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Key Metrics in Customer Service: Direct Response
The metrics you want to analyze in customer service in banking may be collected from different sources, the first of which is direct response. What should you evaluate here?
Ratings
The first and foremost metric that you collect directly from the customers is the rating they give in a survey provided after their encounter with the customer service agent. It’s a valuable source of information both about your team members’ performance and about the processes as a whole.
You shouldn’t rely fully on ratings, though. After all, dissatisfied customers might give low ratings even to the greatest customer service – for instance, because your agent couldn’t help the client with a task that would be against the company policy and regulations.
Mystery Shopping Scores
Mystery shopping scores are an integral part of your customer service team evaluation. They provide you with information on how the team implements the procedures in practice, giving you insights into the overall team performance.
Naturally, mystery shopping scores cannot be taken as a major part of the overall evaluation. While they do play a crucial role in customer support in the digital world of banking, they are not conducted frequently enough to be the sole basis for your analysis.
Complaints & Compliments
You can also use the number of complaints and compliments as a metric to evaluate your customer service team and procedures. Here, you can use both the raw numbers or analyze each complaint and compliment to eliminate those that aren’t exactly helpful (for instance, the complaint is about not undertaking certain steps that would simply be… impossible).
You may even use AI to help you pave out the unhelpful complaints. This will accelerate the process. However, don’t remove all the procedure-related entries – if a procedure can (technically) be changed, it’s worth taking it into consideration.
Customer Service in Digital Banking: Process Metrics
You can also extract valuable metrics from the data on your customer service processes. Here, you should focus mainly on two of them.
Response Times
Firstly, you should collect information on the time it takes your customer service agents to respond to each ticket on average. If the values are too high, this means that you might need to either hire more agents, or implement solutions that will make the current ones more productive, such as our AI banking assistant.
Transaction Times
You can also measure the transaction times in relation to the established times for each product. This way, you’ll see how your customer service performs against its KPIs.
Performance Metrics for Customer Service in Banking
There are several performance metrics that may also help you evaluate your customer service team. These include:
Products per Customer
An effective customer service team prepares accurate product proposals, which leads to more sales. Therefore, a high number of products per customer indicates that your CS is excellent.
You can improve this metric by using AI-based tools. For example, our digital customer service platform, LiveBank, gathers data on every client and uses it to generate personalized product proposals.
Customer Lifetime Value (CLV)
Calculating the number of products per customer might not be enough. After all, a customer with just a bank account and a mortgage might bring more value to your organization than one with just 2-3 smaller loans. Therefore, it’s important to include CLV as one of your metrics when evaluating the customer service team in banking.
Customer Churn
The better the customer service, the better the customer experience. And, with excellent customer experience comes customer loyalty.
While you do not have full control over the churn, it’s still an important metric to include when analyzing your customer service performance. You can even take it further and compare it with the average churn in banking to juxtapose your customer service effectiveness with your competitors.
The Number of Referrals
Customer referrals are a sign of high customer satisfaction. Therefore, their high number typically indicates that your customer service teams work properly. However, do not assume that low numbers equal bad customer service – this isn’t a standalone metric to base your evaluation on, but rather one that helps you confirm or disprove your conclusion based on the other ones.
Conclusions
As you can see, there are many metrics that you can use to evaluate customer service in banking. The best analysis takes all of them into consideration, so if you do not collect any of them – start doing so now.
You might also read: How to Leverage Customer Feedback for Continuous Improvement in Digital Banking