Customer satisfaction is one of the terms that’s context has been emptied because it has been used so often without understanding the real meaning. Many companies spent huge sums of money to collect customer satisfaction data (CSAT) to analyze it further to understand the end-user experience. However, many of the companies fail to understand how to collect the data systematically and how to analyze it correctly.
Since the data that is collected will be the basis of all the decisions the company will make, the first step is to ensure that the data is properly collected. You have to make sure that the best practices in survey design and administration are employed. You also have to make sure that the data is representative. With this, I mean that you should not only collect data from some type of customers, such as the lowest/highest budget, or most/least worked with. You should collect data from the whole spectrum so that you will have an accurate representation of your customers. Otherwise, you will have skewed data, which will be misleading at best.
Second, you should know what you will do with the data. Although this looks like a no-brainer, many of the companies do nothing more than grouping and averaging data. This grouping and averaging hides many details and mislead decisions. You have to find appropriate and relative metrics to analyze data. Only with these metrics you will be able to measure different types of customer feedback and different levels of satisfaction.
Attention to minute details and individual occurrences is as misleading as overall averages. Zooming further inside the data to find details makes you lose sight of many trends and systematic occurrences. This leaves you trying to find and correct something that affects tens of people and leave things than affect hundreds or thousands. The best thing to do is analyzing trends, finding out systematic and/or correlated occurrences and then finding and eliminating the root causes.
When you spot root causes, there are three things you can do to eliminate them, which are changing/evaluating processes/workflows, training people to understand what is important and improving/optimizing resources.
The first thing to do is evaluating your processes and workflows and changing them when and where necessary. If your CSAT data is pointing at some problems, then start analyzing the processes and workflows that may lead to such problems. Most of the time, we-always-do-it-this- way masks many of the problems that lead to poor processes and customer dissatisfaction. Be bold and question your processes and workflows. Think about the possible ways to do things better. Think what you can do about the call center workflow when customers report excessive waiting times and being transferred from one staff to another. Maybe you need to rearrange workflows, maybe you need to introduce detailed processes or maybe you need to introduce new set of tools, such as a real-time collaboration platform.
When you are evaluating your processes, it is highly possible that you realize that your staff does not have the knowledge they need to overcome certain problems. Following my question above, it can be highly possible that better trained level 1 support (call center staff) could solve the problems on the spot rather than trying to connect to level 2 support. Or you could see that there is a knowledge gap between level 1 and level 2 support staff, which leads to transferring calls between support teams, increasing the waiting time. Maybe it is the level 2 support staff that should receive the training.
Many organizations fall into the fallacy that once the staff is hired and trained, they know what they are doing. However, business conditions and customer expectations change and the training has to be renewed. You should approach training in a structured way: it should be continuous, tied to business processes, mapped to desired outcomes, be part of the annual review, which should include reviews from customer feedback and knowledge evaluation based on present conditions.
Next, you need to optimize your resources. The resource optimization is closely matched to your customers’ expectations. Following our example above, how do your customers feel when they are waiting for minutes listening “all our support professionals are busy, please hold the line” response? What hours of the day the customer waiting times are longer? Does adding more level 1 staff to the – say – 1000 – 1400 hours will reduce waiting times? Do you require more level 2 support people during 1900 – 0300 hours? Or do you need more level 2 staff? Maybe your web site is not able to keep up with the current customer connections? By optimizing your human and machine resources you can match your support to the customer expectations.
In case that you are producing goods, rather than services, you need to evaluate all these with your product development, production and delivery personnel. If the product has design flaws that lead to dissatisfied customers blocking your level 1 staff, you need to involve the design and production teams to the analysis. Again, a properly prepared CSAT survey will point you to the right problems, as well as assisting the teams by understanding the priority features and functionalities and eliminating the unnecessary ones.
As you have seen by now, collecting CSAT data gives you absolutely nothing, and in some cases mislead you, if not properly analyzed. On the opposite, if you employ the right techniques and ask the right questions, it can help you keep your customers satisfied and loyal. From the company’s perspective collecting data correctly, analyzing it in detail and deploying it the right way will have meaningful business results with better performance.