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Top 17 Customer Success Metrics & How to Track Them

May 07, 2024
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13 min read
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Table of contents

Customer success is a crucial function in any SaaS business. It drives retention and expansion revenue, both of which are very important for long-term growth. 

So, how do you gauge the performance of your customer success function? How do you know if they’re doing a good job building customer relationships?

That’s where customer success metrics come in. 

These metrics provide a clear picture of how happy or unhappy customers are, whether or not they’re likely to churn, and how much revenue they can help you drive in the future, amongst other things.

Let’s dive in.

Table of Contents

Key Takeaways

  • Customer Satisfaction Score (CSAT): Measure how dissatisfied or satisfied customers are (on a scale of 1-5 or 1-10) with your product, service, or a specific interaction.
  • Net Promoter Score (NPS): Find out how likely customers are to recommend you to their friends and family on a scale of 0-10.
  • Customer Effort Score (CES): Evaluate how easy or effortless it is for customers to resolve their issues.
  • Churn Rate: Indicates the percentage of customers who stop using a service over a specific period.
  • Customer Lifetime Value (CLV): Estimates the total revenue a business can expect from a single customer account over their relationship, based on purchase value and frequency.
  • Customer Health Score: A composite metric assessing overall customer satisfaction and engagement by analyzing various customer interaction data points.
  • Average Resolution Time: Calculates the average time taken to resolve customer issues.
  • Renewal Rate: Shows the percentage of customers who renew their subscriptions.
  • Customer Engagement Score: Assesses the level of customer interaction with the product and service.
  • First Contact Resolution Rate (FCR): Measures the percentage of customer support inquiries resolved on the first interaction.

The Top 17 Customer Success Metrics

These top 17 customer success metrics will give you deep insights into what your customers like, and dislike, their behavior, product usage patterns, and more. These are pivotal for driving growth and ensuring long-term success in your business. 

1. Customer Satisfaction Score (CSAT)

The Customer Satisfaction Score (CSAT) is a metric to gauge how satisfied your customers are with your business, product or a particular service. The method is very simple. It includes asking customers their level of satisfaction with the following question:

‘How satisfied were you with your experience?’ The customers can rate their responses on a scale of 1 to 3, 1 to 5, or 1 to 10, where 1 represents “Very Dissatisfied” and 3, 5 or 10 represents “Very Satisfied.”

Calculating CSAT Score:

The score is then calculated as:

CSAT% = (No. of satisfied customers / Total no. of responses) x 100

For example: A support team of a business asks its customers to rate their support experience on a scale of 1 to 5. If they get 150 responses and 120 of those customers give a rating of 4 or 5, then the CSAT score for the coffee shop would be:

CSAT = (120/150) x 100 = 80%

Get instant CSAT ratings from customers See Hiver Analytics

2. Net Promoter Score (NPS)

The Net Promoter Score (NPS) is a way to measure how loyal customers are to a company. It’s pretty straightforward: customers are asked, “On a scale from 0 to 10, how likely are you to recommend our product to your friends and family?”

This score helps businesses figure out where they can do better to make sure customers keep coming back.

Calculating NPS:

To calculate the NPS, first, sort customers into three groups based on their ratings. Those who give a 9 or 10 are called Promoters—they really liked the service. Customers who rate it a 7 or 8 are Passives—they’re okay with everything but not super excited. Then, anyone who gives a 6 or below is a Detractor—they aren’t happy.

Then NPS is calculated as:

NPS= {(Number of Promoters – Number of Detractors) / Total Number of Respondents}× 100

This formula gives a score ranging from -100 to 100

Let’s say a business sent out an NPS survey and got back 200 responses. Out of these, 100 were Promoters, 70 were Passives, and 30 were Detractors.

To calculate the NPS, you’d take the number of Promoters (100),subtract the number of Detractors (30),and then divide by the total responses (200). Multiply that result by 100 to get the percentage:

NPS = {(100−30) / 200}×100 = 35

An NPS of 35 means there’s a generally positive feeling from customers about recommending the company’s service to others.
But remember, it’s important to compare this score with other companies in the same industry, as what’s considered a good NPS can vary a lot depending on the industry.

