Delving into customer thoughts: TEXT ANALYTICS provides insights
What’s next?
Several trends can be anticipated for text analytics over the next few years. “Specific text analytics capabilities, such as sentiment analysis, will mature,” says Leslie Owens of Forrester. “Right now, the analytical models are at varying levels of maturity, depending on the uniqueness of the topics or the source material itself.” In addition, better integration with traditional business information systems will bring a more comprehensive understanding of the context of the comment, such as the store the customer visited or what they bought.
“All the characteristics of an interaction between a customer and a company need to be put together to form a complete picture that supports the right action to be taken,” Owens adds. Finally, big data (see sidebar following or on page 13, KMWorld, Vol 23, Issue 7) will take on an increasingly important role as the burgeoning volume of data puts greater pressure on creating effective automatesystems for interpreting unstructured information.
BIG DATA and TEXT ANALYTICS
Big data is unquestionably a driver for the increased use of text analytics. “In particular, big customer data is more available than ever before,” says Brian Koma, VP of research, enterprise feedback management practice leader at Verint Systems. Verint provides solutions for capturing and analyzing customer data, security intelligence and fraud/risk/compliance information. The volume of unstructured information in social media customer records, voice recordings, chat sessions, e-mail interactions and open-ended comments in surveys is growing rapidly. “Most of this information is underutilized or in some cases, not analyzed at all,” Koma says.
Yet most organizations are still listening to customer data in silos, because different channels evolved at different times, and fully integrating the data poses many problems across an enterprise. Being able to answer the “why” behind the “what” is where text analytics shines. “Highly sophisticated companies are putting together the structured and unstructured information to track, profile and segment customers,” Koma says, “but the integration process remains a challenge, both organizationally and technically.” However, by overcoming those barriers, companies have the best shot at proactively detecting patterns and fully understanding their customers.
The volume of big data and the speed with which it is flowing into organizations provide a great opportunity for real-time monitoring and response. “Traditional transactional data has a time lag (for example, billing information shows up only once a month), but you can see text data right away,” says Ranjan Mishra, president and senior partner of ESS Analysis, a consulting firm that specializes in analytics. “The question is, can you act on it right away? The best companies are those that do the ?best job of integrating disparate data to provide actionable information. Otherwise the decision-making is siloed too. Without this ?integration, it is difficult to get the right kind of information in front of the CIOs and CFOs.