When it comes to extracting insights from unstructured text there is the hard way and then there is the organized way. Follow these principles and you will be extracting actionable insights and sharing them with CX stakeholders in no time.
In two days my six-year stint in Etuma will be over. We've gotten so much done and I've had a great time. Etuma is a fast-growing company with excellent partners such as Qualtrics and Questback and dozens of large companies as customers.
I've learned a new industry and become somewhat of an expert in analyzing customer and employee feedback. I've written close to 120 blog posts, half a dozen white papers, conducted many webinars and talked to many companies.
I just went through all our customer projects during the past six years: I've been involved with 159 companies' customer or employee feedback analysis. Here is what I have learned about CX text analytics process and CX text analysis business in general.
Donald Rumsfeld imortalized the unknown unknows in a press event during the first war with Iraq.
There are things that only you know, there are things that only the customer knows and then there are things that only your competitor knows. You need to build a data gathering and analytcs system that can capture and uncover the insights for all these three dimensions.
An Enterprise Insight Process is more than just gathering Net Promoter Scores or customer feedback analysis as part of your Customer Experience Management or Voice of the Customer processes. Its main aim is to bridge the information gap that your current systems cannot fulfill. It is about being truly customer-centric.
This means including customers in the service design, product innovation, engaging employees and incorporating strategic enterprise themes and values into the analysis and insight distribution.
Open-text feedback volumes are growing 25-50% per year depending on the industry. This data could be a valuable source of information for improving products, operations and strategy but somehow most companies fail to implement a process and tools, which systematically turn this data into decision-making information.