The Definitive Guide to Product-Qualified Leads (PQLs)

By classifying your PQLs into one of these four categories, you can see where each user is in the sales cycle to accelerate product adoption.

How to Score Product-Qualified Leads

Since every company has a unique product, the actions users take in your product will be drastically different. So, figuring out what key metrics directly correlate to a higher user adoption rate is extremely important.

For example, a communications company like Slack is based on active workspaces. The easiest way to measure this is through metrics like messages sent, active users, invites, number of channels, etc. On the other hand, a company like Grammarly helps users improve their writing, tracks activation progress through key metrics like words typed, spelling errors, words checked, writing style, etc.

Here at Hightouch, we define a product-qualified lead as anyone using more than one of our integrations because this means they are exceeding our freemium product. However, if we want to get more granular with our definitions, we can look at workspaces, syncs, monthly queried rows, etc.

You first need to pick your core metric when identifying precisely what core metrics you want to measure in your PQL definition. For a streaming platform like Netflix, that might be hours consumed. For a SaaS business like Grammarly, it could be something as simple as words typed. Either way, you need to analyze key metrics like:

• Total users
• Product usage
• Most popular features
• Product interest
• Adoption rate
• Spending habits

You should also try and ask the following questions:

• What do your most active customers have in common?
• What key features do your existing customers use the most?
• What is your ideal customer profile?
• When does product usage begin increasing?
• What causes product usage to decrease?
• What is the most used feature in your free tier?
• At what stage do your free-tier customers look to upgrade?
• What is your activation definition?

Building Your PQL Score

Building your PQL definition is very similar to any other type of lead scoring because you need to assign positive and negative values to specific product usage data that you want to measure. For example, if you know that all new users who create a workspace within 30 days of signing up have a 30% chance of becoming a paying customer, you could award 30 points to users with those attributes. Conversely, you could deduct ten points from users who haven't signed into your app within the last week. Typically your scoring system should be based on a scale of 1-10 or 0-100, but ultimately the scale you choose to implement doesn't matter.

In most cases, all of the data to build your PQL definition already lives in your warehouse, which means you need your data team to create a PQL model. The first step to building your model is simply defining all the actions a user can take in your product and assigning values. From there, you'll need to write some SQL logic. Lucky for you, we already created a guide with some SQL to help you get started.

When Does a User Become a PQL?

The moment someone signs up for your product, you should classify that user as a PQL. However, just because someone has met your initial PQL criteria does not mean you should start targeting them from a sales perspective. Not all product-qualified leads are equal. There's a big difference between a new user and someone actively leveraging your product. The ultimate goal of your PQL definition should be to drive product adoption and feature usage.

Implementing PQLs

A PQL definition is useless if it just lives in your warehouse. Your business teams want and need access to this data in their native SaaS tools.

• Your support team wants to know when a customer runs into a bug in your app.
• Your sales reps want to know when company X signed up so they can book a demo.
• Your marketing team wants to build a drip campaign with relevant content to reengage certain users.
• Your product team wants to know which features are being most heavily used so they can optimize the user experience and accelerate feature adoption.

In the past, syncing data from your warehouse to your downstream SaaS tools was challenging because it required you to integrate with third-party APIs and build and maintain custom data pipelines for every tool in your technology stack.

Hightouch eliminates this problem by querying directly against your warehouse and syncing your data to 125+ destinations like Salesforce, Hubspot, Braze, Iterable, etc. With Hightouch, you can map the columns in your warehouse to the appropriate fields in your end destination, whether that's syncing a PQL score or actual product usage data (e.g., last login date.) There's even a visual audience builder for your non-technical users so you can create cohorts of users with the parameters your data team has set in place.

Benefits of PQLs

Product-qualified leads provide many benefits because they allow you to see how users interact with your product and enable you to act on that information in real-time. With PQLs and product usage data at their fingertips, your business teams can leverage real insights in their decision-making and use them to drive meaningful value for your customers.

In addition to streamlining and optimizing your business processes and workflows, PQLs also provide enormous benefits over traditional leads because they represent your ideal customer profile (ICP.) PQLs are more likely to convert into paying customers and less likely to churn after adopting your product. They also have shorter sales, lower customer acquisition costs (CAC), and higher annual contract value (ACV). Ultimately, PQLs represent the single highest intent leads you can generate for your business and they often turn into your most valuable customers.

If you’re not tracking PQLs today, you’re missing out on valuable product analytics data that you could be leveraging to optimize your customer experiences, increase your conversion rates, and drive more revenue.