How to Double Your Sales with PQLs: A Complete Guide

Approximately until a year and a half ago, the business world knew only Sales Qualified Leads (SQLs) and Marketing Qualified Leads (MQLs). But that didn’t show the full story – especially in freemium and free-trial SaaS business models. Over the past year or so – those SaaS and IT companies with freemium began to use Product-qualified Leads (PQLs) as the primary indication of high-quality leads who are ready to purchase the product.

In this article, we’re going to see:

What are PQLs, and why are they important? 

In a nutshell – PQLs are leads who already showed an interest in your product. Usually – they’re freemium or free trial users who’re engaged enough with your product.

When I say engaged enough, I mean that:

  • They’re using your core features to achieve their goals in a free trial/free account.
  • They’re already getting results with your product, but they’re not purchasing.
  • Besides the core feature, they’ve also slowly started to adopt your secondary characteristics.

Since they have sampled your product – they’re more likely to convert than leads who haven’t seen your product from the inside.

In other words – by continually monitoring and nurturing PQLs through your sales funnel – you will be able to create a predictable product-led growth that will skyrocket your sales, revenue, and, most importantly – customer retention.

One of the main reasons why PQLs are so powerful is because they’re very scalable and likely to convert into real customers.

Now when we know what the product-qualified leads are and why they are essential, before we see how SDRs can use them to close more deals, let’s see the main differences between SQLs, MQLs, and PQLs.

What are the differences between SQLs, MQLs, and PQLs?

To understand this better, let’s first illustrate the traditional process of lead generation and qualification.

Usually, traditional qualification criteria included things like downloading an ebook or visiting pricing page — activities that imply an interest in your offering.

But on the other hand – PQLs go even further than just showing interest in your product. 

Nothing says “interested” like engaging with your features and using your product. 

Unlike marketing qualified leads who think about other arbitrary factors like email opens, email marketing data, podcasts, whitepaper downloads, webpage visits, and other things – PQLs are related to a meaningful value from your product.

remote selling

In other words – once the Marketing department brings someone inside your product (as the free or free trial user) – leads will automatically identify themselves as the sales-ready leads by using your significant features inside your product and achieving success with it.

This, in turn, will enable you to identify when leads become sales-ready with much higher accuracy. In the case of PQL, you can see how users engage with your product, unlike relying on a proxy of sales-readiness.

Here’s an example of how the MQL -> SQL -> PQL relationship can look like.


After going through the framework, you can understand that this system allows you to identify when leads become sales-ready with much higher accuracy. 

This method is called Product-led growth, and it works by identifying actions that show that users have explored the product and received enough value that they’re ready for a sales conversation.

Product qualified leads can quickly adapt your product since they understand how it works, and they’re getting value from it. When you reach out to a PQL, they should have already experienced something meaningful in your product. 

This process makes it easy for your SDRs to close more deals because you don’t need to guess what your users want. 

You already know this by looking at your in-app data and metrics.

How can SDRs use PQLs to close more deals?

Now we have arrived at the most critical section of this article.

But before we go and see in-depth tactics on how to close PQLs, let’s see how you can identify them.

How to identify PQLs?

This is something that’s clearly different from product to product, from company to company.

Not every product is the same. Not every product has the same features.

Hence – there’s no universal formula for identifying PQLs as you have for SQLs or MQLs.

But – there are some common rules you should follow together with your product team:

  • Identify your major and core features – usually – these are the features your new users will firstly use. In other words: these features are the foundation of your product. For example, if your product is the sales outreach tool space, your core features would actually be importing your email list, creating an email, and sending the campaign.
  • Define the most important metrics of your product – not every company should monitor the same product engagement metrics. For example – for some companies, time spent in the app will be an essential metric – but for others won’t. Hence – sit down with your product marketing team and try to identify the most critical parameters or try to look at your teams’ product reports.

Once you get these things done, you will be ready to identify your PQLs.

