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Customer Success Metrics: The Definitive Guide [2022]

We explain all the Customer Success Metrics and tell you how to identify the most valuable ones.
Patrick Icasas
March 30, 2022

I. What are Customer Success Metrics?

A Customer Success Metric is a quantifiable measure that tracks and assesses the success of the CS team, and is therefore an indicator of the customer’s success as they adopt and use the product. These metrics are most often used by SaaS or technology companies, although other industries also use some of the same metrics and terminology. 

II. Why are Customer Success Metrics important?

Not all businesses are in a position to be able to gather and analyze CS metrics. In fact, some aren’t even aware that it’s important. But let’s not mince words:

Your business will FAIL if you don’t track customer success metrics.

Is this an exaggeration? Not in the slightest. 

But if that declarative statement (in bold text, too!) isn’t enough to convince you, here are some well-crafted arguments that will help swing your opinion. 

CS metrics keep your business on track

If you’re flying an airplane, you will want to know important information like your altitude, heading, and fuel status. You will want to know what the weather is like up ahead, and the amount of air traffic at your destination. All of this is information vital to your journey and the well-being of everyone on board. 

Metrics are the same way. Monitoring the right metrics can help keep your business on track and ensure that your churn isn’t outpacing your growth, that your customers are happy with your product, and that you can get an idea of where your business is headed. 

CS metrics help improve your product

By tracking who uses your product, how they use it, and how they feel about it, you’ll be able to isolate areas of improvement for your engineering team. Following user behavior and feedback can often result in better UI and UX insights than from internal QA and testing.

Metrics act as a warning sign

Ever heard the expression, “the squeaky wheel gets the grease?” In Customer Success, by the time the wheel squeaks, it’s already basically fallen off. Your customer will have already made the decision to leave you, and is probably already shopping around for a new product. 

You can see the churn coming, if you just know how to read the signs. With proper metrics, you’ll have ample warning, and be able to intervene before things get too bad. 

Measuring metrics can help bring customers more value

Carefully tracking customer sentiment can help you steer product development away from pain points and towards value-added features. As a result, customers will be able to get more out of your product, which increases their satisfaction and loyalty. 

III. The difference between metrics and KPIs

Metrics and Key Performance Indicators (KPIs) are often used interchangeably, but in reality the two are quite different. Although both are based on data, each one’s unique purpose makes them quite distinct from each other. 

A metric is a quantifiable measure that tracks and provides data on standard business practices. In a Customer Success environment, these metrics are used to track customer-related data points such as churn, customer feedback, and renewal rates. 

A key performance indicator (KPI) is also a metric, in that it tracks and provides data, but is also tied to a specific and quantifiable goal. KPIs are a valuable tool for improving your team’s performance, but that’s outside the scope of this conversation so we’ll save it for another post. 

Basically, all KPIs are metrics, but not all metrics are KPIs. 

IV. How do you measure Customer Success?

There are different ways by which metrics that determine Customer Success can be captured, collected, or calculated.

In-app behavior tracking is useful for both your Customer Success and your Engineering teams. They’ll be able to watch what users do in a live environment and collect statistics that can indicate the “stickiness” of certain features, and how friendly the UI is. 

CRM platforms like Salesforce are going to be your primary source of data when building out your CS metrics. This is where most of your customers’ account information is going to be kept and most CRM platforms are capable of assembling basic reports - or at the very least, exporting data. 

Customer Success Platforms (CSPs) like Catalyst are effective for both gathering and analyzing data. CSMs can input new customer data as conversations happen, ensuring up-to-the-minute information. These CSPs are often integrated with CRM databases like Salesforce, but are also capable of generating their own value-rich reports through flexible dashboards.

NPS Surveys are quick-and-dirty temperature checks to tell how your company is performing. Just be aware that it’s a rolling measure from the past 30 days, so it is a measure of how you’re doing right now as opposed to an overall sense of your customer’s sentiments.

Feedback forms are an excellent way to measure sentiment and customer engagement in-depth. You can turn ratings into graphs to get a large-scale picture of customer satisfaction, while using the write-in answers to drill down into specific use cases or themes.

