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Top 17 Customer Success Metrics & How to Track Them
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Top 17 Customer Success Metrics & How to Track Them

Nov 23, 2023
15 min read
Hiver HQ

Table of contents

Understanding customer success metrics is crucial for any business. They show how well a company meets their customer’s needs. This insight helps improve a brand’s products and services. 

When it comes to SaaS businesses, customer success metrics play a particularly important role. Most SaaS businesses rely on ongoing subscriptions. And these success metrics speak of what keeps their customers happy. 

Because happy customers continue their subscriptions while unhappy customers leave. By tracking these metrics, businesses can quickly adapt to ensure customer satisfaction and drive growth.

This article will cover the top 17 customer success metrics that will help you gauge your business’s health. 

Table of Contents

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)

Customer Satisfaction Score (CSAT) is a direct measure of customer satisfaction after an interaction with the brand or experience with their service or product. It’s a key metric in gauging immediate customer sentiment.

How to Measure:

CSAT is typically measured through a survey with a simple question like “How satisfied were you with your experience with the product/interaction?” The responses are usually on a scale of 1 to 5, or 1 to 10;  where 1 might represent “Very Dissatisfied” and 5 or 10 might represent “Very Satisfied.”

The CSAT score is then calculated using the following formula:

CSAT Score = ( Number of Satisfied Customers / Total Number of Responses ) ×100

Number of satisfied customers = responses with scores of 4 or 9 (“Satisfied”) and 5 or 10 (“Very Satisfied”) 

Consider a company that provides online project management tools. After customer service team completes a support interaction, they send a CSAT survey where they ask their customers to rate their service on a scale of 1 to 5. Out of 100 responses, 80 customers rate their satisfaction as 4 or 5. Then the CSAT score will be:

CSAT Score = (80/100)×100 = 80%

This score reflects the immediate satisfaction level of customers with the support service. A high CSAT score, in this context, suggests customers are generally happy with the assistance, Conversely, a lower score would signal a need for improvement in customer service strategies or support quality.

Get instant CSAT ratings from customers See Hiver Analytics

2. Net Promoter Score (NPS)

Net Promoter Score (NPS) is a metric used to assess long-term customer loyalty and the likelihood that customers will recommend the service or product to others. It’s a strong indicator of customer satisfaction and future business growth.

How to Measure:

NPS is measured by asking customers a single question: “On a scale of 0-10, how likely are you to recommend our product/service to a friend or colleague?”, 0 being least likely and 10 being most likely. 

Based on the ratings, customers are categorized as Promoters (giving a score of 9-10),Passives (giving a score of 7-8),or Detractors (giving a score of 0-6).

Then NPS is calculated by using this formula:

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

This formula gives a score ranging from -100 to 100

Imagine a company conducting an NPS survey. They received around 200 responses – out of which 100 are Promoters, 70 are Passives, and 30 are Detractors. 

Using the NPS formula:

NPS = {(100−30) / 200}×100 = 35

An NPS of 35 suggests a positive inclination among customers to recommend the service to others. The company can further analyze the feedback to improve services and convert Passives and Detractors into Promoters in order to increase the NPS.

However, it’s important to note that NPS benchmarks vary widely across industries, reflecting differing customer expectations and industry standards. So, it’s essential to benchmark this score against industry-specific NPS scores to accurately assess performance.

3. Customer Effort Score (CES)

The Customer Effort Score (CES) is a metric used to evaluate the ease with which customers can get their issues resolved or interact with the support team. It’s a critical customer success metric, focusing on the efficiency and simplicity of the support process from the customer’s perspective.

How to Measure:

CES is usually measured after an interaction or resolution of a customer query. Customers are asked to rate their experience with a question like, “On a scale of 1 to 7, how easy was it for you to contact our support team and get your issue resolved??” where 1 means ‘very difficult’ and 7 means ‘very easy’.

The CES is then calculated by averaging the scores received:

CES = Sum of all CES scores/ Number of respondents

This results in a score that reflects the overall ease of interaction as perceived by the customers.

