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[ohio_text text_typo=”null”]If you are a business that truly cares about its customers, you are likely to put a lot of focus on your support services. In the digital age, you can track tens, if not hundreds, of customer support metrics. You can continuously evaluate your efficiency and acquire actionable insights by establishing and tracking your customer service KPIs. 

Measuring your performance and working strategically towards providing satisfying results to your customers is the only way to become a company that provides excellent support services

For the sake of simplicity, we are going to discuss the most important customer support metrics in this article.  


Customer Satisfaction Score | CSAT

After a ticket has been resolved, a customer satisfaction survey is usually offered to obtain feedback.

Customers’ satisfaction levels are determined by having them complete this brief survey in which they rank their whole experience on a scale. 

It could be as simple as asking them to rate their experience on a scale of one to five. 

It is recommended that you track both, the CSAT and the number of people who filled the survey form. 

You might be able to increase CSAT without putting in much more effort if you can get more people to finish the survey. Angry consumers are the most vocal. Encourage satisfied clients to participate in the survey in order to obtain a more balanced measure. 


Net Promoter Score | NPS

Measure how likely your customers are to recommend your product to others. 

We could go about asking – ‘How likely it is that you will promote Toolpill’s services to a friend on a scale of 10?’

Promoters: Customers who rate 9 or 10

Passives: Customers who rate 7 or 8

Detractors: Customers who rate anything between 0 to 6 

NPS = Percentage of promoters – Percentage of detractors


Customer Retention Rate | CRR

The percentage of existing customers who stay with you after a certain amount of time is known as customer retention rate. Your customer retention rate can help you better understand what keeps consumers coming back to your business and can also indicate areas where customer service could be improved.

Customer retention rate = (Number of customers at the end of a period – Number of new customers acquired in that period)/ Number of customers at the beginning of the period. 

Suppose you have 150 customers at the beginning of the season. You found 32 new customers during the season, and by the end of it have a total of 158 customers. 

The CRR = (158-32)/150*100, which is 84% 


Customer Churn

The churn rate, also known as attrition rate, is the rate at which consumers discontinue doing business with a company after a certain amount of time has passed. The higher your churn rate, the fewer clients are willing to buy from you. The smaller your customer turnover, the more clients you’ll retain.

Customer Churn Rate = (Customers beginning of the month – Customers end of the month) / Customers beginning of the month.

Suppose you have 150 customers at the beginning of and only 136 by the end of it, 

Customer Churn Rate during the month = (150-136)/150, that is 9.33%


Ticket Backlog

This represents the total number of unresolved customer service tickets. It’s crucial to keep track of this number so you can see if your customer care team is running well and if there’s anything else you can do to handle these tickets. You should be able to filter these unresolved issues by category, allowing you to spot any areas of weakness and prioritise your next measures. 

Digital solutions like an AI bot can help significantly lower the backlog of unresolved cases


Average Ticket Resolution Time

You can calculate it by dividing the overall time spent resolving tickets over a certain time period by the total number of tickets resolved during that time period.

Instead of focusing on response time, effective support teams strive to improve resolution time. Efficient support replies are usually indicated by a short resolution time. Customers are given all of the information they require, plus more.

Now that we have discussed these metrics in detail, why don’t you get started and put data-oriented systems in place?[/ohio_text]

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