Your CSMs are an oft-overlooked source of qualitative customer insights. Your Customer Success team speaks to customers every single day and will be a gold mine. You only need to document the hard-won info in a manner conducive to building effective reports.

V. Examples of Customer Success Metrics (and how to calculate them)

Customer Success Metrics

1. Customer Churn Rate

Customer churn rate formula
Customer Churn Rate Formula

Formula: Customer Churn Rate = (# of Departing Customers in a year / # of Total Users in a Year) x 100%

What is it: Customer churn rate refers to the percentage of customers that leave you in a certain period of time. 

This can be measured in either the number of accounts or number of users. It’s an important distinction, because an account that has 100 users will have far more of an impact on your bottom line than an account with 10. 

Churn rates can be measured on a monthly or annual basis. 

Why it’s important: Churn rate is arguably the most important customer success metric that you need to track. Your churn rate signals whether or not customers are happy with your product, and the effectiveness of your Customer Success program. 

Best practices: The annual churn rate of a typical SaaS company is 5%, but negative churn should be the ideal target for everyone. 

2. Revenue Churn Rate

Revenue Churn Rate Formula
Revenue Churn Rate Formula

Formula: Revenue Churn Rate = ($ Value of Churning Users in a year / $ Value of Total Annual Revenue) x 100%

What is it: Revenue Churn Rate is a churn rate variation that tracks dollar value instead of number of users or customers. 

Why it’s important: Revenue churn rate is a valuable metric for tracking how much revenue you’ve lost in a given period of time. 

Best practices: Revenue churn can be segmented by pricing plan or tier so that you can find out which tiers of users are contributing most to your churn. 

3. Net Promoter Score

Net Promoter Score formula
Net Promoter Score Formula

Formula: NPS = % of Promoters - % of Detractors

What is it: Net Promoter Score (NPS) is a metric that helps measure how likely your customers are to recommend your product or service to others. 

Customers are given a one-question survey that asks, “how likely are you to recommend us to a friend or colleague?” And are placed into one of three buckets based on their response: Promoter, Passive, and Detractor. 

These responses are tallied and then used to generate a result between 100 to -100. 

Why it’s important: The NPS used to gauge overall customer satisfaction and is a strong indicator of brand loyalty. This simple survey tends to have much higher engagement than other customer feedback surveys. 

Best practices: According to Bain & Company, the creators of NPS, any result above 0 is considered okay, above 20 is considered favorable, above 50 is excellent, and a score above 80 is considered “world-class.”

4. Customer onboarding costs

Customer onboarding costs formula
Customer Onboarding Costs Formula

Formula: Customer Onboarding Costs = # of Training / Implementation Hours Spent x Hourly Rate of CSM

What is it: Customer Onboarding Costs (COC) tracks the dollar value of getting your customer set up and trained in your product. 

Why it’s important: Lengthy or inefficient onboarding processes can end up costing you more in terms of time and manpower than the account is worth. It also affects the efficiency of your Customer Success operations. 

Best practices: For better visibility, you can also segment COC by stage of onboarding (whether training or implementation) or training type (group vs one-on-one). You can also factor in technology costs such as Learning Management Systems.

5. Customer Effort Score

Formula: Since most of the data will be generated by surveys, there is no fixed formula for determining CES. 

What is it: The Customer Effort Score (CES) is a metric that describes how much effort it takes for a customer to get an issue resolved. This information is usually collected via survey with a range of responses based on their overall satisfaction. 

Why it’s important: In a study, the CEB discovered that the amount of effort it takes to get a problem resolved is a stronger indicator of customer loyalty than customer delight. 

Best practices: Make sure your survey has a healthy mix of quantitative (rating) and qualitative (write-in) responses. If possible, also try to send this survey to customers that have already churned, since they are the ones who are most likely to tell you how much effort is too much. 

6. Customer Health Score

Formula: Customer Health Score is one of the most difficult scores for a business to calculate, simply because there is no universal measure for “customer health.” 

