13 Product-led growth metrics to measure in 2023

How does a company develop a shared language for understanding performance?

How does it motivate teams, company-wide, to work toward mission-critical goals? 

Most importantly: How does it measure success?

‍Metrics.

‍Metrics are key to business, process, and revenue growth because, as we’ve all heard, you can’t optimize what you can’t measure.

It’s perhaps even more important when you have a product-led growth (PLG) or Product-Led Sales motion (PLS), but the metrics may look a bit different from your typical SaaS business. 

In this article, we’ll discuss the top product-led growth metrics to measure in 2023, including metrics that are critical to the success of your PLS approach. 

Metrics to measure in a PLS motion

The fact is that the vast majority of PLG businesses do have sales teams. 

🪄Download Pocus’ 2022 Product-Led Sales Benchmarks Report for more insights from 200+ of today’s best GTM teams. ‍

However, these Product-Led Sales teams look different from those in your traditional, sales-led organizations. They’re typically more data-driven, more consultative in nature, and heavily focused on the product. Because of this, they also tend to be more effective. 

We realized there wasn’t a solid definition for this new way of selling SaaS, which isn’t sales-led but at the same time isn’t fully product-led either. 

That’s why we set out to define this hybrid approach — the Product-Led Sales motion. 

Here’s our current definition, although we expect these parameters may continue to shift as the space develops and matures: 

“Product-Led Sales is a go-to-market approach that relies on existing users of the product to drive revenue, including conversion, upsell, cross-sell, and expansion.”

Measuring the success of this cutting-edge motion requires specific metrics. Let’s take a look at what those are:

1. Product-qualified leads (PQLs)

A product-qualified lead (PQL) is a user that meets the following core criteria: 

• Demonstrates high product usage
• Fits your ideal customer profile, and/or
• Has indicated buying intent

PQLs are an indicator that it’s time for the go-to-market team to jump into action. 

Say goodbye to the idea that PQL is just one score — that usually won’t be enough to capture the nuance of your GTM motion. Instead, over time, you should develop multiple PQL definitions and think about them as a stage in the customer lifecycle. PQLs can be segmented based on factors like:

• Target market: company size, industry, etc. 
• Your PLS goals and playbooks: expansion, free trial conversion, etc.
• Level of sales-readiness: sales, sales-assist, marketing nurture, etc.  

PQLs are great for spotting product champions, building relationships, and, if done well, taking that champion wherever they go next. They are the people sales-assist should be keeping a close eye on, finding ways to delight them whenever possible, solving pain points, and helping them unlock new paths to value.

‍🪄Read How to convert product-qualified leads into revenue to learn more about PQL segmentation, workflows, and product-led growth tools that boost PQL conversions. 

2. Product-qualified accounts (PQAs)

We’ve seen this next PLS metric — product-qualified accounts (PQAs) — used almost interchangeably with PQLs. 

However, PQAs are actually a little (a lot) different.

A Product Qualified Account refers to a company or “account” that has been qualified based on a combination of the aggregate usage from individual users, ICP fit, buying intent, and potentially other important signals.

PQLs have a many to 1 ratio with a PQA. You can have many PQLs associated with 1 PQA. But a concentration of PQLs within an account does not always mean their associated account will also become qualified.

To understand how individual user behavior influences account conversion, you need to operationalize both PQLs and PQAs within your PLS motion. PLG orgs are starting to appreciate the difference between these metrics, and tracking them accordingly. In 2022, 17% measured PQAs specifically. 

More on PQLs vs. PQAs

Most companies will focus their PQL definition on end-user behavior inside the product. These signals are key milestones met or feature usage that qualifies that user. In contrast, companies will define PQAs more broadly. A PQA will often focus first on firmographic data like customer size and whether it is a target account within a particular industry or geography. Then the definition will layer in whether there is meaningful usage from both end users and decision-makers within the account. PQA definitions will also look at signals that the product is being used across multiple teams or workspaces.

PQLs can be a step on the path to PQAs. If you get enough individuals from the same organization to reach value, making the case with a decision-maker to upgrade to an enterprise license can be easier. In reality, that's not always the case. Departments often work in silos and the consolidation process can be lengthy, causing friction and drop-off.