I’ve asked people from different companies how they are identifying PQLs, here’s what they’ve told me.

For example, BetterProposals, a proposal software, considers someone as their PQL if they have published at least one proposal.


On the other hand – Airfocus, a product roadmap tool, considers someone to be a PQL if they have created the first project and invited a teammate:

PQL – alternative – according to CEO Loukman Nacik – is considering someone a PQL if they have created his first in-app feature survey.

And finally – Userpilot, a user onboarding software, considers someone their PQL if they have installed the chrome extension, created a few experiences – and published them.

Then, once you have identified your metrics and PQL indicators, it’s up to you to collect and store all this information.

Here’s a snippet from Userpilots’ sheet where they monitor different customers and identifying whether someone became PQL or he still needs some time:


Another great way to identify PQLs during their free trial or free period is by using NPS or CSAT surveys.

If their feedback was great – it means that they’re ready to start paying. If they’re wrong, it means that your customer success team will need to push harder with different scenarios so they can eventually be considered as the PQLs.

In the case of the image above – we can conclude that 25 PQLs are ready to buy products, while 21 one of them need just a little push.

How to close PQLs?

We’ve come to the last but not the least important step.

Now, since you identified who are your PQLs, what should you do?

Here’s how to close your PQLs based on how we at Userpilot do it:

Essentially – everything is based on sending highly-relevant emails to your PQLs.

By looking at different in-app data and metrics, you can create a bunch of different email templates you can use.

For example, if a PQL of Userpilot has low completion rates of one of his/her user experiences, we send him an email like this:


As you can see, it’s super relevant to his current user journey stage. 

When it comes to closing PQLs – everything is about personalization and offering value at the right time (that’s the reason why, besides for identification, monitoring users’ journey is also important). 

Short, catchy, crisp, and straight-to-the-point emails are what delivers the real results in these chaotic times.

Offering unselfish help at the right time is what helps us to close more free trial into customers – here’s what we send if someone needs more time to get adopted to our product:


If someone is achieving a big success with our product and getting great results – you should move on to the next step and try to schedule a demo – also by offering even more value.

Here’s the email we send in this case:

Remember that I mentioned how NPS and other surveys could help you to significantly improve your number of PQLs and identify them in a better and more accurate way?

Here’s how we leverage the power of those surveys to both improve our product, engage with our trial users, and convert them into paying customers:

If someone gives us bad feedback – we send them an email like the one below. The main goal of this email is to understand the users’ pain with our product and try to solve them. Very often – they give us a bad score because they lack an understanding of our product. Fortunately – that’s solvable. 








As you can see – before we send this email – we take an in-depth look at their response and try to understand the reasons behind their opinions as much as we can.

On the other hand – if someone gives us a great score, we consider him a PQL and send them this type of email:

This email helps us to both:

  • Get great score on review platforms (which helps our user acquisition)
  • Build a great relationship with our PQL that will later result in closing a deal.

As you can see – the process of closing PQLs is based on the following:

  • Creating the perfect user onboarding flows – so you can understand the stage in the users’ journey much better.
  • Monitoring in-app data and metrics
  • Sending personal and manual emails that are relevant to users’ current stage, context, and behavior.

The Bottom Line

As you can see – PQLs are far more qualified and accurate than MQLs and SQLs.


Because they’re not based on our opinions and common sense, we are not guessing if they’re interested in our product. We know it by looking at the different in-app metrics.

To identify PQLs, you’ll need to correctly understand your user’s behavior, user onboarding, and relevant in-app data.

Once you identify them – send accurate, personalized, and relevant emails that will engage with your trial/free users and help you to build relationships with them.

Also, as we could see – to successfully close PQL leads, this process requires excellent team management, since it involves a lot of different departments. But that’s a yet different topic.

After you have implemented PQLs into your sales funnel – you will close them more quickly than MQLs or SQLs.

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