Defining Customer Success: Key Metrics and KPIs in SaaS

In our previous article, we explored the evolution of Customer Success from its roots in traditional support to its current role as a strategic business function. We will now start to dig deeper to understand how investing time and resources into existing customers is becoming more important for growth than investing mostly in new logo acquisition.

The Importance of Metrics in Customer Success

It is said that Customer Success 1.0 was all about trying to make the users happy in order to (hopefully) reduce churn. Today, Customer Success 2.0 is about deeply (and truly) understanding your customers in order to successfully guide them to measurable and believable value (we’ll talk about the 3.0 in a later article). It’s the customer value that will deliver cross-sell, upsell and retention. Therefore, having a deep understanding of performance metrics and intervention points is the cornerstone of a successful Customer Success function. This fortnight’s article will look at the top KPI’s to measure how well Customer Success is achieving this business critical mission.

Key Customer Success Metrics and KPIs

Let's explore some of the most critical metrics that every Customer Success team should be tracking. There are entire books written on each and every KPI - and even companies built around most of these - so I am going to try to distill it down using my own practical reflections. I’m sure there will be differing views on usage, applicability, effectiveness. Please feel free to reach out to me to discuss and learn from each other!

Gross Revenue Retention (GRR)

GRR is probably one of the most used KPIs in Customer Success. GRR shows how much of your customers’ revenue is being renewed over time. The time period is mostly Yearly or Monthly but sometimes it can be per Half year, Quarter, Week or even per Day.

GRR takes contractions and losses into account, but not any expansions (see NRR) and it is calculated as follows:

GRR% = (Revenue Begin - Churn - Contractions) / Revenue Begin x 100%

Where:

Revenue Begin = Revenue from your customer cohort at the start of the measurement period

Churn = Revenue amount lost from customers from the same cohort that are no longer customers at the end of the measurement period

Contractions = Revenue decrease from for eg fewer users, lower tier or fewer product SKUs (same customer cohort) at the end of the measurement period

What is a good GRR? According to the Harvard Business Review, acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one, so clearly the closer a company gets to 100% the better. But as a benchmark: a 2023 survey of 1500 B2B SaaS companies conducted by SaaS Capital Insights shows a median spread of 90%-93% depending mostly on contract size buckets (which are also correlated to ‘age’ of the company).

Net Revenue Retention (NRR)

If we start with GRR, then the next one in line should be NRR. Where GRR measures revenue decreases (from downgrades or churns), NRR also takes revenue increases from the existing customer cohort into account. For me personally, this KPI is the single most important KPI for a Customer Success 2.0 organization: it starts with retention, but adds in the power of the CS organization for growth. Because of its compounding effect on this growth, NRR has shown to be one of the most important metrics for measuring medium- to long-term business health. Which also translates to (or even predicts) company valuation: McKinsey researched 20 of the most used operational metrics in 200 SaaS companies and found that there are only 4 metrics that have a strong correlation to company valuation. ARR growth and NRR are two of these four! In the case of NRR, it was shown that companies with an NRR >120% delivered an Enterprise Value to Revenue ratio of 21-fold compared to 9-fold below the 120% mark.

NRR is calculated as follows:

NRR% = (Revenue-begin - Churn - Contractions + Expansion) / Revenue-begin x 100%

Where:

Expansion is the new Revenue customers have started spending with you in the measurement period through upsell, cross-sell or other means.

I can’t stress this one enough: NRR is a vital metric for SaaS companies, and through strategic investments in customer retention and success initiatives focusing on NRR, you are influencing both growth potential and company valuation. A high NRR provides a more predictable revenue stream, which is essential for financial planning and forecasting. It allows companies to project future revenues with greater accuracy, making it easier to manage resources and investments.

But what is a Good NRR? SaaS Capital Insight research into 1500 B2B SaaS companies from 2023, shows top quartile companies with NRR>130% and Bottom quartile average of 103%. As mentioned above, a McKinsey study showed that companies with an NRR>120% have more than twice the valuation to revenue multiples than those <120%. Please do note that company age and revenue (ARR) is a correlating factor in these numbers.

Customer Lifetime Value (CLV. Also abbreviated as LTV) and Customer Acquisition Cost (CAC)

CLV is a comprehensive metric for measuring the total value a customer brings to your business over the entire relationship. It takes into account not just the initial sale, but also renewals, upsells, and cross-sells (which we'll explore in more depth in a future article on "The Art of Upselling and Cross-Selling in Customer Success").