3. Customer Effort Score (CES)

The Customer Effort Score (CES) is a measure used to see how easy it is for customers to use a product or service, find information, or resolve issues. It’s based on customer feedback collected through surveys, where customers rate how much effort they had to put in to interact with the company. 

Calculating CES:

To calculate the Customer Effort Score (CES),ask customers through a survey to rate how easy it was to interact with the company, like using a product, finding information, or solving a problem. The rating is usually on a scale ranging from 1 (very difficult) to 5 or 7 (very easy).

Then, the CES is calculated using this formula:

CES = Sum of all CES scores/ Number of respondents

This calculation provides an average score that reflects how much effort customers felt they had to exert. 

For example, a food delivery business wants to find out its CES score. After each order, they ask customers to rate how easy it was to place their order with a CES survey. Let’s say out of 100 customers: 40  respond with “very easy” and give a score of 7, 35 customers say it was “easy” with a score of 6, and 25 rate it as “neutral” with a score of 5.

To calculate the CES, you’d multiply each group’s score by their number, add them up, and then divide by the total number of responses:

CES = (50 × 7)+(30×6)+(20×5) / 100 = 6.3

With a CES of 6.15 out of 7, it shows most customers found the app straightforward to use, but there’s scope to make it even smoother.

4. Churn Rate

Churn rate is the percentage of customers that stop using your service or cancel their subscriptions over a period of time; like a month or a year. It tells you the number of customers you are losing during that period.

Calculating Churn rate:

To calculate the churn rate, you first need to keep track of how many customers stop using your service or cancel their subscriptions over a set period.

The formula for churn rate is pretty straightforward:

Churn Rate = (Number of Customers Lost During the Period / Total Number of Customers at the Start of the Period) × 100

This calculation tells you the percentage of your customers who left during that time, giving you an idea of how often people are choosing not to continue with your service.

Let’s say a gym starts the year with 800 members. Over the first three months, they see that 40 members decide not to renew their memberships. To figure out the churn rate, you’d use this formula:

Churn Rate = (50/1000) × 100 = 5%

This tells the gym that 5% of their members left during that period. It’s a cue for them to look into why members are dropping out.

Recommended Read: 11 Ways To Reduce Customer Churn

5. Customer Lifetime Value (CLV)

Customer Lifetime Value (CLV) is the total amount a customer is expected to spend on your business during their entire relationship with you. CLV looks at everything they might buy over time, including repeat purchases, giving you an idea of how valuable that customer is to your company in the long run.

Calculating CLV:

You first need to figure out how much a customer spends on average each time they purchase from your company. Then, look at how often they buy over a year and how many years they typically remain your customer.

The formula for CLV goes like this:

CLV=Average Order Value×Number of Transactions per Year×Average Customer Lifespan (in years)

This formula helps you understand the total revenue you can expect from a customer throughout their relationship with your business. 

For example, let’s look at a company that sells online fitness programs. They charge $30 a month and a customer sticks around for about 2 years. Additionally, customers often buy extra workout gear or supplements that add up to about $10 each month. So, the total monthly spending per customer is $40.

Here’s how you’d calculate the Customer Lifetime Value (CLV):

Average Purchase Value: $30 + $10 = $40 per month

Average Purchase Frequency: 1 (they subscribe monthly)

Average Customer Lifespan: 24 months (2 years)

So, the CLV is calculated as:

CLV=$40×1×24=$960

This means each customer, on average, brings in about $960 over their time with the company.

6. Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR)

ARR is the money your company anticipates making from customers annually. MRR, on the other hand, is the predictable revenue you count on each month.

Calculating MRR and ARR:

To calculate Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR),you start by adding up all the money you get from your customers on a regular basis.

The formula goes like this:

  • MRR=Total Monthly Subscription Revenue from All Customers
  • ARR=MRR×12

Let’s say there’s a SaaS business with 100 customers paying $50 a month for a basic plan and another 50 customers $100 each month for an elite plan.

