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16 critical customer success metrics you need to track

To measure the performance of your customer success team, track these essential metrics and KPIs.

Published on Jan 17, 2024 by AirOps Team

While customer support and customer success teams measure many of the same metrics and KPIs, there are some key differences between the two functions. These differences impact the metrics that teams use to measure their performance.

Customer support is generally reactive, with a focus on addressing customer problems and answering questions as they arise. Customer success should be proactive. To ensure your customers are successful, you need to understand their desired business outcomes and how your solution helps them achieve those goals.

While customer support tends to be a standalone entity that a single department in the business owns, customer success takes a more collaborative approach that involves customer support, sales, product, and other teams as needed.

This chart from our friends at OpenView Partners provides a quick summary of the differences:

Customer Success vs. Customer Service

What customer success metrics should my organization and team track?

So, which customer success metrics belong in your metrics framework? It depends on your goals, your organization and industry, the maturity of your customer success function, and more. 

Still, most customer success teams share some common goals, like increasing retention and customer lifetime value (CLV).

With this in mind, we’ve broken the 16 customer success metrics that we’re about to review into three categories:

💰 Revenue metrics

💻 Product metrics

💭 Quality of life metrics

In the explanations below, you’ll get a brief overview of the metric, a calculation where applicable, and notes on important caveats and considerations.

Revenue-related customer success metrics

Ideally, every function within an organization can tie its performance to financial outcomes, and customer success is no exception. The following revenue metrics can help your team demonstrate its value to the organization. 

1. Net Revenue Retention (NRR)

NRR measures the percentage of recurring revenue retained from existing customers over a specific period. It factors in upgrades, downgrades, and Customer Churn to measure growth potential from the company's existing customer base. It provides valuable insights into your current customers' health, longevity, and overall satisfaction. 

While NRR is a critical revenue metric for any business with a recurring revenue model, it’s especially vital to PLG SaaS companies. These businesses tend to have higher churn rates, so they must constantly improve their offerings and keep their customers engaged to retain revenue.

This is the formula for NRR:

Net Revenue Retention = (Starting MRR + Expansion MRR – Churned MRR) ÷ Starting MRR x 100

A few notes on the NRR calculation inputs:

  • MRR = Monthly Recurring Revenue
  • Expansion MRR = Upsells, cross-sells, and price increases
  • Churned MRR = Cancellations, non-renewals, and account downgrades

2. Monthly Recurring Revenue (MRR)

MRR is a common North Star growth metric used by SaaS companies and other businesses with subscription-based revenue models. It tracks the amount of normalized, predictable monthly revenue you can expect from active accounts on subscription-based contracts. 

If customers are paying up over and over again, it’s probably because they find value in your products and/or services.

Here’s how to calculate MRR:

Monthly Recurring Revenue = (Average revenue per account that month) x (Number of active accounts for that month)

A few notes on MRR:

  • Annual Recurring Revenue (ARR) is preferred by some companies, especially those with longer-term subscription models.
  • Since MRR is sensitive to month-over-month changes, early-stage companies often prefer it.
  • There's no hard and fast rule, but B2C SaaS companies generally track MRR, whereas B2B SaaS companies prefer ARR because they have more extended sales contracts and less churn.

3. Expansion Revenue

Expansion Revenue measures how effectively a company grows its revenue from existing customers through cross-sells, upsells, and add-ons.

For example, if a customer you acquire signs up for a $1,000 annual contract, but ultimately ends up spending $1,200, you've generated $200 of Expansion Revenue.

High Expansion Revenue also suggests that your customers are satisfied and find value in your offerings… so much so that they want to spend even more. 

Monthly calculations for Expansion Revenue are known as Expansion MRR, but you can use any period that makes sense for your company, including quarterly or annually. 

This is the calculation using Annual Recurring Revenue as an input:

Expansion Revenue = ARR from cross-sells + ARR from up-sells 

4. Average Revenue Per User (ARPU)

ARPU tracks the average amount of revenue generated by each user of a product. 

It's a key indicator of profitability and growth used by PLG companies to measure the organization's ability to capture revenue from a product’s user base. 

The calculation for ARPU is straightforward:

Average Revenue Per User = Total revenue generated during the specified time period ÷ Number of active users during the same period 

When tracking ARPU as a customer success metric, it’s helpful to segment users based on factors like pricing tiers and usage patterns. This is a solid best practice for any company, but it can be especially helpful for companies with usage-driven pricing models. 