That's why relying solely on PQLs to run expansion or consolidation playbooks isn't always the right move. Instead, having a PQA framework with specific account-based triggers allows sales teams to have more accurate data to make a convincing business case. Within a PQA, you can call on PQLs first, document how they're using the product, and navigate to the decision maker to make a case for broader adoption — a perfect example of multithreading at work.

3. Conversion rate from PQL to SQL

In a PLS motion, it’s not only important to know how many product-qualified leads (PQLs) have been surfaced — but whether or not there was a meaningful conversion from PQL ➡️ SQL (sales-qualified lead: more on that later).

However, out of the PLG teams we surveyed for the PLS Benchmarks Report, only a quarter knew whether or not they were even measuring the conversion rate from PQL to SQL. Out of those who were tracking it, the conversion rate was 20 to 30%.

The most effective strategy for sales to convert PQLs into revenue in a PLS motion is to remember one thing: Help, don’t sell.

That means reaching out to PQLs when: 

• They raise their hand for help
• They appear stuck
• They’re blocked from reaching value for any reason 
• They have run into your paywall
• Sales can add real value (exposing new features, etc.)

Sales can act on these triggers in two steps:

1. Set up notifications when PQLs take certain actions in the product

2. Use this information to take the best action to move the PQL down the path to conversion

That covers the PLS metrics portion. But, there’s a variety of additional metrics every sales leader should keep top of mind to understand the overall health of their revenue engine, beyond acquisition.

PLG metrics for tracking GTM team performance

Growth at all costs is no longer the only way to build a SaaS business. This was evident in the responses to our 2022 Product-Led Sales Benchmarks Report, where Net Dollar Retention (NDR) ranked pretty high (50% of companies surveyed are tracking it) in terms of priority metrics to track GTM team performance.

‍OpenView’s 2022 SaaS Benchmarks Report, also backs this step away from growth as the only success indicator, proving the “Rule of 40” is back in style.

📈Context refresh: The Rule of 40 rose to popularity in 2015 by venture capitalists. It states that for venture-backed SaaS companies, their annual revenue growth rate + operating profit should be equal or greater than 40%. ‍

Kyle Poyar, Operating Partner at OpenView, recently dove into the subject in his newsletter. In 2021 growth was the name of the game: 57% of a company’s valuation was explained by the rate at which they could grow their ARR. The Rule of 40, which takes into account growth and profitability, it seemed, was out. As Kyle put it, “profitability metrics on their own were entirely uncorrelated with public SaaS company valuations and made the Rule of 40 less predictive than growth on its own."

That’s all changed. As of June 2022, the Rule of 40 explained 39% of valuation differences while growth rates alone only explained 27%. 

The following product-led growth metrics, especially NDR and CAC:LTV, are powerful for going steps above optimizing for new revenue acquisition. To build an effective growth strategy based not only on the bottom line, but on other factors like churn and resource spending, all product-led businesses (no matter where they land on the spectrum) need to be looking at this kind of variety of metrics.

Here are the core metrics PLG organizations can use to track and understand their go-to-market (GTM) team performance.

4. Net dollar retention (NDR)

Net dollar retention (NDR), or net revenue retention (NRR), is a metric that shows the percentage of revenue retained from existing customers, over a specific amount of time. 

NDR = ((MRR + upgrade MRR - downgrade MRR - churn MRR)/MRR) x 100 

• Monthly recurring revenue (MRR): repeat revenue your company brings in, monthly
• Upgrade MRR: monthly addition revenue from upgrades (upsells, add-ons, etc.)  
• Downgrade MRR: monthly revenue losses from contract downgrades or cancellations
• Churn MRR: recurring revenue lost to downgrades, monthly

NDR is a valuable measurement because it shows how good your product is at engaging and retaining paying customers — which pours into a higher customer lifetime value, another important metric we’ll cover in this section. NDR is often used to create growth predictions and used in equity discussions. 

Since driving growth from existing customers is less costly than acquiring net new business, we expect to see more PLG organizations (and others along the product-led growth spectrum) in 2023 and beyond lean on expansion playbooks that grow NDR and increase profit margin efficiency — sustainably. 

‍🪄To further protect and increase NDR, SaaS businesses can also take a cue from OpenPhone’s Grow-Defend-Maintain playbook to:

• Go after upgrade opportunities (grow)
• Defeat the churn of awesome accounts (defend) 
• Preserve business with accounts that have reached their full potential (maintain)  

5. Win rate

Win rate is a metric for understanding how much success a sales team has had, aka how many deals it has closed, during a certain period of time — such as a quarter. 

