Mining and analyzing customer comments to understand sentiment is no longer a wish. It’s a must. Based on years of experience, I suspect many of you are like the business partners I work with: you understand the value of the activity, would love to be able to get your hands on the insight, but don’t have the resources to do the work.
But there is good news. Using basic business intelligence approaches, it is possible to get a quick start on sentiment and text analysis to better understand what your customers think and say about your business. This information can then be leveraged to better serve customers and ultimately, improve the bottom line.
The rate at which customers provide commentary in customer experience surveys in itself can be very telling. Below are examples of insights that can be gained simply by examining the relationship between key real-time survey metrics and the propensity of customers to provide verbal feedback.
For the business partner depicted in the chart below, customer comments and real time alert rates were highly correlated. The more likely a customer was to comment, the more likely alert rates were to increase, and vice versa. This suggests that dissatisfied customers who required a follow up call from a manager were more likely to leave negative comments than positive ones.
While this may seem troublesome at first blush, understanding customer complaints is often an untapped gold mine. Reading and mining these comments could offer significant intelligence and gains for this business partner which can then be woven back into continuous improvement initiatives.
Furthermore, the frequency of customer comments and the proportion of first time callers were inversely correlated; in other words, repeat callers were more likely than first time callers to provide this organization with specific feedback about their service experience. Eureka! What an opportunity to make your business more efficient and save some money for your organization!
Repeat calls result from failure to deliver a customer-approved resolution on first contact. The greater the degree of first contact resolution (FCR) failure, the more staff is needed to support the repercussions of that failure. And that staff has a cost, the hourly rate of the agents, the salary of the supervisors who manage their performance, cost of seats, technology, etc.
This too is a rich source of data that can drive continuous improvement while significantly reducing costs. Mining and understanding the root underlying causes of repeat calls (people, technology, process, manufacturing defects), then working to correct these deficiencies and actually reduce repeat calls, will have an immediate positive impact on bottom line profits as well as on customer retention rates.
If you are like many of the companies we encounter, you know that implementing business intelligence is a must. You know that customer comments are a rich source of data that can help drive real improvements. But getting started is a daunting task. These are two very simple areas where you can get a quick start, drive real results, and get the ball rolling on your 2012 business intelligence to-do list.
- Putting Humanity in Contact Centers - July 26, 2017
- Avoiding Pitfalls of Customer Satisfaction Surveys - July 19, 2017
- Why Customer Experience is Like Sex in High School - January 11, 2017
- VoC Execution Gap in Contact Centers is Huge - June 29, 2016
- How long should my contact center survey be? - June 7, 2016
- Stop the Freaking Customer Feedback - April 27, 2016
- What is your Contact Center Top Priority? - April 11, 2016
- Nine words to stop using to describe your quality assurance program - March 10, 2016
- What NOT TO DO with your contact center budget - March 9, 2016
- What to aim for with your Contact Center Budget - February 15, 2016