Everything You Need to Know About PQLs (Product Qualified Leads)

Move aside SQLs, PQLs are here to save the day. 

PQLs are prospective customers who have used a freemium or trial version of your product and whose actions show a strong interest in purchasing it.

A PQL takes lead qualification a step beyond a marketing qualified lead (MQL) or a sales qualified lead (SQL) — where a PQL is way more likely to convert. 💸


Because they’ve already received value from first-hand experience with your product!

But how do you begin to identify leads with buying intent?

Read our ultimate guide to find out what a PQL is and how to qualify them, with a few industry examples for comparison.

Then, we’ll discuss how to measure your PQL conversion rate, turn these leads into customers, and other key metrics.

Further Reading

  • Discover 4 brilliant benefits of tracking the SaaS Magic Number and how to calculate it. 
  • Are you an aspiring entrepreneur? Check out the 4 major types of SaaS Business Models
  • Read our guide on SaaS Net Burn Rate to resolve your burning questions about this crucial metric.

This Article Contains:

What Is a PQL?

PQLs are ‘product qualified’ because they’ve actually used your product and experienced meaningful value from it. They are more likely to become a paying customer based on their product engagement. 

How do you find them?
Typically, you identify a qualified lead by tracking their in-product actions. 

These actions can be anything from signing up for a freemium plan or free trial, completing certain tasks, or frequent product usage (more on that later).

But you may be wondering, is it worth all the effort?

With a PQL strategy, you can:

  • Gain insight into who an ideal customer is via product usage.
  • Pinpoint the right moments to reach out to them, e.g. if they’ve frequently used a key feature or hit a usage limit.
  • Improve collaboration between departments like marketing, sales, customer success, and the product team, as everyone has a role in driving PQLs.
  • Spot upselling and cross-selling opportunities by understanding what draws a prospect to your offering.

And the best part?
PQLs are revolutionizing the world of SaaS sales. 

Using product usage data for lead qualification can drastically reduce the length and cost of your sales cycle. This approach is notably more cost-effective than traditional marketing or sales qualification.

Unlike SQLs, you don’t have to depend too heavily on the sales team to turn PQLs into customers.

Let’s look closer at what makes PQLs stand out from the crowd.

What’s the Difference Between PQL Vs. MQL?

PQLs show buying intent by using your product directly. 

Marketing qualified leads (MQLs) show interest via engagement with your marketing materials.

In contrast to a product qualified lead, a marketing qualified lead doesn’t directly interact with products or show intent to buy — yet.

Instead, a SaaS company uses alternative analytical methods to assess which leads are marketing qualified. For example, subscribing to newsletters, interacting on social media, or repeating site visits.

MQLs need more nurturing from the marketing team before becoming a sales qualified lead (SQL). Once the marketing team believes they’re showing buying intent, the team can classify the marketing qualified lead as a sales qualified lead.

What’s the Difference Between PQL Vs. SQL?

PQLs indicate interest in your product by directly using it. 

SQLs indicate interest through deal-closing conversations with your sales team.

Like PQLs, a sales qualified lead shows they’re open to purchasing.

So, what’s the difference?
Although they’re both high intent, with SQLs, you assess leads based on a content and website data model, not product usage data.

In a nutshell, SQLs will talk to a sales rep before buying. PQLs may not even want to talk to the sales team before purchasing. They may skip your sales team for a ‘self-service’ conversion model.

For SQL lead generation to be profitable, you need a top-notch sales team. Meanwhile, PLG companies utilize a PQL model because they have a strong quality assurance process and believe the product speaks for itself.

Unlike MQLs and SQLs, you don’t have to squander your sales and marketing team budget to acquire and qualify leads. Instead, your priority is quality assurance because the product experience is your main selling point.

So how do you even qualify PQLs?

Let’s discuss identifying a qualified lead by monitoring product usage.

How to Identify a Product Qualified Lead

You can define a lead as ‘qualified’ once they’ve reached their ‘aha moment’.

