To business analysts and project managers, Service performance is a matter of making sure that the processes are performing according to the specifications. To developers, Service performance is a matter of making sure that the functional requirements are being met. To the business, Service performance is a matter of meeting Key Performance and Agility Indicators. And so, to properly define Service Performance, we have to look at the concept from all these perspectives.
The relationship between service performance measures and the customer measures determines the operational improvements that can achieve the required increase in customer satisfaction. This is used to make improvement plans that specify how the current design should be improved.
To ensure that the right information is accurately collected and available when needed, the service management term’s first priority should be to set up processes for regularly collecting quantitative measures of the performance of the service.
The correlation between the financial and customer measures determines the revenue generating potential of the service. This correlation can indicate the increase in customer satisfaction needed to achieve a specified market share gain or a strategic financial objective, which can then be used to set service improvement targets or new performance standards.
The relationship between service performance measures and the customer measures determines the operational improvements that can achieve the required increase in customer satisfaction. This is used to make improvement plans that specify how the current design should be improved.
This procedure should follow the steps listed below:
Step 1: Select the design attributes to be analyzed.
Step 2: Measure the performance effectiveness of each selected attribute
Step 3: Measure the capability of each selected attribute
Step 4: Measure the efficiency of key processes
Step 5: Identify attributes whose performance does not conform to standards or shows unusual change.
Step 6: Analyze the attributes identified in Step 5 in detail to determine the cause for poor performance or for unusual change in performance.
Step 7: Decide whether any corrective action is necessary, and if so, what steps need to be taken.
Step 8: Take the corrective action. Before we move on, it is important to explain the term changes in performance. Many teams take this to automatically imply that only changes in a negative direction are worthy of further analysis. Improvement in performance is often treated as good news and ignored.
Need for accurate data:
What is the key determinant of the service management team’s ability to successfully execute the eight steps described above? Note that three steps begin with words “measure” and one step contains the word “analysis”. It is impossible to underestimate the importance of quantitative analysis using current and accurate data. This requires the following:
Metrics must be correctly defined to ensure that the right information is available. Data collection procedures must be implemented and tested so that accurate information is available. Aggregation, reporting, and distribution processes should be designed so that the information is available to the team in a timely manner.
Team members should be trained in interpreting analysis results, charts, and diagrams. The data should be stored in a system that allows easy access to historical performance information. Designing a system and / or a process to satisfy these requirements, called a performance management system, should be the first activity of the service management team. This activity should be begun while the service is being implemented so that the system is in place when the service goes into operation.
In practice, however, many teams responsible for managing a newly designed service do not take the time to develop a complete and integrated performance management system. This is usually because the teams are assembled several months (or years) after the service is in operation, by which time it is difficult to replace the dozens of local reports and data collection techniques that are already in place.
Many service management teams believe they base their decisions on quantitative data, but very often the metrics used are inaccurate or incomplete, and present an erroneous picture of the performance of the service. Incorrect data is sometimes more detrimental than no data at all, since misleading or even counter-intuitive results obtained may be unquestionably accepted just because they are presented as the output of quantitative analysis.
Metrics for Measuring Customer Service Performance
Below are the top customer service metrics examples businesses can monitor. When used in combination with each other, these KPIs can provide a well-rounded view of your performance and success.
- Customer Service Abandonment Rates
We’ve found that about seven in 10 consumers will hang up a call or exit a chat if they’ve had to wait a frustrating amount of time without receiving customer support. Ideally, your call or chat abandonment rate would be zero. To calculate it, divide the number of abandoned customer service inquiries by the total number of inquiries.
- Average Resolution Time
Consumers are usually happiest when their issue can be resolved quickly. This metric will help you see how your performance stacks up. To find your average resolution time, find the sum of all case resolution durations, then divide this by the total number of customer cases.
- Customer Effort Score (CES)
CES is one of the newer customer service measurement metrics to monitor. It essentially tracks how much effort your customers feel they have to dedicate toward resolving an issue. The more effort required, the more frustrating the experience. Following a customer service interaction, you can capture these feelings with a Likert scale question.
- Customer Satisfaction Score (CSAT)
CSAT measures your customers’ feelings immediately following an interaction with a customer service agent. As with CES, you can send out a Likert scale survey question to capture your customer’s satisfaction level on a scale from one to five.
- Customer Retention Rate
This customer satisfaction metric is the opposite of customer churn rate, but both show how likely your customers are to stick around. To calculate retention rate, first subtract the number of new customers from the total at the end of a specific period of time. Then, divide the number of customers you retained by the total number of customers you had at the start of that period. A figure close to 1 indicates high retention.
- First Response Time
Customers expect immediate assistance, and you can find out how quickly they’re getting support by calculating the first response time. Simply calculate the average duration between the moment a customer reaches out and how long it takes a customer service agent to respond.
- Resolution Rate
To calculate the overall resolution rate, subtract the number of unresolved cases from the number of customer inquiries, then divide this by the total number of inquiries. The fewer left unresolved, the more successful your customer service has been. You can adapt this metric by figuring out the first contact resolution (FCR) rate, which identifies just the cases resolved during the first interaction.
- Net Promoter Score (NPS)
NPS is a popular metric for how to measure customer service effectiveness and gauge customer satisfaction. As with CSAT and CES, you can gather customer feedback with this type of survey question: “How likely are you to recommend our brand to a friend?” High responses indicate higher levels of satisfaction with your company and the customer experience.
- Sentiment Analysis
Also known as opinion mining, sentiment analysis involves scanning the language a customer uses to see if it skews positive, negative or neutral. Conducted through natural language processing technology, this is a great way for agents to get an immediate read on customers’ emotions and adjust their approach accordingly.