Product-led growth metrics

The right metrics can give your teams a common language and goal to rally behind.
Product‑led foundations
Product‑led Growth cOLLECTIVE


“Alignment” can feel like a bit of a buzzword—everyone in SaaS preaches it, but few really define what it looks like in practice.

And yet alignment across teams is both a requirement and a benefit of product-led growth. To help demystify what we, the Product-Led Growth Collective, mean when we talk about alignment, let’s take a closer look at one of the more tangible ways that teams can become aligned: metrics.

Metrics provide a common language and reporting system that cross-functional teams can rally around. The right set of metrics can act as a north star that helps all departments navigate toward the same goal. Metrics should not be siloed—they should be reported on and affected by cross-functional teams who can leverage the data to make more informed decisions and enact coordinated changes across your business.

Of course, the exact metrics and benchmarks will vary from company to company. But with the old “there’s no one-size-fits-all” caveat aside, here some of the most important SaaS metrics for measuring and monitoring product-led growth.   

The Product-Led Growth Flywheel

Before we go any further, we should ask: Is your company still talking about funnels? Or have you embraced the flywheel model?

Hate to tell you, but if you’re still looking at your customer journey as a linear chute from awareness to revenue, your company is going to struggle to achieve product-led growth—a LOT.

That’s because adopting a flywheel model—or at least embracing the principles behind it—is critical to fully realizing the potential of product-led growth.

The Product-Led Growth Flywheel is a framework for growing your business by investing in a product-led user experience. In this framework, the experience is designed to generate higher user satisfaction and increased advocacy, which in turn drives compounding growth of new user acquisition.

The Product-Led Growth Flywheel depicts 4 sequential user segments that correlate with stages in the user journey—evaluator, beginner, regular, and champion—and the key actions that users need to take to move on to the next stage—activate, adopt, adore, and advocate. The goal is to focus company- and team-level strategy on optimizing the user experience to move users from one stage to the next—as more users become advocates, they drive more acquisition and growth increases exponentially.

Take a look:

This is an image of the Product-Led Growth flywheel framework whtat shows 2 circles depicting the user journey and the actions needed to move users from one stage to the next and fuel growth. On the inner circle are 4 user segments: evaluators, beginners, regulars, and champions. On the outer ring are 4 steps: activate, adopt, adore, and advocate.

The Product-Led Growth Flywheel is meant to align your teams around the user experience as the primary driver of business growth. An understanding of how it works and why it matters is essential to successfully becoming product-led. As such, the PLG metrics below should be thought about and implemented through the lens of the flywheel model—not a siloed funnel that spits customers out at the end.

Got it? Great! Let’s continue...

Revisiting the pirate metrics framework

You’re probably familiar with the pirate metrics (or AARRR metrics), the 5-step framework for SaaS growth initially outlined by David McClure way, way back in 2007. Part of what makes this framework so powerful is that it encourages people to look beyond vanity metrics, as Archana Madhavam, PMM at Amplitude, explains:

"McClure got people past vanity—how many people are looking at my page?—and into thinking about the whole customer lifecycle, the most efficient way to break it down, and how each part could be improved. It was a sea of change in the way founders thought about their businesses."

McClure’s original framework listed the 5 pirate metrics as acquisition, activation, retention, referral, and revenue—each essentially a category of metrics tied to relevant stages in the user journey. But in a free-to-paid revenue model, monetization happens much earlier in the journey—when free trial or freemium users convert to paying customers.

We rearranged the order of the pirate metrics to reflect this increasingly common SaaS business model.  

In our framework, the pirate metrics are:

  • Acquisition—the number of users who sign up for your free trial or freemium plan
  • Activation—expressed as the percent of users who have achieved value, out of total acquired users
  • Revenue—can be measured by average contract value (ACV), monthly recurring revenue (MRR), average revenue per user (ARPU), etc.
  • Retention—the number of users who continue using or paying for your product (typically month over month)
  • Referral—the percentage of current users who successfully recruit new users to your product

You might notice some rough correlation between the Product-Led Growth flywheel and the pirate metric framework. And it’s true: The pirate metrics can easily be applied to our flywheel model to measure of success at each stage in the user journey.

The good news is that if you’ve fully embraced the principles behind the pirate metrics already, transitioning to the Product-Led Growth Flywheel should feel like a natural next step.

How to measure product-led growth

Now that we’re clear on our frameworks, let’s take a closer look at some of the most important SaaS metrics for measuring product-led growth.

Time to value

Time to value definition with icon from the Product-Led Growth Collective. This image defines time to value (TTV) as the time it takes for new users to reach their aha moment or activation event and realize your product’s value.

Time to value (TTV) is the amount of time it takes new users to reach their first aha moment or activation event. Time to value could also be looked at as the time it takes users to go from evaluator to beginner—first 2 stages in Product-Led Growth Flywheel.

Time to value can be further broken down into immediate (or short) time to value, and long time to value.

