In this article we cover 21 essential KPIs in customer service that every customer support team should be using. We also include formulas and industry specific examples.
21 Customer Service KPIs
1. Customer Satisfaction Score (CSAT)
Measures the overall satisfaction of your customers with your product or service. It helps to identify areas of improvement to enhance the customer experience.
Formula: (Number of Satisfied Customers / Total Surveyed Customers) x 100
Example: In a software company, 80 out of 100 surveyed customers are satisfied with their recent support experience. CSAT = (80/100) x 100 = 80% satisfaction rate, indicating generally positive customer sentiment.
2. Customer Effort Score (CES)
Assess the ease of solving issues or getting help from your customer service. A lower score indicates a smoother and more convenient customer support experience.
Formula: (Sum of Effort Ratings / Number of Surveyed Customers)
Example: A retail company receives effort ratings from 50 customers with a total score of 180, on a scale of 1 to 5. CES = 180/50 = 3.6, which indicates a moderate level of effort required from customers to get their issues resolved.
3. First Response Time (FRT)
Calculates the average time it takes for your support team to provide an initial response to a customer inquiry. Quicker response times often lead to higher customer satisfaction.
Formula: Sum of all First Response Times / Total Number of Tickets
Example: An online store has a total of 100 tickets, with a sum of 500 minutes for all first response times. FRT = 500/100 = 5 minutes, meaning the support team responds, on average, within 5 minutes to each inquiry.
4. First Contact Resolution
Determines the percentage of customer issues resolved during the first interaction with support. A higher percentage indicates efficient problem-solving and customer satisfaction.
Formula: (Number of Issues Resolved in First Contact / Total Number of Issues) x 100
Example: In a telecom company, 40 out of 50 issues are resolved in the first contact with customer service. First Contact Resolution = (40/50) x 100 = 80%, suggesting that the majority of issues are resolved quickly and effectively.
5. Cost Per Resolution
Calculates the average cost incurred to resolve a customer support ticket. This KPI helps businesses evaluate their customer service efficiency and identify potential cost-saving opportunities.
Formula: Total Monthly Operating Expense / Total Number of Tickets
Example: A SaaS company has a total monthly operating expense of $10,000 and receives 200 customer support tickets. Cost Per Resolution = $10,000/200 = $50, which means the average cost of resolving a single ticket is $50.
6. Net Promoter Score (NPS)
Measures the likelihood of your customers recommending your business to others. A higher NPS indicates strong customer loyalty and potential for growth through positive word-of-mouth referrals.
Formula: (Percentage of Promoters - Percentage of Detractors) x 100
Example: A hotel has 70% promoters (satisfied customers likely to recommend) and 10% detractors (dissatisfied customers unlikely to recommend). NPS = (70-10) x 100 = 60, which signifies a positive net promoter score and a good reputation among customers.
7. Customer Retention
Calculates the percentage of customers who continue doing business with you over a specific period. High customer retention rates indicate customer loyalty and satisfaction with your products or services.
Formula: (Number of Customers Retained / Number of Customers at Start of Period) x 100
Example: A subscription box service retains 90 out of 100 initial customers after a month. Customer Retention = (90/100) x 100 = 90%. This high retention rate shows that the majority of customers are satisfied and continue to engage with the service.
8. Volume by Channel
Monitors the number of customer support interactions across different channels, such as phone, email, and social media. This KPI helps to identify the most popular channels and allocate resources accordingly.
Formula: Number of Tickets per Channel
Example: A travel agency receives 200 phone tickets, 150 email tickets, and 50 social media tickets. This indicates that phone support is the most popular channel, requiring the most attention and resources.
9. Ticket Backlog
Measures the number of unresolved customer support tickets at a given time. This KPI helps identify bottlenecks in the support process and highlights areas for improvement.
Formula: Total Number of Open Tickets - Total Number of Closed Tickets
Example: An eCommerce platform has 500 open tickets and 400 closed tickets. Ticket Backlog = 500 - 400 = 100, which signals a need to improve ticket resolution rates to reduce the backlog.
10. Resolution Time
Calculates the average time it takes for your support team to resolve customer issues. This KPI helps assess the efficiency and effectiveness of your customer support processes.
Formula: Sum of all Resolution Times / Total Number of Resolved Tickets
Example: A software development firm has resolved 300 tickets, with a sum of 1,500 hours for all resolution times. Resolution Time = 1,500/300 = 5 hours, meaning it takes an average of 5 hours to resolve a customer issue.
11. Average Handle Time (AHT)
Determines the average time spent by your support team on each customer interaction, including talk time, hold time, and follow-up work. Lower AHT can indicate efficient customer support.
Formula: (Total Talk Time + Total Hold Time + Total After-Call Work Time) / Total Number of Calls Handled
Example: A financial services company has a total talk time of 800 minutes, a total hold time of 200 minutes, and a total after-call work time of 400 minutes for 100 calls. AHT = (800 + 200 + 400) / 100 = 14 minutes per call.