Consider a scenario involving a company that provides online accounting software. After resolving their customers’ technical issues, the company sends out a CES survey to all of them. If 100 customers respond to the survey with scores as follows: 50 customers rate the interaction as “very easy” (7),30 customers rate it as “easy” (6),and 20 customers rate it as “neutral” (5),the CES would be calculated as:

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

A CES of 6.3 out of 7, in this context, indicates that the majority of customers found it relatively easy to resolve their issues. However, there’s still room for improvement in making interactions more effortless for customers.

The company can use this feedback to streamline its support processes, aiming to enhance the user experience and increase the CES.

4. Churn Rate

Customer churn Rate is a critical customer success metric, indicating the percentage of customers who discontinue their subscriptions or stop using the service within a specific period of time. It’s a vital indicator of customer retention and overall satisfaction. It is a key measure that your customer success team can use to assess the long-term viability of a business.

How to Measure:

Churn Rate is typically calculated over a regular time interval, like monthly, quarterly, or annually. It’s determined by dividing the number of customers who left during the period by the total number of customers at the start of that period.

The formula for Churn Rate is:

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

This formula gives the percentage of customers who have churned.

For example, let’s consider a business that had 1,000 customers at the beginning of the quarter. By the end of the quarter, they found that 50 customers had canceled their subscriptions.

The Churn Rate would be calculated as:

Churn Rate = (50/1000) × 100 = 5%

This information is crucial as it signals the need for the company to analyze why customers are leaving and to implement strategies to improve customer retention rate. 

Recommended Read: 11 Ways To Reduce Customer Churn

5. Customer Lifetime Value (CLV)

Customer Lifetime Value (CLV) is one of the key KPIs in understanding the long-term value of a customer to a business. It estimates the total revenue a business can expect from a single customer account over the course of their relationship with the company. CLV is crucial for making informed decisions about marketing, sales, product development, and customer support.

How to Measure:

To calculate CLV, you need to know the average purchase value, frequency of purchases, and customer lifespan with your company. 

A simplified formula for CLV is:

CLV = Average Purchase Value × Average Purchase Frequency Rate × Average Customer Lifespan

This formula gives a rough estimate of how valuable a customer is to your business over time.

For instance, let’s consider a business specializing in project management software. It has an average subscription fee of $100 per month per customer. If an average customer stays with the company for 3 years (36 months) and purchases additional features worth an average of $20 per month, the CLV would be calculated as:

  • Average Purchase Value: $100 + $20 = $120 per month
  • Average Purchase Frequency Rate: 1 (monthly subscription)
  • Average Customer Lifespan: 36 months

So, the CLV would be:

CLV = $120 × 1 × 36 = $ 4,320

This means, on average, each customer is worth $4,320 to the company over the span of their relationship. Understanding the CLV helps the company determine how much they should invest in retaining customers and acquiring new ones. 

It also aids in strategizing upselling, and cross-selling opportunities to maximize the value of each customer.

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

Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR) are pivotal metrics for businesses, providing a clear view of the predictable, steady income generated on a monthly (MRR) and yearly (ARR) basis.

How to Measure:

  • MRR: Calculated by summing up the monthly subscription revenue from all active customers.
  • ARR: Typically, ARR is MRR multiplied by 12. However, it also accounts for annual subscriptions and any changes in MRR over time.

So, the formulae for calculating MRR and ARR would be:

MRR = Total Monthly Subscription Revenue from All Customers

ARR = MRR x 12

Imagine a business that has:

  • 100 customers on a basic plan at $50 per month.
  • 50 customers on a premium plan at $100 per month.

Then, the MRR would be calculated as:

  • Basic Plan Revenue: 100 customers × $50/month = $5,000
  • Premium Plan Revenue: 50 customers × $100/month = $5,000

Total MRR: $5,000 (Basic) + $5,000 (Premium) = $10,000

The ARR would be:

ARR: $10,000 (MRR) × 12 = $120,000

This MRR of $10,000 and ARR of $120,000 provide the company with a clear understanding of its stable monthly and annual revenue streams. These metrics are crucial for budgeting, forecasting, and planning business growth strategies. 