What is it: Customer Health Score (CHS) is a metric that determines how much a customer is invested into your product and whether or not they are actively using it. 

Why it’s important:  CHS is one of the most important metrics in Customer Success because it serves as an early-warning indicator of whether an account will churn or renew. 

Best practices: Each business has their own standard for what constitutes a “healthy” account, and a number of factors that could potentially affect the score, like:

  • Number of active users
  • Goal-oriented objectives
  • Feature adoption
  • Depth of usage
  • Contract duration
  • Renewal cycles
  • User sentiment
  • And more

For best results, you should make the effort and develop your own unique Customer Health Score based on the key performance indicators of your most successful clients and work backwards from there to develop a baseline definition of “healthy.”

That said, many Customer Success Platforms come with their own versions of a Customer Health Score that could potentially be useful to client companies that are satisfied with a generic CHS formula. 

Catalyst employs a flexible Weighted Health Score that allows CS leaders to leverage nearly any metric they want, from Time in App to MAU to Number of Integrations - whatever you need to measure your customers’ health (and nobody else’s). 

7. Qualitative Customer Feedback

Formula: No formulas for qualitative feedback. You could categorize comments as positive or negative when building a report, however. 

What is it: Qualitative Customer Feedback is non-numerical customer feedback that is collected through a variety of sources like social media, survey forms, or conversations with Customer Success or Sales. 

Why it’s important: Qualitative feedback is important for establishing the context of why a customer likes or dislikes your product. You want to know the reason a customer gave you an NPS score of 4, so that you know what you need to fix. 

Best practices: Measure and record qualitative feedback whenever possible. This can come from a written follow up question on an NPS survey or verbally during a customer check-in call. All qualitative feedback should be tracked and recorded in your CSP for future reference. 

8. Trial-to-paid Conversion Rate

Trial to paid conversion rate formula
Trial-to-paid Conversion Rate Formula

Formula: Trial-to-paid Conversion Rate = (# of Trial Customers that convert to paid / # of Total Trial Customers) x 100%

What is it: Trial-to-paid Conversion Rate measures how many of your trial users successfully convert to paid users. This can be measured monthly, quarterly, or annually.

Why it’s important: TTP Conversation Rate helps establish whether or not your trial period motions are effective. Low TTP Conversion Rates signal for you to review them more closely. Do you need more in-app walkthroughs? Are your sales people assisting them through the trial?

Best practices: You can segment this metric by subscription tier, so that you can see which tier is the most attractive to trial users. Be aware that this metric is only relevant to a specific subset of companies that offer trials to potential users. 

9. First Contact Resolution Rate

First-contact Resolution Rate Formula
First-contact Resolution Rate Formula

Formula: FCR Rate = (# of Resolved First-contact Calls / # of Total First-contact Calls) x 100%

What is it: First Contact Resolution Rate measures the number of customer contacts or requests that are successfully resolved after the first interaction with the customer. 

Why it’s important: While FCR Rate traditionally is applied to Customer Support functions, it still has value in Customer Success because it helps measure the effectiveness of your success team and/or CS training. 

Best practices: Global standard for first-contact resolution rates are in the range of 70-75%. Keep in mind though that this number also includes call centers for a variety of industries, not just in tech. 

10. Customer Satisfaction Score (CSAT)

Formula: CSATs are mostly customer surveys, and as such don’t have a formula per se. 

What is it: The Customer Satisfaction Score (CSAT) indicates the effectiveness of your Customer Support and Customer Success teams, as well as the quality of your product or service. 

Why it’s important: While CSAT is more of a general customer care metric, it can also be used to gauge how a customer perceives any interaction with one of your team. This is useful for diving deep into the performance of a specific CSM or the attitude of a specific account.

Best practices: Always make your rating scales consistent between surveys. That way, you can create average CSAT scores based on specific segments such as type of interaction, overall account, or CSM in charge. We’ve got a sample CSAT form for you to see here

Also try to avoid leading or loaded questions, and instead try to use smart questions that will help you fill your end goals.

