15 Best SaaS Customer Support Metrics To Track This 2023
For a SaaS business, the top priority is providing the best user experience possible. That means your SaaS solution should be user-friendly, provide useful features, and encounter as few technical difficulties as possible.
However, these technical issues can be inevitable, which is why SaaS customer support exists. Your support team is there to provide a seamless customer experience and help users with any issues they may have.
Now, knowing how well your SaaS customer support is performing is essential in maintaining or improving the user experience. That’s why SaaS customer support metrics can be so helpful.
These metrics measure key performance indicators (KPIs) related to customer service, such as response time and resolution rate. By tracking these KPIs, you can quickly identify areas of improvement and make sure your SaaS solution remains user-friendly and provides the best possible experience for customers.
In this article, we’ll discuss the 15 essential SaaS customer support metrics you should be tracking.
Let’s dive right in.
1) Conversation Volume
Your conversation volume is one of the most straightforward SaaS customer support metrics you can track. It refers to the number of conversations your team has with customers on a daily, weekly, or monthly basis.
It’s a good indicator of how active your users are and gives you an idea of the overall demand for support.
You may also track your conversation volume per customer support rep. Doing that can help you determine if your team is getting overwhelmed or underutilized.
2) Customer Satisfaction (CSAT) Score
Though customer satisfaction and retention come from collaborative efforts among different aspects of your SaaS business, customer support plays an integral role in keeping your customers happy.
Your customer satisfaction (CSAT) score reflects how satisfied customers are with their experience of your SaaS product.
Finding Your CSAT score requires two things: A customer satisfaction survey and your score calculation.
The Customer Satisfaction Survey
Finding your CSAT score starts with a survey asking a question like this: “On a scale of 1 to 5, how satisfied are you with our SaaS solution?”
However, since we’re talking about measuring the performance of your customer support efforts, you can customize the question accordingly.
It can go like this” “On a scale of 1 to 5, how satisfied are you with the technical support you received?”
The scale would have the following equivalents:
- 1 – Extremely Disappointed
- 2 – Somewhat Disappointed
- 3 – Neither Satisfied Nor Disappointed
- 4 – Somewhat Satisfied
- 5 – Extremely Satisfied
Obviously, you’re going to ask this survey at the end of every customer support conversation.
To draw more insights about how your customer support team performed, you can also add some follow-up questions to your survey.
Here are some examples:
- How knowledgeable was the support team member?
- Was your issue resolved to your satisfaction?
- Was your problem solved in a timely manner?
Getting answers to these questions can help you pinpoint areas of improvement.
Calculating Your CSAT Score
Your SaaS customer support’s CSAT score is calculated by dividing the total number of “satisfied” responses (4 and 5 ratings) by the total number of responses. The result is expressed as a percentage.
For example, if 100 respondents answered your survey, and 70 marked 4 or 5 rating, then your SaaS customer support effort’s CSAT score would be 70%.
This metric helps you measure how well your SaaS customer support team is performing and how happy customers are with their SaaS experience.
The CSAT score benchmark for the SaaS industry is at 77%. True, that could be a high bar to aim for. But that’s what it takes to be competitive in the SaaS space today.
3) Net Promoter Score (NPS)
Your SaaS customer support’s Net Promoter Score (NPS) is another survey-based metric worth monitoring. It measures the likelihood of customers recommending your SaaS solution to their friends and family.
There are three steps to finding your NPS score: Send the NPS survey, group your respondents, and calculate your NPS rating.
Let’s talk about them one by one.
The Net Promoter Score Survey
Like the CSAT survey, you can launch an NPS survey periodically or after a customer’s interaction with your customer support team,
You will use a survey asking a question like this: “On a scale of 0 to 10, how likely are you to recommend our SaaS solution to someone else?”
And like the CSAT survey, you may also ask follow-up questions to get more detailed answers about what your customers like and don’t like.
Grouping Your Survey Respondents
After you have collected the survey responses, it’s time to group them based on their answers to the survey.
You can divide your respondents into three groups:
- Promoters (Scored 9 or 10): Promoters are very happy customers who may drive word-of-mouth marketing by recommending your SaaS product to their friends and colleagues.
- Passives (Scored 7 or 8): These are customers who are somewhat satisfied with your SaaS product but may still decide to switch to another SaaS provider if they see better offers.
- Detractors (Scored 0 to 6): These are dissatisfied customers who will likely spread negative word-of-mouth about your SaaS solution.