It’s the moment they go:

The ‘aha moment’ is when users move past their skepticism and discover the promised initial value of your SaaS product.

But what makes a lead product-qualified?
Generally, your qualification criteria boils down to three major factors:

  • In-app usage patterns: Regular logins, lengthy or repeated sessions on the price page, or clicking on premium features can reveal buying intent.
  • Assistance requests: A lead that has queries for more information is a good indicator of interest in your SaaS product.
  • Adoption velocity: The speed at which a prospect begins to engage in product usage could indicate that they see meaningful value in your offering. Slow adoption rates can highlight which leads may need more nurturing.

Still unsure what data you can count toward an ‘aha moment’?

Let’s look at some examples of how other PLG companies define PQLs.

4 Examples of PQLs to Help Define Your Qualification Criteria

PQLs don’t have a static definition. What a PQL looks like for one company might be entirely different from another.

You should tailor a PQL’s aha moment around the services you provide.

For example, let’s look at how industry leaders define PQLs:

  • Slack: When an account reaches the 2,000 message limit
  • Salesforce: Once someone creates a custom object
  • Facebook: When a user adds 10 friends in seven days
  • Intercom: When someone has a certain number of conversations

Of course, there’s no one-size-fits-all approach. 

The makeup of your analytical methods depends entirely on what product data you consider to have the most value to your SaaS company.

So if you offer a messaging service like Slack, it makes sense to shape your PQL definition around the number of messages a user sends.

Once you’ve identified your criteria, there’s another important factor to discuss:


After all, the entire point of focusing on PQLs is that they’re more likely to convert without even talking to sales.

So do you determine whether your PQL strategy is paying off?

PQL-to-Customer: Calculating Your PQL Conversion Rate

  • What is PQL-to-customer conversion rate?: A PQL-to-customer conversion rate refers to the percentage of product qualified leads who convert — AKA, start paying to use your product or service.
  • What type of company is PQL-to-customer conversion rate applicable for?: This metric isn’t usually applicable to companies in the pre-launch stage. At that point, you’ll focus your efforts on researching the competition, identifying your unique selling proposition (USP), and defining your target market. You’ll only want to start tracking conversion rates once you’ve officially launched your SaaS product and gathered a sizable number of free trial users.
  • Why is PQL-to-customer conversion rate important?: It’s vital to show if your offering delivers enough value to justify the price.
  • How to measure PQL-to-customer conversion rate:

The formula is:

PQL–to–customer conversion rate = No. of PQLs that converted / Total no. of PQLs * 100

Suppose you gained 1,000 PQLs in a month and 400 converted to paid accounts. Your calculation is:

PQL–to–customer conversion rate = 400 / 1,000 * 100 = 40%

  • How often should you measure PQL-to-customer conversion rate?: Review PQL conversion rates at least every quarter to keep tabs on your progress. However, since PQLs convert faster than SQLs or MQLs, you may want to check your PQL-to-customer conversion rates more regularly (e.g. monthly).
  • PQL-to-customer conversion rate benchmark: PQLs convert to paying customers around 25% of the time in the SaaS industry.

How to use the PQL-to-customer conversion rate in your SaaS company:

When monitoring your PQL conversion rate month on month, you can tweak the customer experience based on your results.

For example, if PQL conversion rates go down, you might want to offer more proactive customer support, simplify the onboarding process, or utilize churn surveys to identify any barriers to purchasing.

And to further refine your calculations, compare conversion rates to CAC (Customer Acquisition Cost).

CAC measures the total cost of winning a paying customer. So you’ll be able to see whether product-focused lead generation results in lower customer acquisition costs than SQLs or MQLs.

The big question is:
How do you boost those conversions?

How to Increase PQLs Conversions

To push a PQL into becoming a paying customer, consider the following steps to a winning PQL strategy:

1. Adaptive Pricing Strategy

You know what the most important part of a good pricing strategy is?

That’s right!

You need to strike a balance between attracting customers and generating revenue.