They also help in assessing the company’s financial health and stability, guiding decisions related to investments, resource allocation, and market expansion.

7. Expansion Revenue

Expansion Revenue is another customer success metric, which tracks the additional revenue generated from existing customers. This includes income from upsells, where customers upgrade to a higher-tier plan, and cross-sells, where customers purchase additional products or features.

How to Measure:

Expansion Revenue is calculated by summing the additional revenue gained from existing customers over a specific period. This can include upgrades, additional subscriptions, and extra services beyond the base subscription.

The formula for calculating Expansion Revenue is:

Expansion Revenue = Revenue from Upsells + Revenue from Cross-sells

This total gives a clear picture of how much additional income is being generated from current customers.

Consider a SaaS business offering a cloud-based CRM system. They have several add-ons and higher-tier plans available. 

In a given month, the company might experience:

  • 20 customers upgrading from a $50/month plan to a $100/month plan, resulting in an extra $1,000 ($50 extra per upgrade).
  • 30 customers purchasing an additional feature costing $20/month, adding $600 to the monthly revenue.

Therefore, the Expansion Revenue for that month would be:

  • Upsell Revenue: 20 customers × $50 extra = $1,000
  • Cross-sell Revenue: 30 customers × $20 = $600

Total Expansion Revenue: $1,000 (Upsells) + $600 (Cross-sells) = $1,600

This $1,600 in Expansion Revenue demonstrates the company’s success in not only retaining customers but also in increasing the value of these customers over time. Tracking this metric helps the company understand the effectiveness of its upselling and cross-selling strategies, guiding future sales and marketing efforts. 

It also indicates higher engagement with the product, as customers are willing to invest more in the services offered.

8. Customer Health Score

The Customer Health Score is a composite metric used by companies to assess the overall health and satisfaction of their customer base. It combines various factors such as customer engagement, product usage, and overall satisfaction to provide a comprehensive view of how well the company is meeting customer needs.

How to Measure:

This score is calculated by analyzing multiple indicators, including product usage data, customer feedback, support ticket frequency, and more. Each factor is assigned a weight based on its importance, and the combined weighted average forms the Customer Health Score.

While there is no standard formula, a typical approach to calculating the Customer Health Score might look like this:

Customer Health Score = Weight1 × Factor1 + Weight2 × Factor2 +…+ Weightn × Factorn

Each factor (such as product usage, NPS, and support interactions) is assigned a weight (Weight_n),reflecting its importance.

For instance, a business providing an email marketing tool might consider the following factors for its Customer Health Score:

  • Product Usage Frequency (weight: 40%)
  • NPS Score (weight: 30%)
  • Support Ticket Frequency (weight: 20%)
  • Account Upgrade Requests (weight: 10%)

If a particular customer has a high product usage frequency, a strong NPS score, few support tickets, and has requested an account upgrade, their individual factors might score high. The weighted sum of these scores would result in a high Customer Health Score.

A high score indicates a healthy, satisfied customer who is likely to continue using the service and potentially upgrade or refer others. Conversely, a low score signals a customer at risk, potentially requiring intervention or additional support to improve their experience.

By regularly monitoring the Customer Health Score, the company can proactively address issues, tailor its offerings, and improve customer satisfaction and retention over time.

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.

How to Measure:
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 is a key performance metric for customer support. It measures the average duration taken to resolve customer issues or inquiries. This metric is crucial for assessing the efficiency and effectiveness of the customer support team in a SaaS company.

How to Measure:

Average Resolution Time is calculated by summing the total time taken to resolve all issues within a given period and then dividing it by the number of issues resolved in that period.

The formula for Average Resolution Time is:

Average Resolution Time = Total Time to Resolve All Issues / Number of Issues Resolved

This time is usually measured in hours or days.

For example, a business specializing in online education tools might track the resolution time of customer support tickets. Let’s say in a week, they resolved 50 issues, and the total time taken to resolve these issues was 100 hours.