Let’s take this question as an example:

“Our company is consistently rated 5-stars for our customer service. How good has your experience with us been so far?”

That’s a very biased question with an implied “correct” answer. A much better version would be:

“How satisfied have you been with our service so far?”

It’s simpler, clearer, and more likely to receive an honest answer. 

Product / Business performance metrics


Monthly Revenue Retention and Annual Revenue Retention Formulas
MRR/ARR Formulas

Formula: MRR = Average Recurring Revenue per Customer (monthly) * Total Number of Customers

ARR = MRR x 12

What is it: MRR stands for Monthly Recurring Revenue, while ARR stands for Annual Recurring Revenue. The two figures are a measure of how much money you’re earning from active subscriptions or renewals for a given period of time. 

Why it’s important: These are the measures by which many businesses judge success. It monitors the performance of the entire company and as such plays a part in many important CS performance calculations and reports. 

Best practices: It’s important to note that MRR/ARR are just snapshots of that particular moment in time. Recurring revenue changes constantly based on churn, new sales, and account expansion and contraction. It’s a good idea to always stay up to date with what your current MRR/ARR numbers are. 

12. Net Revenue Retention (NRR)

Net Revenue Retention Formula
Net Revenue Retention Formula

Formula: NRR = (($Value of MRR + $ Value of ER) - ($ Value of CR + $ Value of Churned Accounts) / $ Value of MRR ) x 100%

What is it: Net Revenue Retention (NRR) is the percentage of recurring revenue that’s collected from existing customers. It measures how good the company is at sustaining its customer base and growing those accounts.

Why it’s important: NRR is one of THE most important metrics for a SaaS organization. Companies use it to assess business health and predict the likely rate of growth. 

Best practices: The ideal Net Retention Rate would be anywhere above 90%, because that would mean the business is able to consistently retain or grow most of its customer base. World-class companies are able to achieve NRR rates of 130% and up. 

13. ARPA

Average Revenue Per Account (ARPA) Formula
Average Revenue Per Account (ARPA) Formula

Formula: ARPA = Total MRR / # of Accounts

What is it: Average Revenue Per Account (ARPA) is a profitability metric that tracks how much revenue a company makes per account. It’s also sometimes referred to as Average Revenue Per Customer (ARPC). 

Why it’s important: ARPA is a useful way to determine your average deal size, which could potentially impact both your pricing and your sales offerings. 

Best practices: Track ARPA across multiple months and display the changes in a trend line, so you can see how it is evolving over time, and whether it’s getting closer or further away from your goals. 

14. ARPU

Average Revenue Per User (ARPU) Formula
Average Revenue Per User (ARPU) Formula

Formula: ARPU = Total MRR / # of Users

What is it: Average Revenue Per User (ARPU) is essentially the same as ARPA, except it divides revenue by individual users instead of overall accounts.

Why it’s important: ARPU is valuable for SaaS companies that charge based on licenses or seats, because different accounts may have different numbers of users, thus making ARPA misleading. 

Best practices: ARPU can be used to help identify ideal price points per user, as well as catch any upselling trends. Use ARPU trendlines to map out the differences between user cohorts and segments. 

15. Expansion revenue

What is it: Expansion revenue is the amount of income generated through upsells or cross-sells.

Why it’s important: A company whose expansion revenue is high enough can actually compensate for lost revenue and achieve negative churn. 

Best practices: Expansion revenue can be considered a signal of customer satisfaction and growth. If possible, segment the expansion revenue in your CRM by things like industry, subscription tier and account size. This will help you discover which segment of your customers are getting the most value out of your solution. 

16. Contractions or Downgrades

What is it: Revenue Contraction tracks the amount of income lost when paying customers decide to downgrade to a lower subscription plan or reduce their number of users. 

Why it’s important: Revenue contraction is essentially a subset of churn, and is important to track for the same reasons. It’s a warning sign that things may not be going well for certain accounts, and may require action or follow-up on your part. 

Best practices: As with Expansion revenue, Contraction revenue metrics are most useful when put into trend lines and segmented, so that you can clearly understand partial churn by industry, subscription tier, or company size. 

