68% Of Analytics Professionals Use A Mix Of Unstructured And Structured Data To Get Customer Insights
Editor’s Note: Text Analytics is one of the central connecting technologies driving the convergence of market research with the broader business intelligence and analytics industries. Advances in this space are staggering and although much of MR has been slow to catch on other than using it as a utility to to help manage verbatim responses or sentiment analysis, the capabilities of newer entrants in the marketplace go far beyond that basic functionality and can, when deployed in the appropriate context, deliver stunning results on all levels.
Our friends at the Text Analytics Summit West are just one of the many groups (including folks like Seth Grimes & Tom Anderson) who are working to help explore the impact of text analytics on business insights, especially from the BI perspective. They have been steadily releasing very interesting content in preparation for their event, and today’s post is a wonderful case in point. MR needs to hear more about the overlap of our industry with business analytics so we can chart our future and define our value proposition more effectively.
By Alesia Siuchykava
Text analytics is no longer just a science but rather a vital part of any company’s data strategy. A recent survey of over 300 analytics professionals from world class companies such as Microsoft, Xerox, and Starbucks found that 68% of them use a mix of unstructured and structured data to get customer insights.
The survey, commissioned by Data Driven Business, also found that 53% measure the ROI of text analytics by the extent to which it enables deeper customer insights.
But how does one make sense of text data and use insights for better business decisions? What are the main challenges that the leading analytics professionals face on a daily basis?
According to Han-Sheong Lai, Director of Consulting, Operational Excellence & Customer Advocacy at PayPal, “business executives, who hold the power to allocate text analytics resources, are beginning to see and realize the potential benefits of text analytics to help better focus and solve business problems. Faced with thousands and millions of systematic, unstructured customer feedback, a company or team should quickly, repeatedly, consistently and effectively identify and monitor the biggest customer sentiment or pain points as well as their fluctuations. The challenge is only very few truly understand what it takes to do and scale text analytics right”.
Caio Peixoto, Supervisory Analyst – Information Management, Board of Governors of the Federal Reserve System thinks that “the main challenge is not so much the technology, but the business side of it – guiding the customer to pin down the problem, identifying what questions need to be answered, and/or what is of interest to them”. Whereas Miguel Ares, Customer & Market Intelligence professional at Bloomberg LP says that his biggest challenge is “how to analyze social media data at the individual/micro level especially from those who might be considered influencers.”
In today’s business world, more and more companies are attempting to employ data science to better understand customers and achieve significant competitive advantage. Data scientists are becoming the must have executives of our time, and colleges all over the country are now introducing advanced analytics programs. As Dave Tomala, Sr. Director of Analytics – Knowledge Solutions, Express Scripts Inc said, “Text data scientists are rare and increasingly in high demand. Certainly supply will grow, but the trends in text data accumulation and analysis will probably continue to outstrip supply for some time. If you are lucky enough to have some good text data scientists, treat them well!”
Han-Sheong Lai, Caio Peixoto, and Miguel Ares are sharing more data insights at the 12th Annual Text Analytics Summit West (http://textanalyticsnews.com/west/) in San Francisco on December 3-4. The conference focuses on making a business case for text analytics, choosing the right vendors, driving deeper customer insights and making sense of big unstructured data sets.
If you’d like more information, please contact Alesia Siuchykava, Project Director at Data Driven Business: 201-204-1694 and email@example.com