Then the Average Resolution Time would be calculated as:

  • Total Time to Resolve All Issues: 100 hours
  • Number of Issues Resolved: 50

Average Resolution Time = 100 hours / 50 = 2 hours per issue

An Average Resolution Time of 2 hours indicates the promptness of the support team in addressing and resolving customer issues. Maintaining a low Average Resolution Time is important, as it directly impacts customer satisfaction and retention. 

A high Average Resolution Time means that there are bottlenecks in the support process and areas where additional training or resources might be needed to improve the efficiency of support agents.

11. Renewal Rate

Renewal Rate is a crucial metric, measuring the percentage of customers who choose to renew their subscriptions after their initial term ends. This rate is a direct indicator of customer satisfaction, product value, and long-term business sustainability.

How to Measure:

To calculate the Renewal Rate, you count the number of customers whose subscriptions are up for renewal in a given period and then determine how many of those actually renew.

The formula for Renewal Rate is:

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

This calculation provides the percentage of customers who continue their subscriptions.

Imagine a business offering a cloud-based project management platform. At the end of a quarter, they have 200 customers whose subscriptions are due for renewal. Out of these, 180 customers renew their subscriptions. The Renewal Rate would be:

  • Number of Customers Who Renew: 180
  • Total Number of Customers Up for Renewal: 200

Renewal Rate = (180/200) x 100 = 90%

A 90% Renewal Rate suggests strong customer loyalty. This indicates that the majority of customers find continued value in the business’s service. High Renewal Rates are often associated with successful customer service, effective user engagement, and a product that meets or exceeds customer expectations. 

On the other hand, a low Renewal Rate would indicate areas needing improvement, such as product features, customer support, or overall user experience.

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.

How to Measure:

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.

How to Measure:

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.

How to Measure:

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.

How to Measure:

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.

How to Measure:

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.

How to Measure:

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

Customer Success Metrics are important for every business. Thus, it’s quite obvious to have questions about these metrics while trying to understand which of these are essential for your business. In this section, we’ll address some of the frequently asked questions about these metrics. 

1. What are customer success metrics?

Customer success metrics are data points used to measure how well a company is serving its customers. These metrics provide insight into how satisfied your customers are, how well they are using your product and more. 

Customer success metrics include various scores like Net Promoter Score (NPS),Customer Satisfaction Score (CSAT),Churn Rate, and more. For instance, NPS measures how likely customers are to recommend a product or service, giving insight into customer loyalty.

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

Tracking customer success metrics is essential for understanding customer needs and expectations. They help businesses identify areas for improvement, gauge customer satisfaction, and predict future growth. 

For example, a high Churn Rate might indicate customer dissatisfaction, signaling the need for product or service improvements. By monitoring these metrics, companies can make data-driven decisions to enhance customer experiences and build stronger relationships.

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

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

The importance of a metric can vary from business to business. It is heavily dependent on the business model and goals, and there’s no one-size-fits-all approach here. However, one widely recognized metric is the Net Promoter Score (NPS). 

It provides a broad measure of customer loyalty and satisfaction by asking customers how likely they are to recommend the product or service to others. A high NPS suggests that customers are happy and likely to bring in more business through referrals.

4. How do you measure customer success?

Measuring customer success involves collecting and analyzing data on various aspects of the customer experience. Surveys are commonly used for metrics like NPS and CSAT, where customers rate their satisfaction. 

Other metrics, like Churn Rate or Customer Lifetime Value (CLV),are calculated using sales and customer data. For instance, CLV is calculated by estimating the total revenue a company expects from a customer over their relationship with the company. Regularly tracking these metrics gives businesses valuable insights into their customer base and service.

The Bottom Line

For SaaS businesses, understanding and using these key customer success metrics is vital. They show how satisfied and engaged their customers are. These metrics guide businesses in making choices that improve customer experiences. This leads to lasting customer loyalty and helps 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 gauge your support team’s response time, resolution rate, and more, providing valuable insights that can shape customer success strategies. And it doesn’t end here. It also simplifies the process of gathering data on customer interactions. 

With Hiver, you can get instant customer feedback with simple surveys that can be inserted into emails with just one click. How cool is that?

Schedule a demo to know more

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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