17. Revenue Renewal Rate

Revenue Renewal Rate Formula
Revenue Renewal Rate Formula

Formula: Revenue Renewal Rate = ( Annual Renewable Revenue / ARR ) x 100%

Remember to substitute ARR for MRR if you are calculating monthly revenue.

What is it: Revenue Renewal Rate (RRR) is a metric that tracks how much of a company’s monthly or annual income is derived specifically from renewals. Unlike NRR, it does not include churn in these calculations, nor does it include expansion or contraction revenue like MRR/ARR does. 

Why it’s important: Revenue Renewal Rates are indicators of how loyal your customers are, and whether or not they’re finding value in your product. 

Best practices: The ideal Revenue Renewal Rate is above 80% according to the CFI, and businesses need to bring it as close to 100% as possible.  

18. Customer Renewal Rate

Customer Renewal Rate Formula
Customer Renewal Rate Formula

Formula: Customer Renewal Rate = ( # of Renewing Customers in a period / # of Canceling Customers in a period ) x 100%

What is it: The Customer Renewal Rate (CRR) is a figure similar to Revenue Renewal Rate, except this time focusing on customers instead of the revenue they generate. This metric does not take into account upsells or cross-sells. 

Why it’s important: It’s an easy and straightforward method of measuring renewals that serve as a temperature gauge for your business. 

Best practices: Anything above 100% means that your company is able to keep more customers than it loses, although that by itself is not a true indicator of churn, as each account may have different numbers of users or may be worth a different dollar value. 

VI. Product usage performance metrics

19. Active Users (DAU and MAU)

What is it: Daily and Monthly Active Users show how many people in a customer’s account are using your product.

Why it’s important: DAU and MAU indicate engagement and activation. The more active  the number of users in an account are, the more likely they are to stay. The more users are dormant, the higher the risk of churn.

Best practices: You first have to decide what constitutes an “Active” account. Do they simply need to log in, or do they actually have to click through a few screens? What if the user just logs in and never logs out?

Also, always keep the total size of the account in mind. An account with a lot of licenses but low MAU may mean multiple things. For example, it may mean that the core team is using your product but the other licenses are for employees who don’t need to be in the system day-to-day. Or it may actually mean that the customer is a churn risk. Either way, it’s a sign that you need to investigate.

20. Product Stickiness

Product Stickiness Formula
Product Stickiness Formula

Formula: Product Stickiness = (DAU / MAU) x 100%

What is it: Product stickiness is a ratio of daily to monthly users. 

Why it’s important: While DAU and MAU tell you the quantity of your user base in a given account, Product Stickiness tells you the quality. For example, if you had an MAU of 100 but a product stickiness of 25%, that means only a fourth of the people who logged in that month stuck around. 

Best practices: Use product stickiness to first assess the natural cadence of your users. You’re setting a baseline of behavior. Then you can continue to monitor product stickiness for your account over time and investigate any time you see significant change. 

21. Avg. number of sessions per user

Average number of Sessions per User Formula
Average number of Sessions per User Formula

Formula: Avg SPU = Total # of Sessions per month / MAU

This figure can be adjusted to use sessions per day and DAU.

What is it: This metric calculates how engaged an account’s user base is by tracking the average number of sessions a user takes in a given period of time, whether it’s daily, weekly, or monthly. 

Why it’s important: Calculating the average number of sessions per user is very useful for assessing product adoption and user activation. It can also be useful in ROI and time-to-value predictions. 

Best practices: If the data allows, try segmenting users by department or function to see if there are any differences in their Average SPU. It may help you identify which features are popular with which groups of users and why. 

22. Avg. session duration

Average Session Duration Formula
Average Session Duration Formula

Formula: Avg. Session Duration: Total Session Length (monthly) / # of users

What is it: This metric measures the length of time that users spend in your product every time they log in. 

Why it’s important: Session length is important to measure both how sticky your product is and how easy to use, depending on the context. 

