Thought Leaders in Big Data: Interview with Michael Wu, Chief Scientist at Lithium (Part 5)

Sramana Mitra: You anticipate that that is going to be much more of a common practice going forward?

Michael Wu: I believe it is going to be very important for a lot of people, like marketers who are interested in big data analytics. Whether it becomes a common practice or not, it depends on how people use this data. This is behavior data. If people use this data in a nice way – by this I mean a way that benefits the consumer and delivering value for them, not only focused on driving sales and marketing for the brand – people are going to perform more of these types of action. >>>

Thought Leaders in Big Data: Interview with Michael Wu, Chief Scientist at Lithium (Part 4)

Sraman Mitra: So you are anticipating user queries and caching them into intermediary steps.

Michael Wu: We are not really anticipating. Query time is one thing, but there is also actionability. How are you going to look at what every single user in our community does? We have millions of users in our community, and each of those users performs thousands of actions over the years. People need to aggregate around that and summarize it in some way. A way of summarizing that data is a framework I developed, which basically allows the NoSQL solution to aggregate very quickly around who did what, when and where. >>>

Thought Leaders in Big Data: Interview with Michael Wu, Chief Scientist at Lithium (Part 3)

Sramana Mitra: Give us some information on what kinds of metrics those are.

Michael Wu: If you send a message, that message can be a blog post, an idea for people to vote on, etc. So the message has a different context. Not all messages are of the same type. That is what I mean by different context of the message. A person could create 100 ideas but has never posted a single blog post. >>>

Thought Leaders in Big Data: Interview with Rick Kieser, CEO of Ascribe (Part 5)

Sramana Mitra: Is there anything else that is significantly different in the text analytics field currently?

Rick Kieser: The other element is taking a look at foreign languages through text analytics and how that evolution is taking place. The context of generating sentiment from English vs. French vs. German is very different in terms of creating rules around it. Within our platform, our base technology can handle any character-based language – any foreign language. >>>

Thought Leaders in Big Data: Interview with Michael Wu, Chief Scientist at Lithium (Part 2)

Sramana Mitra: Can you double click down into each of those two cases and give us examples of what data you track and what kind of behavior you are trying to stimulate by tracking it?

Michael Wu: Both communities – whether it is the support community or the marketing community – run on our platform. On our platform we track every single behavior. In the support community you may want to reward people for answering people’s questions, whereas in the marketing community you may want to reward people for sharing and reading lots of content. >>>

Thought Leaders in Big Data: Interview with Michael Wu, Chief Scientist at Lithium (Part 1)

Michael Wu is the chief scientist at Lithium. Lithium, as the company’s own website says, helps companies unlock the passion of their customers, providing a platform that customers can use to interact with these companies. Lithium is a social customer experience company with a collective 91 million users each month (more than Pinterest or LinkedIn), and it has helped companies like Sephora to build an social online experience and a tight-knit community of brand ambassadors on the Web. Lithium has also assisted companies like Verizon and Barclays do the same. In this interview, Michael discusses in detail what the platform does and how it helps companies gather insights on consumer behavior.

Sramana Mitra: Michael, what is your background? Tell us a bit about your company and what you do in big data.

Michael Wu: Lithium is a social customer experience platform. What that means is that we offer a platform for large brands to enable them to engage with their customers and also to enable customers to engage with each other. >>>

Thought Leaders in Big Data: Interview with Rick Kieser, CEO of Ascribe (Part 4)

Sramana Mitra: We have done a story on Clarabridge, and I met the founders of Attensity a long time ago, when they were just starting up. Can you talk about the technological point of view? Who is doing what, and how would you rate those approaches?

Rick Kieser: I mentored a firm that was a pioneer in text analytics. That company sold its technology to Insight, which was acquired by Business Objects, which was then acquired by SAP. We use the SAP technology in our NLP engine. This is technology that our predecessor firm created back in 1998. In essence, it is the same thing. They have made some tweaks to it, but it is not dramatically different from our core base one. >>>

Thought Leaders in Big Data: Interview with Rick Kieser, CEO of Ascribe (Part 3)

Sramana Mitra: What are the trends in the data you are processing?

Rick Kieser: It is difficult to say, because we process more than 300 million comments a year. Since we have such a large platform, we span the major industries – pharmaceutical, transportation, energy, financial services. >>>