And offering a free trial or freemium version of your product benefits both parties. Customers get to try before they buy, so they know exactly what they’re paying for, while you gain delicious insights from product usage data.

With this data, you can hone in on a PQL’s most-used and valued features and create individualized, targeted pricing tiers. For example, cost by volume of app usage, cost per use, and monthly or annual subscription pricing.

Just ensure you clearly showcase each plan’s features, benefits, and pricing. Your PQLs will start upgrading to paid plans in no time!

2. Intuitive User Onboarding

Users can derive value from free trials but may still have some queries. 

A lack of guidance at this stage could result in a lost opportunity.

Onboarding involves familiarizing users with your offering to help them unlock the full potential of your product.

The process may include the following:

  • Interactive walkthroughs
  • Video guides
  • In-app messages
  • Customer feedback forms 

Skeptical about the value of this step?

Around 97% of SaaS companies believe this process is necessary for product led growth.

By providing real-time assistance, you can resolve any issues preventing users from converting into customers.

3. Timely Interactions

It’s not just about how you reach out to leads but when.

In-app notifications and automated emails are great conversion tactics. 
They’re even better if you send them at the right time.

Watch out for suitable conversion opportunities, such as:

  • When a user hits a paywall.
  • When users encounter issues during their trial and appear to be stuck.
  • When product usage data indicates they may gain more value via trying additional products, services, or upgrades.

These may be signs that it’s time to begin actual sales discussions.
Ultimately, conversions are driven by having a good understanding of your target audience.

Many PLG companies view product data as a great KPI (key performance indicator) because of the user information PQLs provide.

But how do you know if the cost of acquiring, nurturing, and converting PQLs is worth it?

Some metrics can give you insight into how well your PQL model works:

Product-led Metrics and KPIs all Departments Need to Know

For a window into the success of your entire organization, you’ll need to track metrics that measure the pulse of your business. 

Critical PQL-related metrics include:

  • Activation Rate: This is the number of users who reach a certain threshold (one of the above ‘aha moments’) in the product experience and become a qualified lead. This metric is crucial for identifying PQLs.
  • ARPU (Average Revenue Per User): This metric is how much income each of your subscribers generates, so you can gauge how successful your leads are on an individual basis.
  • Revenue Churn: This metric is the earnings you’ve lost from cancellations and downgrades. When offering a subscription service, you must continually monitor your revenue beyond the initial conversion stage.
  • MRR (Monthly Recurring Revenue): MRR is your monthly subscription earnings. Tracking MRR and ARR helps companies assess their product-led growth model’s health and potential profitability.
  • ARR (Annual Recurring Revenue): ARR is your yearly subscription earnings.

Which metrics can you use as a PQL-related KPI?

It depends on your goals, for example:

  • Activation: To improve your activation process, you should track your activation rate, as these numbers can reflect the quality of a prospect’s product experience.
  • Growth rate: Tracking NRR (net revenue retention), MRR, or ARR can keep you in touch with your business’s health and forecast the momentum of your product led growth.
  • Revenue growth: Conversion rates are crucial if you’re focusing on monetization. Ideally, your conversions should be high, but low rates can reveal whether the product experience isn’t delivering enough initial value, the product team needs to improve any features, or you need to lower pricing.

Spot Qualified Leads Lightning-Fast with Product Data

By firmly establishing your own qualification criteria, you can correctly identify who’s deriving the most meaningful value from your services.

Product led growth is a fantastic way to shorten the sales cycle, combat churn, and identify conversion opportunities.

Follow our rock-solid tips and pave the way for a smooth, efficient PQL-to-customer pipeline.

And if you need help enhancing your content’s performance and driving organic search traffic, contact one of Startup Voyager’s specialists today and supercharge your conversion rates!

With our powerful content and SEO strategy, you can target your ICPs and greatly improve your chances of turning them into PQLs.


About the author

Startup Voyager is a content and SEO agency helping startups in North America and Europe acquire customers with organic traffic. Our founders have appeared in top publications like Entrepreneur, Fast Company, Inc, Huffpost, Lifehacker, etc.