking about sheer storage volume. But as a statistician, we care about sample size. Facebook may have the biggest social network of 300 millions users, but it is only one network. Lithium has hundreds and the number is growing! This enables benchmarking and cross sectional studies that are not possible anywhere else. It is almost as if you can play god and start the network over and over again hundreds of times with different initial conditions. In statistics terms, this is what gives statistical powers to any inferences we make about the community.

Because Lithium has such a rich set of conversation data, we can also glean much insight from understanding these conversations using advance text analysis tools from machine learning. Because the conversations in a community are highly relevant to the sponsoring company, we do not need to worry about information retrieval and deal with the tradeoff between precision and recall. So we can focus our computing power on understanding the content of the conversation. Personally, I believe this will revolutionize the CRM industry, and this is the topic that I am most excited about.

By listening and comprehending the conversation of their customers, companies can understand customer needs and serve them better. On the flip side, customers can truly make their voices heard! CRM would be much more than an automation system of business processes on top of a database of customers' name, contact, when, what, and where they bought in the past. CRM system would know, for example, is a customer satisfied about the product? Do they like all the features? Which feature didn't they like? What problem did they have when using the product? Are they considering switching to a different brand? Are they considering your brand because of the bad experience with another brand? These are the kinds of insight we can reveal by understanding the conversation within the community.

So now that you know what got me into social analytics and what's in my mind, next week let's can get a little more detail about my research at Lithium Lab and what I am currently working on. Stay tuned at mich8elwu.