  • Immediate or short time to value: If it’s raining and you duck into a nearby store to buy an umbrella, the time to value is immediate—you’re no longer getting soaked and can see the value of the umbrella straight away.
  • Long time to value: Many SaaS products fall into this category. Buying or signing up for your product doesn’t automatically provide value—some further action is required. That might involve inviting colleagues, importing customer data, integrating other tools, or otherwise completing your user onboarding sequence before value is achieved.

The goal is to reduce TTV as much as possible—the closer to zero, the better. For products with an inherently long time to value, that often means optimizing the user onboarding experience around the key actions within your product that correlate to activation.

Product-qualified leads

Product-qualified leads definition with icon from the Product-Led Growth Collective. This image defines product-qualified leads (PQLs) as leads who have already experienced your product’s value. Typically activated users with a free trial or freemium account.

Product-qualified leads (PQLs) are typically activated users—folks who have completed a key action within your product, had their aha moment, and have seen the value that your product can offer first-hand. In other words, they’re probably the warmest leads that your sales team is ever going to get.

Your exact definition of a PQL will differ from other companies. How you define a product-qualified lead will depend on the specific actions that a user takes within your product that indicate they are ready to move on to the next stage of the user lifecycle.

To find your product’s activation event and define what a PQL looks like at your company, you’ll want to use a combination of user interviews, session recordings, and A/B tests to identify the user behaviors that correlate with conversion and retention.

Expansion revenue

Expansion revenue definition with icon from the Product-Led Growth Collective. This image defines expansion revenue as one of the most important levers for SaaS growth. Measures the revenue generated from existing customers through upsells, add-ons, cross-sells, etc.

Expansion revenue—also called expansion MRR—measures the revenue generated from existing customers through upsells, add-ons, cross-sells, etc.

Although it’s often overlooked in favor of net new acquisition, expansion revenue is easily one of the most important levers for SaaS growth. Think about it: It’s a lot easier to get more money from happy (already paying!) customers than it is to sign on brand new accounts.

It’s a lot more cost-effective, too: It’s roughly 2X cheaper to upsell to an existing customer than it is to acquire a new one—and over 3X cheaper to generate expansion revenue than new customer CAC.

Prioritizing net new acquisition at the expense of expansion drains time and resources across the company. The result is slower growth and a lot of untapped revenue. For a healthier business, ProfitWell recommends that at least 30% of your revenue should be expansion revenue—but really, the higher the better.

“Customers leave. Churn is inevitable. Even if you can get it down >1%, it's still going to hurt your growth. Acquisition can't fight it. The only thing that can is expansion.”
Patrick Campbell, Co-Founder & CEO of ProfitWell

Average revenue per user

Average revenue per user (ARPU) definition with icon from the Product-Led Growth Collective. This image defines ARPU as a good indicator of the overall health of your business. Includes an equation for ARPU: It’s calculated as MRR divided by number of customers.

Average revenue per user (ARPU) is the amount of money, on average, that you can expect to make from an individual user. It’s a straightforward metric, calculated as total MRR divided by the total number of users.

Although it’s sometimes dismissed as a vanity metric, ARPU can be a very good indicator of the overall health of your business. It’s most useful as a high-level way to compare your company to your competitors—and indeed, ARPU has been used by stock analysts to compare subscription-based companies for decades.

“All else equal, the company with the higher ARPU is more profitable.”
ryan farley, lawn starter

Customer lifetime value

Customer lifetime value (CLV) definition with icon from the Product-Led Growth Collective. This image defines customer lifetime value as a prediction of how much revenue you can expect from a single customer over the duration of their account’s lifetime. Used to identify valuable customer segments.

Customer lifetime value (CLV, or LTV) is a prediction of how much revenue your business will receive from a single customer over the duration of your relationship. Lifetime value is used to identify valuable customer segments and gain a more thorough understanding of reasonable acquisition and retention costs.

There are many ways to calculate CLV, both historically and predictively. At its simplest, the formula can be written as:

(Customer revenue * customer lifetime) - cost of acquisition and maintenance

Or you get more involved, as HubSpot does :

Average purchase value * average purchase frequency rate * average customer lifespan

Here’s another formula from David Skok:

(Average MRR per account  * gross margin percent) / revenue churn rate

However you calculate it, customer lifetime value is one of the most important SaaS metrics that you can measure—some would say it’s the most important. That’s because CLV provides a long-term perspective to your customer strategies by allowing you to not only understand how much a customer is worth to you right now, but also to predict how valuable they will be to your business over time.

Customer lifetime value can help you make important decisions across your business. Marketing teams, for instance, can use CLV to understand how much money should be spent acquiring new customers. Hint (but also kind of a no-brainer): The cost of acquisition should always be lower the lifetime value of a given customer segment. This same logic can help sales determine which types of customers they should spend their energy pursuing.

Customer success teams can use CLV to determine the amount of money and resources that should be spent retaining existing customers. Customers with high CLVs probably warrant more CS resources and maintenance than those with a lower lifetime value.

And product teams can use customer lifetime value to understand the needs of their most valuable users. These kinds of customer insights can not only inform design decisions, but help product teams validate their decisions at a business level.

