Text Analytics World Interview

Tom H. C. Anderson
April 2nd, 2013
1 Comment

The Future Directions for Text Analytics

[Text Analytics World Pre Conference Interview with Tom H. C. Anderson, CEO of Anderson Analytics – OdinText and Jeremy Bentley CEO, Smart Logic. April 2, 2013 Q&A Reposted with permission from Text Analytics World]

We asked two leading text analytics experts, Tom Anderson of Anderson Analytics – Odin Text and Jeremy Bentley of Smart Logic, what their take was on some possible future directions for the field. Their answers are shown below:

Tom Reamy: What do you see as the major trends in text analytics in the next year or two?

Tom Anderson: Realizing that customization is key. I think we’re only at the tip of the iceberg. It’s great that we’re starting to finally leverage all the data (CRM, Survey etc.) that we’ve spent so much time and money collecting and storing. But over the next two years I predict we’ll be using it in several other areas that are hard for us to foresee now.

Tom Reamy: What are the problems and issues that are slowing down the field?

Tom Anderson: The infatuation with “Social Media Monitoring” which really mainly is “Twitter Monitoring”. Until walled gardens around Facebook and LinkedIn data come down (I’ve been waiting and waiting), there really is limited usefulness in this area and we may be better off concentrating more of our efforts elsewhere. As clients start realizing they’re just listening to 8% of the population on Twitter or blogs, whom really often are somewhat different than normal customers they begin to question the ROI here.

The reason this can be problematic is that clients are so wrapped up thinking that they need to listen to “what people are saying about us on the Internet” that they don’t think about all the valuable data sources text analytics companies can help them with today.

For instance many are already paying a lot of money to field incoming customer calls and emails, storing this data, and yet don’t take the time to listen to what these very real customers are saying.

This in my opinion is hindering the advancement of text analytics in some ways. The focus needs to be broader.

Tom Reamy: What new technologies and developments in text analytics or related fields (predictive analytics, machine learning, artificial intelligence, etc.) do you see or want to see in the next year or two?

Tom Anderson: I think data visualization today is incredibly poor. I can’t believe many of our competitors in the text analytics field still offer simple “word clouds” as output.

Conversely, I think clients have to realize that data visualization techniques are generally best used as exploration tools, and not one click export to a management level PowerPoint slide.

There is currently an opportunity in best ways to communicate insights from text analytics. Having powerful software and the right data is half the battle. But we also need more creative analysts who understand the respective business and data and who can communicate the findings effectively. This more of a shortage of good analysts with the time to use these tools problem than a need for additional technology.

Tom Reamy: Do you see any revolutionary changes for text analytics on the horizon?

Tom Anderson: Yes, what I’ve been talking about a lot is domain expertise. OdinText for instance is focused on the use of text analytics for consumer insights. That is a very different thing than using text analytics for engaging with twitters or detecting terrorists or fraud etc. All these require special knowledge, rule and code modification.

I think there will be less “Enterprise” as well as “Twitter Monitoring” firms, and a lot more domain and industry specific text analytics tools/firms.

Also this technology will be incorporated by most of the companies that own sizeable amounts of unstructured data. So there will be more licensing and acquisitions going on.

Tom Reamy: Is there anything else you would like to say about the future of text analytics?

Tom Anderson: I’m so glad I got into text analytics as early as I did. It’s still in its infancy, not in terms of what we can do with it already/the power, but in terms of adoption and creatively thinking about how to leverage it in different ways. Very exciting times ahead!

 

Tom Reamy: What do you see as the major trends in text analytics in the next year or two?

Jeremy Bentley: To borrow from Big Data parlance – Velocity, Volume and Variety mean text analytics in real time over a lot of it, in different formats and from different places.
Content Intelligence (which includes text analytics) brings structure to unstructured information so it can be joined with the data world. Data tells you what happened, and content tells you why. Associating the what with the why is the major requirement for organizations that protect, value and make money from their information.

Tom Reamy: What are the problems and issues that are slowing down the field?

Jeremy Bentley: The reality check that content is not clean, properly managed or sufficiently findable today. Information overload (the often cited big issue) is nothing but a filter problem – the problem is that the filter parameters are not present in the current information management systems of CMS, ERDMS and search engines. Until it is recognized that the gritty and unglamorous task of metadata management and automatic application of whatever metadata is needed for a particular view of the content at any particular point in time. Once addressed content becomes process-able and valuable.

Tom Reamy: What new technologies and developments in text analytics or related fields (predictive analytics, machine learning, artificial intelligence, etc.) do you see or want to see in the next year or two?

Jeremy Bentley: There is a balance to be drawn between what is fully automatic and what requires some human oversight – Classification and text analysis should be fully automatic – the methods and rules used to drive the analysis should be subject to user oversight. Machine learning and AI have a role to play in the latter – as software become more sophisticated so the effort needed to achieve quality analytics and metadata derivation will go down.

Tom Reamy: Do you see any revolutionary changes for text analytics on the horizon?

Jeremy Bentley: Most users see text analytics as pretty cutting edge as it is, so to this question we have to widen it from Text to Content – in all of its forms to see where the revolution comes.

Content Intelligence for Big Data will revolutionize how organizations use their information to gain insight and competitive advantage. This is already happen ing in forward thinking enterprises- inclreasingly it will not just be the larger organizations that benefit from such an approach.

Tom Reamy: Is there anything else you would like to say about the future of text analytics?

Jeremy Bentley: Being able to process content, as we do data in a database will seem standard in a decades time.

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