Calculating Your SaaS Customer Support NPS Score
To calculate your overall NPS score, subtract the percentage of Detractors from the percentage of Promoters. This could range from -100 (if all are Detractors) to 100 (if all are Promoters).
For example, if 50% of respondents are Promoters and 10% are Detractors, then your SaaS customer support effort’s NPS score would be a positive 40.
This metric helps you measure how well customers view your SaaS product in comparison to others and shows whether they’d recommend it to other people.
At the bare minimum, your NPS score should be more than 0. If it’s not, then you know it’s time to take action and improve your SaaS customer support efforts.
For SaaS business, the average NPS score should be around 30 to 50.
This means you have a considerable gap between the number of Promoters and the number of Detractors. However, you should still think of ways to turn Passives into Promoters and keep Detractors from churning.
An NPS rating of more than 50 is considered excellent. You should strive for this goal and make sure that your SaaS customer support team is delivering the best possible experience to your customers.
4) Customer Effort Score (CES)
The Customer Effort Score (CES) is yet another survey-based SaaS customer support metric. But this one specifically measures how easy it is for customers to get help or advice from your customer support teams.
The Customer Effort Score Survey
Like the previous two metrics we just discussed, CES involves a question that your customer needs to answer after an interaction with a customer support representative.
With CES, you need to ask them how much effort they put in to get their issue resolved.
However, unlike the previous two we discussed, CES does not necessarily require a number-based scale. To make it more engaging and interesting to your users, you could use emoticons or other visual items to help them express their thoughts.
Still, if a number-based scale is still more appropriate for your customers, then by all means, use that as well.
Calculating Your Customer Effort Score
If you’re using a number-based scale on your CES survey, calculating your CES is pretty straightforward.
But even if you have a visual-based scale, you still need to calculate a numerical score for your SaaS customer support team’s CES. You can do that by assigning a numerical value to each option.
For example, if you’re using a 3-point scale with emojis, then you can assign 1 to the sad emoji, 3 to the neutral emoji, and 5 to the happy emoji.
Now, to calculate your CES rating, get the average of all the responses you have received.
For example, let’s say you have 100 customers who got in touch with your customer support team within the month. Imagine 50 of these respondents gave a score of 5 (happy emoji), then 25 gave a score of 3 (neutral emoji), and 25 gave a score of 1 (sad emoji).
In that case, the calculation for your CES would be as follows: ((50 x 5) + (25 x 3) + (25 x 1))/100 = 3.75.
And that’s your SaaS customer support team’s CES score for the month. A higher number indicates that your SaaS customers are finding it easier to get help from your customer support team.
According to CEB Global, a CES above 2 is considered good. If it’s not, you should look into ways to reduce customer effort and make your SaaS customer support system more efficient.
5) Resolution Rate
Let’s take a break from survey-based metrics and talk about the resolution rate.
The SaaS customer support team’s resolution rate is the percentage of SaaS issues they managed to resolve during a given time period.
It’s one of the most important SaaS customer support metrics because it directly reflects how efficient and capable your SaaS customer support team is in resolving SaaS related issues for customers.
To calculate your resolution rate, simply divide the number of successfully resolved cases by the total number of cases received within the same period.
For example, let’s say that within a 30-day period, your customer support teams received 500 cases and successfully resolved 475 of them. In that case, your SaaS customer support team’s resolution rate would be 95%.
A higher resolution rate indicates that your SaaS customer support team is efficient and capable in resolving SaaS related issues for customers. On the other hand, a lower resolution rate could be an indication that there is some room for improvements to make your customer support process more streamlined and effective.
6) First Contact Resolution Rate (FCR)
First contact resolution rate is another SaaS customer support metric that measures how efficient your SaaS customer support team is in resolving SaaS related issues for customers.
However, this one specifically looks at the percentage of SaaS-related issues that were resolved with just a single interaction between the customer and the customer support representative.
To calculate your first contact resolution rate, simply divide the number of successful resolutions on first contact by the total number of cases received.
For example, let’s say that within a period of 30 days, your SaaS customer support team received 500 cases and successfully resolved 375 of them in one interaction with their customers. In this case, your SaaS customer support team’s first contact resolution rate would be 75%.
The industry benchmark for FRC Rate ranges from 44% to 92%, with an average of 71%.
A higher FCR rate indicates that your SaaS customer support team is more efficient in resolving SaaS related issues for customers. A lower FCR rate could be an indication that there is some room for improvements to make your customer support process more streamlined and effective.