12. Agent Utilization
Calculates the percentage of time agents spend on customer support tasks compared to their total working hours. Higher agent utilization rates can indicate effective resource allocation and efficient support operations.
Formula: (Time Spent on Customer Support Tasks / Total Agent Working Hours) x 100
Example: A call center has agents spending 400 hours on customer support tasks in a week, with a total of 500 agent working hours. Agent Utilization = (400/500) x 100 = 80%, showing a high degree of efficiency in utilizing agent resources.
13. Agent Satisfaction Score (ASAT)
Measures the overall satisfaction of your customer support agents with their working environment, tools, and processes. A high ASAT can lead to lower employee turnover rates and improved customer support quality.
Formula: (Number of Satisfied Agents / Total Number of Agents) x 100
Example: A technology company has 45 satisfied agents out of a total of 50 agents. ASAT = (45/50) x 100 = 90%, indicating that the majority of agents are satisfied with their work environment and support tools.
14. Ticket Escalation Rate
Calculates the percentage of support tickets that require escalation to a higher level of expertise or authority. A lower escalation rate can indicate well-trained and knowledgeable support staff.
Formula: (Number of Escalated Tickets / Total Number of Tickets) x 100
Example: A telecommunications company has 30 escalated tickets out of a total of 500 tickets. Ticket Escalation Rate = (30/500) x 100 = 6%, which shows a relatively low rate of escalation, suggesting capable support staff.
15. Support Costs vs. Revenue
Compares the cost of providing customer support with the revenue it generates. This KPI helps to determine the profitability and efficiency of your customer support operations.
Formula: (Total Support Costs / Total Revenue) x 100
Example: A retail company has support costs of $50,000 and total revenue of $500,000. Support Costs vs. Revenue = ($50,000/$500,000) x 100 = 10%, indicating that the support costs represent 10% of the total revenue.
16. Customer Lifetime Value (CLV)
Estimates the total revenue a customer will generate for your business throughout their entire relationship with your company. A high CLV can indicate strong customer loyalty and the effectiveness of your customer support in retaining customers.
Formula: Average Purchase Value x Purchase Frequency x Average Customer Lifespan
Example: An online subscription service has an average purchase value of $20, a purchase frequency of 12 times per year, and an average customer lifespan of 3 years. CLV = $20 x 12 x 3 = $720, which represents the estimated revenue generated by a single customer over their lifetime with the company.
17. Service Level Agreement (SLA) Compliance
Measures the percentage of support interactions that meet or exceed the agreed-upon service levels. A high SLA compliance rate indicates that your support team is delivering on its promises to customers.
Formula: (Number of Tickets Meeting SLA / Total Number of Tickets) x 100
Example: A logistics company has 900 tickets meeting their SLA out of a total of 1,000 tickets. SLA Compliance = (900/1,000) x 100 = 90%, showing a high level of compliance with the agreed-upon service levels.
18. Knowledge Base Usage
Tracks the number of customers who use your knowledge base or self-help resources to resolve their issues. Higher usage rates can indicate effective self-service tools and reduced support workload.
Formula: Number of Knowledge Base Visits / Total Number of Support Interactions
Example: A software company has 3,000 knowledge base visits and a total of 5,000 support interactions. Knowledge Base Usage = 3,000 / 5,000 = 0.6, which means that 60% of customers use the knowledge base to find solutions to their issues.
19 Social Media Response Time
This key performance indicator measures the average time it takes for your support team to respond to customer inquiries or complaints on social media platforms. Faster response times can lead to improved customer satisfaction.
Formula: Sum of all Social Media Response Times / Total Number of Social Media Responses
Example: A fashion brand has a sum of 400 minutes for all social media response times and a total of 100 social media responses. Social Media Response Time = 400 / 100 = 4 minutes, indicating that the support team responds to customer inquiries on social media within an average of 4 minutes.
20. Chatbot Interaction Rate
This KPI determines the percentage of customer support interactions handled by chatbots rather than human agents. A higher chatbot interaction rate can indicate effective automation and efficient use of resources.
Formula: (Number of Chatbot Interactions / Total Number of Support Interactions) x 100
Example: A financial services company has 1,500 chatbot interactions out of a total of 4,000 support interactions. Chatbot Interaction Rate = (1,500/4,000) x 100 = 37.5%, suggesting that chatbots handle a significant portion of customer support interactions, freeing up human agents for more complex tasks.
21. Ticket Backlog
Calculates the number of unresolved customer support tickets at any given time. A low ticket backlog indicates that your support team is efficiently resolving customer issues.
Formula: Total Number of Unresolved Tickets
Example: A travel agency has 120 unresolved customer support tickets in their queue. This ticket backlog can help the agency identify areas where they need to improve their support process or allocate additional resources to resolve the backlog and maintain customer satisfaction.
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