Root Cause Analysis: Getting to the Heart of your CX Problems
February 14, 2017
It’s not that your customers lie to you, exactly. But sometimes the feedback you get from your customers doesn’t tell you the whole story. For example, a customer might complain that one of your employees is slow. But you know that the employee was doing her best—your computer system was down. Root cause analysis means looking at all your data to find out what is really causing the problems that your customers are experiencing.
Another real-life example was the mystery of the loose headrests.
B/E Aerospace, a manufacturer of aircraft parts, started getting complaints about the headrests on their airplane seats coming loose. They looked at their designs and didn’t see a flaw. They considered their production and shipping processes and couldn’t identify anything. Then, they used text analytics to review data from the maintenance logs of those planes.
They realized that the maintenance crews were removing the headrests to clean them. And they were not putting them back together properly.
Because of this root cause analysis, the engineering team redesigned the headrest fastening system. They were easier to remove and replace. And loose headrest complaints fell by 97%.
It’s not always easy to find the root cause when you first notice a change in your metrics. You might see a change in the volume of customer complaints. Or, your sentiment or satisfaction scores could start moving.
And it gets harder the more data sources you’re looking at. Several layers of structured attributes may be contributing to the change. You should use root cause analysis techniques including multivariate regression to learn more. Multivariate regression lets you analyze multiple attributes, themes, and Natural Language Processing (NLP) relationships at the same time. Then you can measure the significance of each factor, unlocking the most important issues.
Root cause analysis allows you to get to the heart of customer experience problems. It shows you what is really driving your metrics, and gives you a chance to fix what’s wrong.
For more, download our cheat sheet, “9 Ways to Analyze Customer Data,” from the form on this page.
Lisa Sigler is Senior Manager, Content Marketing at Clarabridge. For over 16 years, Lisa has used her writing and editorial skills to bring the value of technology to life. Today, she works to demonstrate Clarabridge’s position as thought leader and trailblazer in the Customer Experience Management market. Lisa holds a B.A. in English from Kent State University. Read more from Lisa on Twitter @siglerLis.