Now, the thing about FCR is that it counts all support tickets equally regardless of how hard or how easy it is to resolve. And some support concerns are just too complex that you can’t solve them on the first go.
That’s why SaaS businesses also measure the Net First Contact Resolution Rate.
Your Net FCR is basically your FCR rate minus cases that can’t possibly be resolved on the first contact due to their complexity.
Let’s take our earlier example. Let’s say that, out of the 500 support tickets your team received, 50 were complicated SaaS related issues that can’t be solved on the first go. In this case, your Net FCR would be 375/(500-50) = 87.5%.
7) Average Interactions Per Resolution
As we just mentioned, there will always be support concerns that you just can’t resolve on the first attempt. However, you should always try to resolve each ticket as quickly as possible.
To help you with that, you should track your number of interactions per resolution.
Just as its name suggests, this customer support metric looks at how many interactions it takes your SaaS customer support team to resolve an issue.
To calculate this metric, simply get the average number of interactions it takes for your support team to resolve a technical issue.
A good average number of interactions per resolution is around the 4 to 7 range. But you should always aim to keep it at 4 interactions or lower.
This SaaS customer support metric is particularly useful for SaaS businesses because it helps you identify any bottlenecks in your SaaS customer support process that may be causing delays in the resolution of SaaS-related issues.
Once identified, you can take the necessary steps to fix them and streamline your SaaS customer support process.
8) Average Resolution Time
Another way of measuring how quickly you can solve customer support issues is by looking at your average resolution time, also known as average handle time.
Average resolution time measures the amount of time it takes for your SaaS customer support team to resolve an SaaS-related issue.
As its name suggests, it is simply the average amount of time it takes for your SaaS customer support team to resolve SaaS related issues.
Your goal should always be to keep this number as low as possible while still maintaining a high quality of service for your customers.
Of course, resolution times will vary depending on the complexity of the problems your customer support team is dealing with. But it’s important to keep an eye on your average resolution time and make sure that it’s within a reasonable range.
9) Average Response Time
One crucial factor in providing SaaS customer support is responding to SaaS-related issues in a timely manner.
That’s why SaaS businesses should also measure their average response time. Obviously, this SaaS customer support metric looks at the amount of time it takes for your customer support team to respond to support concerns.
Now, standards will vary depending on which support channel the customer is using. For example, your customers will expect your team to respond to a live chat sooner than you would an email.
That’s why you should track your average response time for each support channel that you have.
For email support, it should take you no more than 24 hours to respond to SaaS-related issues. If a customer reaches out to your social media for customer support, you should respond within an hour. As for live chat, you should aim for at least 3 minutes of response time.
10) Highest Wait Time
If you’re intent on optimizing your customer support response time, you should also track the highest wait time. This is simply the longest time that a customer has had to wait for a response from your customer support team.
This customer support metric is important because it allows you to identify any issues in how quickly your SaaS customer support team responds to SaaS-related issues.
If the highest wait time of one of your customers is too high, then that’s a sign that something must be wrong with your SaaS customer service process and needs to be fixed as soon as possible.
11) Cost Per Conversation
Another SaaS customer support metric to track is the cost per conversation. This SaaS customer service metric measures how much money your SaaS business spends on resolving SaaS-related issues for each customer interaction.
To compute this, you will need to consider all costs associated with having support conversations with your customers.
These include the following costs:
- Customer support team salary and benefits
- Training costs for support team
- License fees for customer support tools
To calculate your cost for conversation, simply divide the total cost of providing customer support by the number of SaaS-related issues resolved within a period of time.
For example, let’s say your SaaS business spends $5,000 a month for customer support. If you also solved 500 SaaS-related issues during that same period, then your cost per conversation would be $10.
Tracking your cost per conversation is a good way to monitor the cost-efficiency of your SaaS customer support team. It may also help you identify any cost-saving opportunities that you can apply to reduce the overall costs associated with SaaS customer support.
12) Customer Health Score
One of the most holistic and versatile ways to measure your customers’ experience with your SaaS product is by measuring the customer health score for each of them.
It gives you an overall rating of each customer’s “health” based on their actions and interactions with your SaaS business.
Now, finding the customer health score takes a few steps:
Identify Customer Behavior That Affects Health Score
First, identify the SaaS-related customer behaviors that are important for measuring the customer health score. You can set any action or metric that may affect it.
But since we’re specifically looking at customer support here, try identifying those that reflect the quality and efficiency of your customer support.
These could include factors like resolved (or unresolved) support requests or average response time.