To find out the Monthly Recurring Revenue (MRR):

Basic Plan Money: 100 customers × $50/month = $5,000

Premium Plan Money: 50 customers × $100/month = $5,000

Put them together, and you’ve got an MRR of $10,000.

Now, for the Annual Recurring Revenue (ARR):

ARR=$10,000×12=$120,000

So, with an MRR of $10,000 and an ARR of $120,000, the company knows exactly how much cash is rolling in every month and every year. 

7. Expansion Revenue

Expansion revenue is the extra money a customer brings in beyond what they initially agreed to pay. It usually comes from them buying more stuff or getting extra services, like upgrades or add-ons.

Calculating Expansion Revenue:

Look at what additional purchases or services a customer has made beyond their original agreement. Then, add up all the extra money they’ve spent.

The formula for expansion revenue is pretty simple:

Expansion Revenue = Total Additional Purchases or Services

This shows you how much extra cash a customer is bringing in beyond their initial purchase or subscription.

For example, let’s say a SaaS company sells CRM software. In one month:

  • 20 customers upgraded from a $50 plan to a $100 plan, making an extra $1,000.
  • 30 customers bought a $20 add-on, adding $600.

Total Expansion Revenue for the month: $1,000 (upgrades) + $600 (add-ons) = $1,600.

This shows the company’s success in keeping customers happy and getting them to spend more.

8. Customer Health Score

A customer health score is a metric used to figure out if a customer is likely to stick with or leave your company. It’s helpful for account managers and customer service teams because it shows the risk of a customer leaving, or churning.

Calculating Customer Health Score:

To calculate a customer health score, start by gathering data points about how a customer interacts with your company. This might include how often they use your product, their satisfaction score, support ticket history, and more.

Then, you assign weights to these different factors based on their importance, And then you calculate the health score score, typically on a scale, like from 0 (at high risk of leaving) to 100 (very healthy).

The formula looks something like this:

Customer Health Score = (Usage Score×Weight)+(Satisfaction Score×Weight)+(Support Interaction Score×Weight)+…

This score helps you understand which customers might need more attention to prevent them from leaving and which ones are happy and engaged with your services.

Let’s say a company measures Customer Health Score by looking at a few key things:

  • Product usage (weight: 40%)
  • Customer feedback scores (weight: 30%)
  • Number of help requests (weight: 20%)
  • Account upgrade request (weight: 10%)

Here’s how you calculate the weighted sum:

Multiply each score by its respective weight:

  • Product Usage Frequency:  85×0.40 = 34
  • Customer Feedback Score: 90×0.30 = 27
  • Support Ticket Frequency:  95×0.20 = 19
  • Account Upgrade Requests: 80×0.10 = 8

Add these weighted scores together to get the total Customer Health Score:

Total Score: 34+27+19+8=88

So, the Customer Health Score for this customer would be 88 out of 100. This high score suggests a healthy, satisfied customer who is likely to continue using the service and possibly upgrade.

Recommended read:18 Key Customer Service Metrics + How to Use Them

9. Time to First Value (TTFV)

Time to First Value (TTFV) is another customer success metric, measuring the duration it takes for a new customer to experience the first significant value from the product after purchase. TTFV is a strong indicator of the effectiveness of the onboarding process and the initial user experience.

Calculating TTFV:

TTFV is calculated from the time a customer signs up or purchases the product until they reach a predefined ‘value’ milestone. This milestone varies based on the product and could be anything from completing an onboarding process to achieving a specific outcome using the product.

TTFV is typically measured in days or hours, and the formula is straightforward:

TTFV = Time at First Value Milestone − Time of Purchase

This calculation gives the time taken for a customer to start deriving value from the product.

Consider a business offering a project management tool. Let’s say the first value milestone is defined as the completion of a project setup within the tool. If a customer purchases the tool on the 1st of the month and completes their project setup on the 5th, the TTFV would be:

  • Time of Purchase: 1st of the month
  • Time at First Value Milestone: 5th of the month

TTFV: 5 – 1 = 4 days

A TTFV of 4 days suggests that customers are able to quickly find value in the product, indicating an effective onboarding process and a user-friendly product design. Monitoring and reducing TTFV is essential for businesses. A shorter TTFV typically leads to higher customer satisfaction, quicker adoption, and better retention rates. 