Best practices: Session length by itself doesn’t mean much. A long session duration might mean that all users are using your system full-time, which is good, or it might mean that people are stuck and can’t figure it out, which is bad. Establish a baseline session duration for your product and that particular account so you know what is “ideal.”

You can also compare the session durations between churned and retained customers. By doing so you’ll be able to get insights into what product or onboarding improvements you can make to increase user engagement. 

23. Avg. Key Actions Per User Session

Key Actions per User Session Formula
Key Actions per User Session Formula

Formula: Key Actions Per User Session = Total # of Activations per session / # of users

What is it: Every software has certain key actions a user must perform in order to get the most value of a product. In Project Management Software this might be creating and closing tasks. In accounting software it might be invoices created. Key Actions Per User Session counts how many of those actions a user performs every time they log in to the system.

Why it’s important: This metric is key for tracking user engagement and product activation, and helps both the customer success and product teams.

Best practices: Look at the difference between the number of key actions that a churned customer takes versus the number of actions a healthy customer takes. 

Also, don’t forget to establish a baseline of “ideal” user actions a particular account should be taking and watch for any deviations. 

24. Time spent in product

What is it: This is another metric that tracks how much people use your product, but unlike previous metrics is not limited by session length. Rather, this is the total amount of hours a user or account has spent in your software over a given period. 

Why it’s important: Monitoring user behavior is important for product and customer success teams, because they will be able to gauge how effective the tool is at engaging users and assisting them in their tasks.

Best practices: Context is everything with this metric. Do you want people to spend a lot of time in your product? Or is it a sign that things aren’t going very smoothly? Monitor user behavior and compare it to your goals for the implementation.

25. Onboarding engagement

Onboarding Engagement Formula
Onboarding Engagement Formula

Formula: Onboarding Engagement = (# of Users that complete onboarding / # of Users that start onboarding) x 100%

What is it: Onboarding engagement tracks which percentage of users that start your onboarding program actually complete it. 

Why it’s important: Onboarding is one of the most crucial times in a customer’s lifetime, and directly impacts their likelihood of churning. That makes Onboarding Engagement an important metric for Customer Success and Implementation teams to be measuring.

Best practices: You can also get more granular with this metric and track the number of onboarding goals completed instead of simply finishing the onboarding process. 

26. Product adoption rate

Product Adoption Rate Formula
Product Adoption Rate Formula

Formula: Product Adoption Rate = (New Active Users / Signups) x 100%

Measure Product adoption rate for a set period of time, such as monthly or quarterly, to give active users time to surface.

What is it: Product adoption rate measures how many people adopt your software and become regular users. 

Why it’s important: There’s a big difference between having a license and being an active user. Ideally, most of the people who use your software should actively be using your product day-to-day. If they’re not, it’s a possible sign that they’re eventually going to churn. That makes tracking product adoption rate crucial to the health of your customer account.

Best practices: Depending on the timing of when you measure adoption rate, you will either need to improve your onboarding process (if you measured it at the start of a customer lifecycle) or conduct additional training (if you measured it well into the customer’s contract). 

27. Feature adoption rate

Feature Adoption Rate Formula
Feature Adoption Rate Formula

Formula: Feature Adoption Rate = (Active Users using feature / Total Active Users) x 100%

What is it: Feature adoption rate is similar to product adoption rate, except that it measures people’s engagement with a specific feature or set of features. For this, you will need the ability to track user behavior down to the individual page level. 

Why it’s important: As your product evolves and gets new features added, you want to know whether these new functions are providing value. You also want to know whether your core features are delivering on their promise. 

Best practices: Remember to segment users whenever you feasible. Depending on the product, groups of users in the same account may focus on different areas of the software based on their job title. 

28. User engagement

User Engagement Rate Formula
User Engagement Rate Formula

Formula: User Engagement = (# of Active Users / # of Total Users) x 100%

Set the Active Users value based on the duration of time you want to measure (daily, weekly, monthly). 

What is it: The User Engagement metric measures whether or not a user or account is actively using your software at a particular point in time.

Why it’s important: User engagement is one of the key signals of whether or not a given user or account is able to utilize and get value out of your software. Low engagement could signal a churn risk and require further investigation.