Assign Values to Each Behavior
Once you have identified the SaaS-related customer behaviors, assign each one a value according to its importance. You may even assign a negative value for events that negatively impact customer health.
For example, resolved support requests could be worth 30 points. Unresolved tickets may set you back with -40 points each. While each hour added to your response time could be worth -10.
Calculate Customer Health Score
Once you have identified the SaaS-related customer behaviors and assigned each one a value, it’s now time to calculate the customer health score for each SaaS user.
You would have to multiply each action’s importance value to their frequency of occurring.
For example, let’s say that for one particular customer, you’ve resolved 3 support requests and failed to solve 1, with an average response time of 1 hour.
You would have the following health scores for each action:
- Resolved support tickets: 3 x 30 = 90 points
- Unresolved support ticket: 1 x -40 = -40 points
- Average response time: 1 x -10 = -10 points
- So, the total health score for your SaaS customer would be (90 – 40 – 10) = 40.
For example, if 5 SaaS customers have left your SaaS product in a month and you had 100 SaaS customers at the beginning of that month, then your customer churn rate would be 5%.
Benchmarks for the customer churn rate can vary depending on various factors, including your SaaS company’s maturity.
According to Messaged, it’s normal for SaaS startups and small to medium-sized SaaS companies to encounter 10% to 15% customer churn rate in their first year. But you should have a monthly churn of 3% to 5% after that.
On the other hand, more mature SaaS businesses are expected to have more robust customer retention strategies. As a result, the benchmark for bigger SaaS companies range from 1% to 4%.
Revenue Churn Rate
This SaaS metric measures how much of your recurring revenue is lost due to SaaS customer churn.
You can calculate revenue churn rate by dividing the total amount of recurring revenue lost in a given time period by the total recurring revenue during that same time period.
For example, if you had $1,000 worth of monthly recurring revenue (MRR) in a month but lost $100 worth of MRR due to customer churn in that same month, then your revenue churn rate would be 10%.
14) Customer Lifetime Value (CLV)
Customer lifetime value (CLV) is a SaaS metric which measures the amount of revenue that a SaaS customer will bring in for your SaaS product over time.
It’s important to track this SaaS customer support metric because it gives you an idea of how much each SaaS customer is worth and allows you to prioritize SaaS customers according to their CLV.
Calculating Your CLV With Historical Data
If your SaaS business has been around for several years, you probably already have enough historical data to establish an average length of time that a customer stays with your SaaS product. And that would be your average customer lifespan.
Another metric you would need for this is the average revenue per user (ARPU). As its name says, it is the average revenue that you receive from each SaaS customer in a given time period.
Once you have both metrics, you can calculate the CLV of your SaaS customers by multiplying the average customer lifespan and ARPU.
For example, if your typical customer has an average customer lifespan of 6 years and an annual ARPU of $1,000 per year, then your CLV for each SaaS customer would be 6 x $1,000 = $6,000.
Calculating Your CLV Without Historical Data
If you don’t have enough historical data to establish an average customer lifespan, you can estimate it by dividing 1 by your customer churn rate.
Using this, calculating your CLV would simply be dividing your ARPU by your churn rate.
For example, if your SaaS business has an annual ARPU of $1,000 and a customer churn rate of 10%, then your CLV would be 1000/0.1 = $10,000.
15) Customer Retention Cost (CRC)
Customer retention cost is a SaaS customer support metric that measures the amount of money you have to spend in order to retain existing SaaS customers.
These include the following costs:
- Salary and benefits for customer support team, customer success team, account managers, etc.
- Onboarding and training costs
- Customer marketing costs
- License fees for customer support and customer success tools
- Loyalty program costs
To calculate your SaaS customer retention cost, you have to add up all the costs associated with retaining SaaS customers and divide it by the total number of SaaS customers in a given time period.
For example, if your SaaS business has spent $20,000 on customer support costs for 100 SaaS customers during a month, then your customer retention cost would be 20,000/100 = $200 per SaaS customer that month.
By tracking this SaaS customer support metric, you can get an idea of how much it’s costing you to retain SaaS customers and make better decisions when it comes to managing your budget.
Final Thoughts About SaaS Customer Support Metrics
SaaS customer support metrics are key to understanding how SaaS customers interact with your SaaS product. More importantly, they help you see where you should focus your efforts on when it comes to SaaS customer success.
By tracking the SaaS customer support metrics mentioned in this article, you’ll be able to better understand SaaS customer behaviors, anticipate SaaS customer needs, and make more informed decisions about SaaS customer retention strategies.
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