10. Average Resolution Time

Average resolution time (ART) is how long your support team takes to solve an issue. This measure tells you how quickly your team is dealing with issues. A long ART might suggest problems like not enough staff, poor training, or inefficient processes. 

Calculating ART:

To calculate the Average Resolution Time (ART),you first need to know how long it took to resolve each support ticket over a certain period, like a week or a month.

The formula for ART is:

ART=  Number of Tickets Resolved / Total Time to Resolve All Tickets

Let’s say a business’s support team resolved 40 customer issues in one week, using up a total of 80 hours. Their ART would be:

Average Resolution Time = 80 hours / 40 = 2 hours per issue

An ART of 2 hours indicates that the support team is quick to handle and resolve customer problems.

11. Renewal Rate

Renewal rate is the percentage of customers who choose to renew their subscriptions when they come to an end. It shows how many customers continue taking your service after a contract ends. 

Calculating Renewal Rate:

To calculate the renewal rate, count how many customers had the option to renew their subscriptions at the end of their term. Then, see how many of those actually chose to renew.

Here’s the formula for the renewal rate:

Renewal Rate = (Number of Customers Who Renewed / Total Number of Customers Up for Renewal) x 100

This calculation gives you a percentage that shows how many of your customers decided to stick with your service after their initial period ended.

For example, let’s say a business has 300 customers up for subscription renewal at the end of the year. Out of these, 270 decide to renew their subscriptions. The Renewal Rate would work out like this:

Renewal Rate = (270/300) x 100 = 90%

A 90% Renewal Rate shows that the business has strong customer loyalty. 

Recommended read:7 Best Renewal Reminder Templates for Faster Payments

12. Onboarding Success Rate

The Onboarding Success Rate is a vital metric that indicates the effectiveness of the customer onboarding process. It assesses how well new customers are integrated into using the product, which lays the foundation for long-term customer satisfaction and retention.

Calculating Onboarding Success Rate:

This rate is typically measured by tracking the percentage of new customers who successfully complete the onboarding process within a given time frame. ‘Success’ in onboarding can be defined by various criteria, such as completing essential onboarding tasks, reaching certain usage milestones, or achieving initial goals set during the onboarding phase.

The formula for Onboarding Success Rate is:

Onboarding Success Rate = ( Number of Customers Who Successfully Complete Onboarding Process / Total Number of New Customers) × 100

This calculation gives the percentage of new customers who effectively navigate through the onboarding process.

Consider a hypothetical scenario with a company providing online accounting software. If in a month, they onboard 100 new customers, and 85 of these customers complete the entire onboarding process, which includes setting up their account, importing data, and using basic features, the Onboarding Success Rate would be:

  • Number of Customers Who Successfully Complete Onboarding: 85
  • Total Number of New Customers: 100

Onboarding Success Rate =  (85/100) × 100 = 85%

An 85% Onboarding Success Rate indicates that the majority of new customers are finding the onboarding process helpful and are able to start using the product effectively. This is a positive sign for customer engagement and future retention. 

13. Product Adoption Rate

The Product Adoption Rate is another customer success metric, measuring how extensively and effectively customers are using their product. This rate is essential for understanding how well the product meets customer needs and how deeply it has been integrated into their daily operations.

Calculating Product Adoption Rate:

Product Adoption Rate is typically calculated by analyzing user engagement levels with the product. This includes factors like the frequency of usage, the number of active users, feature utilization, and the achievement of key usage milestones that indicate effective product use.

While there’s no one-size-fits-all formula, a common approach to calculating the Product Adoption Rate might be:

Product Adoption Rate = (Number of Active Users / Total Number of Users) × 100

Alternatively, it might involve a more complex calculation considering various engagement metrics.