Net churn

Net revenue churn definition with icon from the Product-Led Growth Collective. This image defines net revenue churn as the amount of money lost after accounting for new and expansion revenue. Often expressed as a percentage.  Includes an equation for net revenue churn: It’s calculated as (revenue lost in period - new and expansion revenue) divided by revenue at beginning of period.

Churn is the bane of every SaaS company. And as Patrick Campbell said, it’s also inevitable—some people are going to leave your product, plain and simple. You’re almost always going to have to report some churn, which can feel a bit doom-and-gloom-y out of context.

That’s why when it comes to measuring SaaS growth, net churn is a more useful metric than gross churn, because it gives you a more holistic picture of your company’s health.

And, generally speaking, revenue churn is a more useful metric for SaaS growth than customer churn. Because, let’s be real, even though it sucks to lose your favorite customer, it losing your most profitable customer hurts even more.

Although that’s not to say that there isn’t important information to be gleaned from monitoring customer attrition at the account level. For instance, if you’re suddenly losing most of your low-tier subscribers and gaining customers on the higher end of the market, you should find out why.

But if you only report one churn number, it should be net revenue churn—the amount of money lost after accounting for new, expansion, or reactivated revenue.

To picture this in practice: Imagine you lost $2,000 from customer attrition during a given time period, but gained $3,500 from new accounts and upsells during the same period. That leaves you with a negative net revenue churn of $1,500—which is a very different picture than the gross churn number.  

Virality and network effects

Virality definition with icon from the Product-Led Growth Collective. This image defines virality. Virality occurs when a product’s rate of adoption increases exponentially as more people share it.
The k coefficient measures the number of new users that each existing user can successfully convert  Includes an equation for virality. Virality is calculated as C(0) * k = number of customers at the end of the period.

The terms virality and network effects are sometimes used interchangeably but are, in fact, very different (although they do often occur hand in hand).

Product virality occurs when a product’s rate of adoption increases exponentially with each additional user. Viral growth is measured using the viral coefficient—or the k factor—which is calculated as:

k = the number of invitations sent by each customer * the % conversion rate of each invite

In order for virality to exist, k must be greater than 1. For that to happen, users must be able to promote the product by using it.

Take Zoom, for example. By sending a Zoom video conference link to attendees who don’t already use the tool, existing users promote the product in the context of its use.

A product with a network effect, on the other hand, becomes more valuable to users as more people adopt the product. In the Zoom example, attendees can join a call without creating an account—their participation adds value to the individual user experience, but doesn’t enhance the product long-term. Compare that to a social networking app like Instagram or 2-sided marketplace like Airbnb: The more people post photos on a regular basis or list their homes for rent, the better the product experience becomes for other users in the long run. These products have network effects.

Network effects definition with icon from the Product-Led Growth Collective. This image defines network effects vs virality. A product with a network effect becomes more valuable to users as more people adopt the product. Includes illustration infographic of a network effect

Why are networks effects so important? Venture firm NfX lists network effects one of the 4 remaining defensibilities—alongside brand, embedding, and scale—that once established, make it harder for your business to fail. Put simply:

“Competitive advantages” [like virality] help your company become successful. “Defensibility” helps you stay there. Both add value to your business.

So, who owns product-led growth metrics?

In short, everyone.

The metrics we’ve detailed above are certainly not the only numbers that your teams will be tracking. In a product-led organization, marketing will still monitor pageviews, sales will still track pipeline and bookings, CS and support will still measure NPS and response times, and product and engineering will still be concerned with delivering an exceptional product.

Product-led metrics aren’t meant to replace all your old measurements of success. As a rule, the more data you track, the more holistic a picture you’ll have of your business. What product-led metrics are meant to do is provide common, quantifiable goals that help every department understand and optimize the user journey as a driver of growth.

We already talked about how customer lifetime value can be leveraged by different teams to make more informed decisions about customer acquisition, retention, and the overall user experience. To give another example of how cross-functional teams can report on and affect product-led growth metrics, let’s a closer look at virality.

The concept of virality may come from marketing, but that doesn’t mean marketing is solely responsible for improving the viral coefficient in a product-led organization. In order for a product to go viral, users must be able to share the product in the context of its use—in other words, a product has to be designed and built with virality in mind. That involves designers, engineers, UX copywriters—the whole lot.

And then of course, there are the aftereffects of selling to and servicing invited users. If your growth model relies heavily on referrals, your customer-facing teams need to be working alongside marketing and product to think about the way you onboard and convert users who have been invited to your product. Because virality isn’t worth much if you’re not retaining the users you gain!

We could go through every one of the PLG metrics above and give examples of ways that they can be affected by different departments. But you get the point—product-led growth is a (multi-)team sport.

And just like you can’t effectively play a game if everyone is using a different scoring system, you can’t become product-led without agreed-upon measures of success. The right metrics give you the tools to measure the otherwise chaotic actions happening within your product. But knowing the “why” behind the data is more important than the metrics themselves.

Remember, the goal isn’t to improve your metrics for the metrics’ sake—it’s to leverage the data you collect to make better decisions and fuel growth by optimizing the user experience. If you’re drowning in spreadsheets but aren’t iterating on your product or processes, you’re probably doing it wrong.