For example, you might find that your most usage-hungry customers have the lowest ARPU. In this instance, you may want to consider restructuring your pricing model.

5. Customer Lifetime Value (CLV)

Customer Lifetime Value (CLV), also sometimes referred to as Lifetime Value and abbreviated as LTV, measures how much revenue a company can expect to earn from a single customer throughout its relationship with the company.

There are a few different ways to calculate your organization's CLV. Here are two of the most common:

Customer Lifetime Value = Annual Recurring Revenue x Average Customer Lifespan (in years)
Customer Lifetime Value = Average Purchase Value x Average Purchase Frequency x Average Customer Lifespan (in years)

When calculating CLV, it’s important to:

  • Segment customers by behavior (e.g., average order value, number of purchases, engagement).
  • Account for Customer Churn; otherwise, you risk overstating your CLV.
  • Include acquisition costs, customer retention costs, and the lifetime value of any customer referrals in your calculation.

Additionally, it’s worth noting that measuring CLV is challenging in a company’s early days – it’s tough to collect meaningful data when you haven’t had customers for very long.

6. Customer Retention Cost

All customers aren’t created equal. Sometimes, maintaining a customer (or cohort of customers) negatively impacts your profitability. When you measure Customer Retention Costs, you can determine whether your customer success initiatives are a cost-effective net positive for the business. 

Here’s how to calculate it:

Customer Retention Cost = (Sum of all customer success expenses ÷ Total # of customers)

Keep the following in mind when calculating your Customer Retention Costs:

  • Include all customer success expenses, including payroll, team training, customer-related marketing, the cost of tools, and everything else that goes into customer success. 
  • You might also want to include customer support expenses in your calculation.
  • As is the case with so many metrics on this list, segmenting customers can provide even more insights. For example, you might discover that certain types of customers are incredibly expensive to retain.
  • If your retention costs are sky-high, look for ways to reduce and/or eliminate expenses. Automating redundant tasks, streamlining inefficient processes, and eliminating processes as needed will help reduce your retention costs.

Product-related customer success metrics

Customer success depends on product success and how effectively the product delivers value to users. Use these product-related metrics to gain a quantifiable understanding of how well your product delivers value.

7. Free Trial Conversion Rate

The goal of any free trial is to convert free users to paid users. This metric measures progress toward that goal and provides valuable insights into your product's value.

This is the calculation:

Free Trial Conversion Rate = Number of free trials that converted to a paid plan in a specified period ÷ Number of all free trial users within that same period

The basic calculation is straightforward; the real value in this metric is found in segmentation. You can (and should) segment your trial audience based on factors like persona, type of plan, company size, and industry. 

8. Customer Churn Rate

Customer Churn Rate measures the percentage of customers who stop using your products or services over a given period. A high Customer Churn Rate means that you're losing customers.

To calculate Customer Churn Rate, divide the total number of churned customers by the total number of customers you had at the beginning of the measured time period. You can use this formula:

Customer Churn Rate = (Lost Customers During Time Period ÷ Total Customers at the Start of Time Period) x 100

Churn Rate is also an example of a metric that customer support and customer success teams both track.

9. Product Usage Rate

Product Usage Rates measure how often your customers use your product over a specific duration. Usage looks different for every company – you need to define what meaningful usage looks like for your customers. 

To calculate Usage, simply add the total number of usage actions completed for a given user or across all users.

There are several considerations to keep in mind when measuring Usage Rates:

  • This metric is best measured several weeks after the customer's onboarding phase since it can take some time for new users to learn the ropes. 
  • You can segment usage by feature, customer cohort, and other factors.
  • Use information gleaned from this metric to influence feature development and customer success initiatives. For example, if you find that specific features go largely unused, determine if there’s an issue with customer education or the feature itself.
  • Your selected product usage metrics may (or may not) correlate with customer satisfaction. To measure satisfaction, look to metrics like Customer Satisfaction Score (CSAT) to get a more complete picture.

10. Average Session Duration

As the name suggests, this metric measures the amount of time your customers spend using your product. It’s calculated by dividing total time spent across sessions by the total number of sessions and is often measured in seconds.

A “good” Average Session Duration will vary between companies. Some products are designed to deliver quick value. Others are meant to be used with more in-depth workflows. Determine what good looks like for your product and benchmark ongoing progress against that baseline.

11. Daily & Monthly Active Users (DAU/MAU)

This metric is extremely important for growth-focused SaaS companies. 