For instance, let’s consider a business that offers a analytics tool. They may define active users as those who log in and use the tool at least once a week. If they have 1,000 total users and 700 of these users are actively logging in and engaging with the tool on a weekly basis, the Product Adoption Rate would be:

  • Number of Active Users: 700
  • Total Number of Users: 1,000

Product Adoption Rate = (700 / 1000) × 100 = 70%

A 70% Product Adoption Rate indicates a strong level of engagement and suggests that a significant portion of the user base finds the tool valuable. They are actively incorporating the product into their work. 

This metric is invaluable for understanding customer engagement levels and identifying areas for product improvement or additional user training. 

Support Ticket Trends is an analytical metric that shows the patterns and tendencies in customer support requests. This metric helps in understanding common issues, customer pain points, and the effectiveness of the support team.

Calculating Support Ticket Trends:

To analyze Support Ticket Trends, companies track various aspects of customer support interactions over time. This includes factors like the number of tickets raised, categories or types of issues, resolution times, customer satisfaction post-resolution, and recurrent issues.

While there isn’t a specific formula, the analysis often involves categorizing and quantifying tickets based on:

1. Issue type (technical, billing, usability, etc.)
2. Resolution time
3. Outcome (resolved, escalated, pending)
4. Customer feedback post resolution

For example, a business offering a web-based design tool might track support ticket trends over a quarter. They may find that:

  • 40% of tickets are related to technical issues with the tool.
  • 30% are billing inquiries.
  • 20% are feature requests.
  • 10% are miscellaneous queries.

Additionally, they might observe that technical issues take an average of 48 hours to resolve, while billing inquiries are resolved within 24 hours. This analysis can reveal that while their billing support is efficient, there might be a need to improve technical support efficiency or address underlying technical problems in the product.

By analyzing these trends, the company can pinpoint areas for improvement in both customer support and product development. 

15. Revenue Churn

Revenue Churn is another significant metric, tracking the loss of revenue due to subscription cancellations or downgrades. Unlike customer churn, which focuses on the loss of customers, revenue churn highlights the impact of churn on the company’s revenue.

Calculating Revenue Churn:

To calculate Revenue Churn, you need to sum up the total amount of recurring revenue lost from existing customers in a given period, including both cancellations and downgrades. It’s important to exclude revenue from new sales or upgrades during the same period to get an accurate measure of revenue loss.

The formula for Revenue Churn is:

Revenue Churn = (Total Lost Revenue from Cancellations and Downgrades / Total Revenue at the Start of the Period) × 100

This calculation provides the percentage of lost revenue relative to the total revenue at the start of the period.

For instance, a SaaS company starts the month with a recurring revenue of $100,000. During the month, they lose $5,000 in recurring revenue due to customers canceling their subscriptions and another $2,000 due to customers downgrading to cheaper plans. 

The Revenue Churn for the month would be:

  • Total Lost Revenue: $5,000 (cancellations) + $2,000 (downgrades) = $7,000
  • Total Revenue at the Start of the Month: $100,000

Revenue Churn = (7000 / 100000) × 100 = 7%

A 7% Revenue Churn indicates that the company lost 7% of its monthly recurring revenue due to churn. This metric is crucial as it directly impacts the company’s financial health and indicates the need to not only focus on acquiring new customers but also on retaining existing ones.

Recommended read:How to Write Effective Apology Emails to Customers

16. Customer Engagement Score

The Customer Engagement Score is an essential metric assessing how actively and meaningfully customers interact with a product or service. This score reflects the level of customer involvement with the business offering, which is crucial for long-term retention.

Calculating Customer Engagement Score:

Calculating the Customer Engagement Score involves analyzing various aspects of customers’ interaction with the product, such as usage frequency, feature utilization, engagement with support and training resources, and participation in community or feedback forums.

While there’s no standardized formula, a typical approach could involve assigning points to different engagement activities and then summing these up for each customer. For example:

Customer Engagement Score = Points for Usage Frequency + Points for Feature Utilization + Points for Support Engagement + Points for Community Participation

Each activity is weighted based on its importance to overall engagement.