By its nature (measuring value over a longer period of time), trend changes will be slow, so measuring and reporting will be less frequent. Then why is this being looked at, if it’s not a KPI to use in the typical quarterly SaaS cycle? Well, in the short-term, understanding what drives long term value helps CS teams prioritize their efforts and resources to focus on customers with the highest potential long-term value (your customer health data will also help assess that). Also, when product or pricing decisions are being made, leadership is increasingly investigating how that decision will influence the lifetime value of a customer. There are different methods to calculating CLV, but the easiest one is simply:

CLV = ARPU x Customer Lifetime

Where:

ARPU = Average yearly Revenue Per User (this average will automatically hold both the original land as well as any increases in ARR over time. The term “User” can also be swapped by “account”)

Customer Lifetime = 1 / Yearly Churn rate (for eg if your GRR is 92%, then your lifetime = 1 / 0,08 = 12,5y)

Where CLV does play a more direct role is in the CLV:CAC ratio (or LTV:CAC ratio). This ratio measures how much value your company gets out of a customer by dividing the Customer Lifetime Value by the Customer Acquisition Cost (CAC).

CLV:CAC ratio = CLV / CAC

If the acquisition cost is higher than the lifetime value, then you are losing money on each customer you acquire and your business will eventually die. If the lifetime value is higher than the acquisition cost, you are earning money with customers. CAC is mostly used, influenced and tracked by Marketing and Sales. Though more and more, not just the cost of acquisition, but also the cost of retention, is being factored into the CAC, which is why CS leadership is increasingly deriving insights from - and influencing - this metric. For your CAC in a specific period, turn to your CFO or Controller or Head of Finance. She or he will be able to give you the P&L numbers for Sales and Marketing cost (salaries, bonuses, tooling, (social) campaigns, advertising, expenses, even relationship gifts and such). Please note that Customer Retention Cost (salaries, bonuses, loyalty programs, support, retention marketing, product improvements to reduce churn and such) is often a separate line item in the P&L outside of the Sales and Marketing cost. Please discuss with your finance colleague.

But what is a good CLV:CAC ratio? In SaaS, it’s generally accepted that a healthy ratio is 3:1 (i.e. over its lifetime, a customer generates 3x the value of its acquisition cost). Anything lower than 3:1 implies your operating model - or even your business model - needs attention (look at improving both the Top line and the Bottom line). There’s also an “upper boundary”: if you are going beyond 5:1, that suggests you are underinvesting in Sales & Marketing which will hurt you in the long term.

Brief sidestep: outside of the cost to value ratio, CAC is also looked at from a recovery period standpoint: how long does it take to earn back the acquisition cost (also referred to as “Last 12 Months (LTM) Median Payback Period”). Also here there are simple and difficult formulas but the simple one does fine as a rule of thumb.

CAC Recovery Period = CAC per User / Average Monthly Revenue per User

Because SaaS has small subscription revenues over a longer period of time, capital becomes scarce and expensive, so a startup should look for CAC recovery periods of <12 months. You’re doing very well if your CAC recovery is <6 months.

Because it is mostly more cost-effective to retain and expand existing customer relationships than to acquire new ones, focusing on a strong NRR will also decrease the CAC, while also increasing average revenue. There are an additional number of tried and tested strategies to sustainably lower CAC but they go beyond the scope of this article, and are mostly employed by the Sales & Marketing departments.

Net Promoter Score (NPS)

NPS measures customer loyalty and satisfaction by asking customers how likely they are to recommend your product or service to others. It's a simple yet powerful indicator of customer sentiment and can be a leading indicator of churn or growth. I’ll skip the calculation mechanics here because it takes up a bit of space and is easily found.

Regular NPS surveys can help CS teams identify at-risk customers early and take proactive measures to address their concerns, a strategy we'll discuss further in our upcoming article on "Reducing Churn: Strategies for Retention and Renewal."

NPS has been researched extensively and is still considered to be a reliable and leading indicator of problems with loyalty. But in practice, there are some typical problems that make it a bit of an oversimplification and it will therefore always be used in conjunction with other KPI’s. Common challenges are: cultural bias affecting the scores and their semantics ; scores are heavily influenced by recency bias ; recency bias introduces the risk of gaming the system. And then there’s a larger one for companies on a Sales or Value Led Growth strategy: that is that WHO is answering the actual NPS survey is extremely important for the reliability of the correlation to loyalty & churn. Tony Ulwick identifies 3 main types of persona’s when it comes to customer segmentation and beneficiaries of value. There are the end users of the product or service, there are the Product lifecycle support teams and there is the purchase decision maker. Practice shows that happiness of only the end users (mostly targeted for NPS surveys), does not correlate well to churn. So when designing an NPS strategy, have some good conversations about who to target for the NPS responses and how much the responses will really tell you.

