Customer sentiment and text analytics are all the rage these days, as organizations aim to differentiate themselves from the competition with the only thing they have left: service. These activities can make the difference between an organization that thrives and one that crumbles against the competition. But in order to experience the values and gains, a significant investment in both people and technology is needed. Text and sentiment analysis is not a case of buy it and good stuff will automatically happen. A human—-a highly skilled and intelligent one at that—must “teach” the technology what to look for, and not just once, but on an ongoing basis.
Even text analytics on a smaller scale, involving customer satisfaction and voice of the customer survey comments, can be a time-consuming task. But the risks of not analyzing customer comments are immense, ranging from failure to recognize business/product/service opportunities, to making key decisions based on incomplete information. As I often say in my results review meetings with business partners, the quantitative (numeric) data we capture tells us what happened in the past, and can be used to predict what might happen in the future. Where the numeric data is less precise is in helping us understand that “why” behind the “what.” That’s where the qualitative (comments) data is invaluable! And while I suspect that companies understand this statement, failure to capitalize on customer comments is one of the top three failures in most all customer experience programs.
Below are two of an endless number of examples of the type of intelligence that would have been lost if customer comments were not analyzed and mined.
Quantitative insight: Perceived value of the contact center was below our set target for the fifth month in a row.
Qualitative insights: 20 percent of all negative comments about the call center have nothing to do with the call center! These complaints are being generated by negative experiences customers have with other departments (underwriting, claims, pre-authorization). Another 12.37 percent of negative comments are being generated by a combination of technology issues and poor customer service (customers being immediately hung up on by agents). However, the remainder of all negative comments is directly within the call center’s control to improve (starred items), 33.89 percent of which are agent behavioral issues.
Risk associated with not mining customer comments: The call center has become the most important place where customer sentiment is captured. However, if relevant business insights are not discovered and shared with other departments (underwriting, claims, pre-authorization, technology), the organization is committing competitive suicide by “killing” these departments of an opportunity to improve, and “killing” the organization from elevating its service differentiation and brand strength. That is just dumb.
Quantitative insight: There is an inverse correlation between a customer’s satisfaction with the amount of time they waited to reach an agent, and the likelihood that they will evaluate their customer experience.
Qualitative insight: More than 70 percent of the comments provided were by customers who reported low levels of satisfaction with wait time (scores of 1-3 on the 1-9 survey scale). The comments focused on they how they felt about the brand as a result of the call.
Risk associated with not mining customer comments: It’s quite easy to look at the cost of adding staff and a service level figure (which is hard to hang a $ figure on), and decide that saving the company a few dollars is the right way to go. Customers might get a little frustrated for a bit, but so what? Without mining customer comments it’s very easy to forget that the consequence of long wait times is not merely customers who hate your call center or hang up and call again later, but more importantly, customers who feel less loyal to your brand because you dismissed the value of their time! Corporate arrogance is not advised.
Know this: your customers are telling you every day how you are inviting them to do business with your competition. Are you using their insights to kill your competition or yourself?
- Notes on Thriving in Contact Center Performance Webinar - November 16, 2015
- How to thrive in contact center performance - October 29, 2015
- What measurement is best? Net Promoter Score, CSAT, Customer Effort - October 12, 2015
- The Ultimate Customer Experience Q&A eBook - September 23, 2015
- What are common contact center survey questions? - June 26, 2015
- Customer Effort Analytics Executive Summary - June 19, 2015
- Inside Customer Effort Score: Analytics Expert Case Study - June 18, 2015
- Stop trying to delight your customers in contact centers - June 17, 2015
- What is analytics outsourcing? - June 16, 2015
- Let Customers Quality Monitor Calls - June 16, 2015