Imagine tracking customer engagement based on:

  • Daily logins (2 points per login)
  • Use of advanced features (5 points per feature)
  • Interaction with customer support (3 points per interaction)
  • Participation in community forums (4 points per post)

If a customer logs in daily, uses two advanced features regularly, contacts support twice and participates in the community forum with two posts in a month, their engagement score would be:

  • Logins: 30 days × 2 points = 60 points
  • Feature Use: 2 features × 5 points = 10 points
  • Support Interactions: 2 interactions × 3 points = 6 points
  • Forum Participation: 2 posts × 4 points = 8 points

Total Customer Engagement Score: 60 + 10 + 6 + 8 = 84 points

A high Customer Engagement Score, like 84 points in this example, suggests that the customer is highly active and finds value in various aspects of the product. Monitoring and improving the Customer Engagement Score is important to ensure that customers are not only using the product but also finding it beneficial and engaging. 

A low Customer Engagement Score helps in identifying areas where customer engagement can be enhanced through better onboarding, feature improvements, or more effective community management.

17. First Contact Resolution Rate (FCR)

First Contact Resolution Rate (FCR) is a key performance metric in customer service. It measures the percentage of customer support inquiries or issues that are resolved on the first interaction without the need for follow-up or escalation. High FCR rates are indicative of efficient and effective customer support.

Calculating FCR:

FCR is calculated by dividing the number of customer issues resolved on the first contact by the total number of issues raised. This metric is usually tracked over a specific time period, like a month or a quarter.

The formula for First Contact Resolution Rate is:

First Contact Resolution Rate = (Number of Issues Resolved on First Contact / Total Number of Issues) × 100

This calculation gives the percentage of issues resolved without any follow-up.

For instance, let’s consider a SaaS company that provides an analysis tool. If, over a month, they receive 200 customer support tickets and successfully resolve 150 of these on the first interaction, their FCR would be:

  • Number of Issues Resolved on First Contact: 150
  • Total Number of Issues: 200

First Contact Resolution Rate: (150 / 200) × 100 = 75%

A 75% FCR rate suggests that the majority of customer issues are being effectively handled in the initial interaction. This is a positive indicator of the support team’s efficiency and the clarity of information provided by the company. 

A high FCR rate leads to increased customer satisfaction and loyalty, as issues are resolved quickly and effectively. It also indicates good product knowledge and preparedness of the support team. 

Recommended read:5 Commonly Misinterpreted Customer Service Metrics

Frequently Asked Questions on Customer Success Metrics

1. What are customer success metrics?

Customer success metrics are measures that tell you how well your business is serving your customers. These metrics give you insights into how customers use your product or service, their level of engagement, the quality of support they receive, and their overall satisfaction levels.

2. Why is it important to track customer success metrics?

Tracking customer success metrics is important to understand customer needs and expectations. They help you identify areas of improvement, proactively reduce churn, and predict future revenue.

Recommended read:Why Customer Success is a Crucial Function of Your SaaS Startup

3. What is the most important metric for customer success?

This varies from business to business. It is heavily dependent on the business model, the industry, and business goals. There’s no one-size-fits-all approach here.

The Bottom Line

For SaaS businesses, understanding and using these key customer success metrics is vital. These metrics guide businesses in making choices that improve customer experiences. This, in turn, leads to improving customer loyalty and helping SaaS companies grow and remain strong.

If you are looking to optimize customer success, tools like Hiver can help. Hiver is a Gmail-based customer support help desk that offers businesses the ability to track and analyze critical metrics seamlessly. 

For instance, Hiver can help you survey your customers and find out how satisfied they are with your company. Based on this data, the tool provides further insights into what’s working and what’s not. 
You can try it out for yourself here.

A B2B marketer, Madhuporna is passionate about breaking down complex concepts into easy-to-digest nuggets with a stroke of her pen (read keyboard). Her expertise lies in crafting research-driven content around customer service, customer experience, IT and HR. When off the clock, you'll find her binge-watching suspense thrillers or basking in nature.

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