Keeping Customer Feedback from Falling into the Abyss
1 Sep, 2008
By: Bob FurnissQuestion:
We gather a fair amount of information from our customers though our annual customer satisfaction survey. But we are not sure if the information is really telling us what we need to know. We have an 85 percent satisfaction rate, but how do we make sure that number is important? We also collect mounds of comments from customers but how do we find the ones that matter?
Assuming there is more…..
Dear Assuming: We all know that assumption is not a good way to run a company. Let’s look at your situation and see if we can find a better way. First, I recommend you do satisfaction surveys more than just on an annual basis. It is important to survey customers at least monthly and many companies are doing it on a daily and even hourly basis. New technology now allows companies to survey customers via IVRs after each call. With the right Quality Analytics technology you can now “search” through thousands and thousands of calls every day to find what callers really think. At a recent conference I attended a case study session where the company is using the data for more than changing call center processes. If you are not familiar with the possibilities, open a browser and Google quality analytics.
You also mention that your company has attained an 85 percent satisfaction rate. Just like you, I am not sure what this means. Eighty-five percent satisfaction sounds like a good level of satisfaction. However, I like to ask my clients to see the results through a reverse lens. If we take customer satisfaction scores and turn them upside down, we find what percent of customers are not pleased with the service they receive. In your case it is at least 15 percent. Let’s take a moment and focus on the negative, with the sole purpose of arriving at the positive.
Consider asking customers about their dissatisfaction. We have all read the statistics about unhappy customers. You know the saying: “If a customer is happy he will tell three other people, but if he is unhappy he will tell nine other people.” And if he becomes really unhappy and leaves, you now have to pay twice as much to get another customer just like him. We believe dissatisfaction reasons are more important than satisfaction reasons and we tell our clients to track the statistic and go deeper to find out why.
Once the results are tabulated, there are two key components to making the information actionable. First, categorize the information in a way that tells a story across the organization. Attempt to understand if the number-one problem is also the most important one in the mind of the customer.
Second, attempt to tie the results to actual customer churn and lost revenue associated with lost customers. This way the plan becomes actionable. Let's say the number-one problem for the large business customer is the way your call center handles claims. Look at the customer turnover rate from last year among customers who had claims and tie lost revenues to the top problems identified within this segment. If customer dissatisfaction can be tied to specific lost revenue, it is much easier to find the money to fix the problem as a next step.
You also mention collecting “mounds of comments” but don’t know how to mine the data. I assume you receive the data in a spreadsheet or data warehouse. Again, using the upside down satisfaction method, consider reviewing the comments of the 15 percent dissatisfied customers. Categorize those comments by specific issue or problem and share the data within the center. Use the comments to tell stories with your agents. Agents respond better to real customer stories. When I tell agents 25 percent of all customers are unhappy about the way we handle claims, they hear the number and think – well, 75 percent are happy – so that is not that bad. When I tell them a story direct from the customer’s perspective (using specific customer comments), they have a better chance of relating to the issue and attempting to change their behavior.
I am glad you assume there is more to data than just the statistics. I hope these ideas help you put stories to the data!