Finding win rate is simple: Divide the number of won opportunities by the total number of opportunities. 

Win rate is especially useful to track over time, as it can uncover whether or not sales productivity is increasing and when it’s time to upgrade your sales practices. 

6. Average contract value (ACV)

Average contract value (ACV), sometimes called annual contract value, is a metric that finds the average revenue generated from all your business contracts over the course of a year. 

To find ACV, take the total value of all contracts/total length of all contracts in years.

Why measure ACV? ACV is a helpful metric for understanding approximately how much revenue you can generate per contract, per year — providing insight when it comes to forecasting, determining sales and marketing efficiency, and how much to spend on customer acquisition. 

🚨Sometimes companies use ACV to measure individual contract values, over the course of a year. In this case, take the total value of a contract/the total contract length in years.

ACV is often compared to customer acquisition cost (CAC) to make sure the contract value is higher than the cost of acquiring a new customer. If it isn’t, you may want to rethink the motion you’re using to close contracts and look for ways to optimize sales resources.

Sales teams can’t:

❌Reach out to every sign-up

❌Chase opportunities that have zero buying intent

And their leadership really shouldn’t:

❌Spend big on costly cold outbound without ROI 

❌Buy tools that sales reps don’t love‍

🪄 Looking for ways to do more with less? Read: 5 common playbooks to activate your Product-Led Sales motion. 

7. Expansion revenue 

The expansion revenue metric calculates new revenue generated from existing customers. This revenue is typically the result of upsells, add-ons, etc.

Here’s how to find expansion revenue: sum of expansion revenue/sum of new revenue.

Expansion is a critical lever in a product-led growth strategy. After all, it’s much more affordable to generate revenue from existing customers than it is to acquire new ones, helping you maintain healthy ratios of other important metrics we’ll mention below, such as CAC:LTV.

Once you find yourself on firm ground within strategic accounts and see an opportunity to increase seats, run a seat expansion playbook to gain users and grow the expansion revenue metric. 

8. Sales cycle velocity

Sales cycle velocity uncovers how long it takes for deals to pass through your pipeline to generate new revenue.

To find sales cycle velocity, take (number of opportunities x deal value x win rate)/length of sales cycle. 

This metric is a pivotal measure of sales effectiveness. It’s also important for forecasting, because it ultimately finds how fast your business can make money and how much revenue you can expect to generate over a certain period of time. 

One way to improve your sales cycle velocity metric is to increase your win rate — closing more deals more often means new revenue faster.

Easier said than done, right? Not with a Product-Led Sales motion. With a PLS approach, sales teams are equipped with product usage data that enables them to swoop in at the right time with value-adding tactics and messaging. This effective and efficient approach means more wins and a shortened sales cycle.

Another element of the PLS motion that can accelerate sales cycle velocity is the sales-assist role. Sales-assist is all about finding and acting on opportunities to engage with and convert high-potential accounts — especially those that aren’t finding value quickly enough in the self-serve flow.  

‍🪄Learn more about sales-assist: ‍

The Zapier playbook to build sales-assist function from zero to one‍

Guide: Implement a sales-assist function in 7 weeks

9. Average revenue per user (ARPU)

Average revenue per user (ARPU) finds the average of how much revenue you earn per paying user, per month.

To find ARPU, divide your monthly recurring revenue (MRR) by your number of paying users that month.

ARPU is crucial for understanding which of your paying users are most profitable — helping you sharpen up your ideal customer profile (ICP) and apply your customer acquisition resources to the highest money-making opportunities. 

10. Customer acquisition cost (CAC) to lifetime value (LTV) ratio (CAC:LTV)

The customer acquisition cost to lifetime value ratio (CAC:LTV) is a formula for figuring out how much you should ultimately spend to acquire new customers. 

Customer acquisition cost (CAC) is the total cost of acquiring customers during a specific period/the total customers acquired in said period.

Lifetime value (LTV) is ARPU/churn rate. 

• ARPU: recurring revenue over specific time frame/paying users in that time frame
• Churn rate: 1 - retention rate 
• Retention rate: new user revenue during time period/total revenue during previous time period

To find the ratio, take LTV/CAC. 