While the concept of DAU and MAU is fairly self-explanatory, there's an important caveat that makes calculating your Active Users a bit tricky: You need to determine the exact criteria that define an active user. 

For example, is an active user someone who logs into the platform for a certain period of time and completes specific tasks?

12. Renewal Rate

Renewal Rates are critically important for SaaS companies with subscription models. If people keep renewing their subscriptions, it suggests they receive value from the product or service.

Low Renewal Rates suggest that customers are having a successful experience with your product. Use this as a sign that it’s time to make investments in customer success, product development, and overall user experience.

Use this formula to calculate your Renewal Rate as a percentage:

Renewal Rate = (# of renewals ÷ # of customers eligible to renew) x 100

13. Customer Health Score

Customer Health Scores are a great way to tie many other customer success metrics together.

When you assign a Health Score to customers, you can predict how likely they are to grow, renew, or churn. From there, prioritizing customers is much easier, so your CS team doesn't spend too much time on customers who are bound to churn anyway.

A Customer Health Score can also help customer success managers and their teams proactively identify customers at risk of churning. 

This metric is unique from one organization to the next – your Customer Health Score is calculated using a combination of data points (you can even use many of the metrics we’ve explained in this article).

The information used to calculate your Customer Health Score should include metrics from these categories:

  • Frequency and duration of use
  • Depth of use (aka the number of features an account uses)
  • Breadth of use (aka the number of users in an account that use the product_
  • Growth in terms of revenue generated, features used, depth of use, breadth of use, and number of referrals made

A "healthy" customer uses your product regularly, accesses every feature they need, and promotes your product to others.

Quality of life customer success metrics

Every customer success program should include “quality of life” customer success metrics.

These metrics are based on first-hand feedback from customers, which gives you deeper insights into how and why they feel the way they do. You can use this information to improve your customer success function, inform new features and updates, and much more.

14. Customer Effort Score (CES)

Can your customers access help when they need it most? How difficult is it for them to get support?

This metric answers those questions.

Customers loathe navigating pre-recorded menu options and transfers from one agent to another (assuming they can even get in touch with someone to help in the first place).

CES surveys are typically sent after the successful resolution of an issue. The survey doesn’t have to be complicated, either. Here’s an example:


15. Net Promoter Score (NPS)

Net Promoter Score (NPS) gauges customer satisfaction and loyalty on a scale from -100 to 100, with the latter indicating higher customer satisfaction. 

The NPS survey asks customers how likely they would recommend a company's product or service on a scale of 1-10. Anyone who responds with a 9 or 10 is considered a promoter, and anyone who responds 0-6 is a detractor.

The formula for calculating NPS is:

Net Promoter Score = % of Promoters - % of Detractors

NPS can be used as a proxy for other metrics like Customer Churn Rate and Lifetime Value. The surveys often include an open-ended question asking customers to explain their score, which can provide invaluable customer feedback and help teams proactively identify issues.

16. Customer Satisfaction Score (CSAT)

Customer Satisfaction Score (CSAT) measures customers' satisfaction with a particular feature, product, or team interaction. 

There are several ways to calculate CSAT, but the most common way is to ask customers to respond on a scale of 1-5 about their experience. The more satisfied your customer is, the higher your CSAT.

Most companies track CSAT in a customer support tool like Zendesk (or another ticketing tool), which streamlines the measurement and monitoring process. You can also use this formula to calculate CSAT:

CSAT = Number of satisfied respondents ÷ Number of total respondents

Keep the following in mind when measuring CSAT:

The best way to measure and monitor your company’s customer success metrics

Most organizations track their customer success metrics using a combination of tools, including platforms like Zendesk, Salesforce, ServiceNow, Intercom, and Gainsight. There might even be some extras included depending on the tech stack in question, like Hubspot, Help Scout, or LiveAgent.

Clearly, there’s no shortage of ways to track your most important metrics and KPIs. All too often, your most valuable data gets stuck in SaaS tools, spreadsheets (that may or may not be up-to-date), fancy dashboards that are more form than function, and other data silos. Getting accurate data insights that can move the business forward can feel downright impossible.

The “too many tools, not enough insights” problem is one that we’re familiar with at AirOps. It’s a problem that can impact every corner of your business, not just customer success.

That's why we've built a product that makes it easier for teams to work with data inside the tools they already use daily, including Notion, Google Sheets, Google Docs, Coda, and other core operating documents.

The result? Less time spent fighting with data and more time using that data to drive action 🙌. Click the banner below to learn more and get started.

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