Best practices: The formula below is useful for quick-and-dirty user engagement measurement if your business doesn’t yet have sufficiently defined key actions to use as more detailed engagement metrics. 

For a more detailed look at user behavior, a User Engagement formula based on Key Actions or Session Duration may prove illuminating.

29. Time to Value

Time-to-value Formula
Time-to-value Formula

Formula: Time-to-value = △ between Signup and Value Achieved

What is it: Time-to-value measures the time it takes for a user or account to reach a state where they are able to use the software effectively for its intended purpose. 

Why it’s important: Customers don’t just want to use your product - they want to be able to use it properly. So while they’re willing to work through an onboarding period and understand the concept of warming up to a new tool, they also are running a business and need to get to the point where it starts adding value.

Best practices: Use Time-to-value to optimize your onboarding process. Accelerate it by focusing on quick wins that align with the most important goals of the customer’s business. This will require a tailored approach to onboarding that can only result from close collaboration with the primary stakeholders. 

You should also align with your stakeholders on what it means to “achieve value.” Is it the number of actions taken? A specific state that the system is in? Level of adoption? Completion of onboard training? 

Each definition of value has to be customized per account. 

VII. Making the Customer Success Metrics make sense

Every Customer Success Metric mentioned above can be important, but not all of it should be important. If you tried to track all of the metrics at once at the same time, you would be so flooded with numbers you wouldn’t be able to take meaningful action. 

The truth is, choosing which Customer Success metrics to pay attention to is almost as critical a task as tracking the metrics themselves. 

So how do you choose? What criteria does a success metric need to meet for you to add it to your CSP dashboard?

Customize metrics to your platform and users

Customer Success metrics should always be matched to your product’s capabilities and, more to the point, your users’ expected behavior. For example, it wouldn’t make sense to measure Session Duration or # of Sessions a Day if your users are in the habit of keeping the product open all the time and never logging out. It leads to false assumptions and therefore poor decision-making.

Instead, focus on the metrics that you know will make sense within the context of users’ daily work habits and the way your software is constructed. It’s these data points that will give you the most valuable intelligence and  insight. 

Align metrics with business goals and objectives

Firmly define or review your business goals, then see which metrics can serve as leading indicators and lagging indicators towards those objectives. Then, assuming that the metrics you chose are measurable, define a set of KPIs that your team needs to shoot for. 

Choose metrics that lead to action

The most useful metrics are the ones that serve as drivers of action and are indicators of progress. 

Consider the difference between “# of Users” and “Daily Active Users.” 

The former is a flat number. There’s not much you can do with it short of asking the sales rep to sell more seats. Its only legitimately useful purpose as a metric is to be an element in some other metric’s formula. 

The latter, “Daily Active Users,” inspires action in and of itself. If DAU is low, then it immediately begs the question, “what can we do to increase it?” This is even before you start incorporating it into other metrics. 

Drill down to find real insights

Truly effective strategy doesn’t come from surface-level analysis. 

When you segment and filter your data, it unlocks a whole new world of insights that drive action and could potentially change your strategy. 

Your customer base might look healthy on the surface, for example, but when you dig into either the SMB or Fintech segments, you may find that a large portion of a segment is in very poor health. You didn’t notice because the other, healthier segments are drowning out the sickly segment’s data and hiding it when you look at it from afar. 

VIII. Conclusion

You can’t safely fly a plane without instruments, and that’s exactly what CS metrics are. They help ensure your business is flying high and flying safely, carrying your customers on a journey towards a profitable future. 

Your Customer Success Platform can be an effective instrument panel (and so much more.) It can display all of the CS metrics you prioritize so you can have a firm grasp on the state of your accounts, and with plenty of early warning of danger as you pilot the customer through their journey. It is also much simpler for CSMs to update and maintain than Salesforce, which makes it easier to keep your data healthy and your metrics accurate. 

Want to know how Catalyst can help? Reach out to us and let’s talk more about important CS metrics like weighted health and Net Revenue Retention!

Better relationships. Less churn.

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