Ideally you’ll want a ratio of 3:1 or higher, which means you’re 3x-ing what you spent on customer acquisition over the lifetime of that customer. 

If your ratio comes out lower, there are several things you can do to focus on raising it:

• Drop CAC, possibly by pivoting to ICPs with higher LTVs
• Play with pricing until you find a better conversion rate 
• Shorten the sales cycle (PLS playbooks can help) 

Bonus: Thinking about traditional metrics through a product-led lens 

We’ll end by touching on some common metrics in a traditional, sales-led motion and how to approach them in a modern, product-led motion. 

11. Marketing-qualified leads (MQLs) 

Marketing qualified leads (MQLs) are potential customers, aka leads, who have been designated by marketing teams as “more likely to become a customer” versus other leads. Scoring is based on their interactions with marketing content like CTAs, downloads, landing pages, emails, social media posts, and so on. MQL scoring is not based on product usage.

The problem with MQLs?

They can still be too cold for sales to close consistently.

Unless they’ve actually raised their hand and asked to contact or to be contacted by sales, MQLs are largely based on marketing consumption and surface-level product interactions — not deep, real-time product usage data that uncovers unique behaviors, use cases, and needs.

While there's a lot of talk in the product-led world about letting go of the MQL in favor of the PQL, there’s a benefit to tracking both. MQL signals help you identify the path your prospects take to discover your product. Which, if you lean product-led, or aspire to, getting users to land on your website and self-serve is all about understanding how to get them there. All that legwork heavily relies on an optimized MQL definition and the corresponding tactics to target and nurture them.

So, we’re not ready to banish MQLs just yet, and neither are 66% of PLG companies (source: 2022 PLS Benchmark Report). Instead, we like to think of them as additional signals you can use to create a 360 degree view of your customer.

Some companies are looking into MQL and PQL composite scoring, while others are keeping them separate and base action (marketing nurture or sales outreach) on the lead’s last activity.

🪄Learn more about advanced PQL scoring concepts 

12. Sales-qualified leads (SQLs)

Sales-qualified leads (SQLs) are former MQLs or PQLs that sales has reviewed and determined are worth pursuing. This usually happens after a qualifying call or other information collection activity that fleshes out the lead profile.

Sales is looking for a few qualifiers: 

• ICP fit: Are they the right size to get value from our product? Are they in the right industry? Do they belong to the function we're targeting? Etc. 
• Purchase intent: Have they signaled they have actual intent to buy by taking a product tour, requesting a demo, etc.   

It’s not surprising that PQLs convert to SQLs at higher rates than MQLs. By definition, PQLs are warmer (they’re already on your product!) This is why we love the PLS motion — it relies on actual product usage data to pinpoint exactly where and when customers experience value in your product, so sales can touch base with the right messaging at the perfect time. 

13. Sales-qualified accounts (SQAs)

Similar to a PQA, the sales-qualified account (SQA) metric is based on a combination of the aggregate actions from individual users, like demo request or product tour, belonging to the same organization and ICP fit, with an extra layer of vetting from sales. PQAs become SQAs once sales has determined the account is a real opportunity for closing.

When an account reaches the SQA threshold, that signals to sales that it’s time to approach with a pitch for converting to a paid account, a higher-tier account, expansion within the account, or whatever next step makes sense for your sales motion.

Level up your GTM tracking and performance

If you’re dealing with black-box product usage scores, or stuck in dev feedback loops to surface the right data — it might be time to update your tech stack. Optimize your tooling for product usage information and power up all of your product-led growth metrics with the right product-led growth tools. 

‍🪄Here’s a list of 30 Product-led growth tools to build a modern tech stack‍

🆘 Don’t know where to start? Pocus is a dedicated Product-Led Sales platform that’s easy to import data into, configure, and start using immediately — no code required. 

Pocus helps GTM teams understand product data and turn it into revenue with customizable Magic Playbooks for operationalizing your PLS strategies, intelligent scoring that lines up with your unique playbooks, a prioritized inbox that empowers sales to instantly action high-potential opportunities, and lots more. 🔮

‍Explore Pocus and get a taste for how impactful transparent product data can be for understanding GTM strategy performance, increasing new revenue acquisition, improving retention, and preventing churn.