What is a good NPS? The NPS calculation leads to a score between -100 and 100. An NPS score of zero or above is considered fine. A reliable median is between 20 and 30 while 50 or above is considered to be excellent.

Time to Value (TTV)

TTV measures how quickly new customers start realizing the promised value from your product. This metric is closely tied to the effectiveness of your onboarding process, which we'll explore in detail in our future article on "Onboarding Excellence: Setting the Foundation for Long-Term Success."

There’s not a generic formula to measure TTV because Value is defined 100% by your own value proposition. First you need to have a thorough understanding of, and measurement for your value proposition. Then you need to understand when the “aha moment” happens (i.e value is being perceived). That’s your TTV.

But what is a good TTV? A short TTV will mostly lead to higher customer satisfaction, increased product adoption, and better retention rates. What is short and what is long? That depends heavily on your product and product complexity. Self-serve SaaS products delivered through a PLG strategy have ranges from a few weeks down to just a few days. Enterprise SaaS products will have longer TTV: 2-3 months is still common and strong, obviously heavily influenced by factors such as implementation process, customization & configuration, integration requirements, training & education.

Please note that TTV is still a difficult one because many SaaS companies aren’t yet great at delivering measurable and perceivable (or even believable) business outcomes. A compelling, clear, customer-centric and quantifiable value proposition is where you need to start.

Customer Health Score

A customer health score is a composite metric that takes into account many factors such as Usage and Engagement metrics, Customer Satisfaction metrics, Contract and Renewal data, Risk Factors, Financial metrics and even Organization or Customer specific factors. The goal of a health score is to provide a holistic view of the customer's likelihood to churn or expand. This score allows CS teams to strategize on their customer portfolio and prioritize their efforts, focusing on at-risk customers or those with high growth potential. Health Scores should go down to the individual customer level, but should also consolidate to portfolio, geo, segment etc levels to assess health as an aggregate. We'll discuss how to leverage this score in our upcoming article on "Proactive Engagement: Strategies for Anticipating and Addressing Customer Needs."

Customer Health Score is also a very non-standard KPI (I’ve been in many and long discussions about “what IS health actually? What do we want it to measure”). It’s one of the most complex to get to a usable state (so not only a score, but a score that you can use to drive your customer portfolio management from). It requires a ton of data (also going back a long way) and a data team to build, test, rebuild, retest hypotheses across cohorts or other factors that might play into a health score. Descriptive statistics, correlation analysis, regression analysis, survival analysis, hypothesis testing are all widely used statistical tests. As health scores gain more predictive power through Machine Learning and AI, we will see jumps in NRR, but also new opportunities for digital CS, further reducing CAC and improving growth. Watch this space!

Others

Product telemetry is a core source for strong usage and adoption data: daily/monthly active users, session duration, feature usage frequency, feature usage duration, feature adoption metrics, feature retention rates, navigation paths, abandonment rates for workflows etc etc. Telemetry is getting better over time - many products did not have this built in from the start - and this is generating terrific insights about where the product might have gaps, which parts are most sticky, etc.

There are still a multitude of “popular” KPI’s such as customer churn (as opposed to $-value), expansion (as a standalone metric instead of part of NRR), CSAT (mostly used in Professional Services and Support engagements) and many others. This article wanted to capture the most used, but also the strongest KPI’s in my personal professional opinion.

Aligning Metrics with Business Objectives

While these metrics each provide valuable insights, it's crucial to remember that they should align with your overall business objectives. The specific metrics you prioritize may vary depending on your company's stage, target market, and growth strategy.

For instance, a startup focused on rapid growth might prioritize NRR and new customer acquisition, while a more established company might focus more on reducing churn and increasing CLV.

The Future of Customer Success Metrics

As we'll explore in our final article, "The Future of Customer Success: AI, Automation, and Evolving Customer Expectations," the landscape of CS metrics is evolving. With advancements in AI and machine learning, we're moving towards more predictive metrics that can forecast customer behavior and needs before they even arise.

In conclusion, defining and tracking the right metrics is fundamental to the success of any Customer Success initiative. By focusing on these key metrics and KPIs, CS teams can demonstrate their value, drive strategic decisions, and ultimately contribute to the sustainable growth of SaaS businesses.

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This article is the second in a series I am writing to dive deeper into the world of Customer Success in SaaS. I will be posting a new article roughly every 2 weeks. With every article I will include a visual that will come from an AI image generator, something that I am experimenting with (and not at all good at). This article's visual has been Designed by Freepik, https://www.freepik.com