Product Qualified Leads

A product qualified lead (PQL) is a customer who uses your product as a free trial or freemium user.

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SaaS KPI Example - Product Qualified Leads Metric

In today's competitive business landscape, generating high-quality leads is crucial for a company’s growth and success. Traditional lead generation methods often focus on quantity over quality, resulting in wasted time and resources on unqualified prospects. 

However, approaching product qualified leads (PQL) makes up for the shortcomings of traditional lead generation methods.

PQLs are potential customers who have already experienced a product or service, like a free trial, and have demonstrated a genuine interest in its value and potential. 

In this article, we’ll delve into the world of PQLs, their importance, and how to identify them to help you find these customers and inspire them to improve your services.

What Is a Product Qualified Lead?

A product qualified lead (PQL) is a customer who uses your product as a free trial or freemium user. They already know what you offer and engage with the product, making them more likely to become paying subscribers.

Unlike other types of leads, such as Marketing Qualified Leads (MQLs) or Sales Qualified Leads (SQLs), PQLs are identified and qualified based on their product interactions rather than solely on marketing or sales activities.

It’s easier to transition an existing user into a paying customer because they know what your product offers and its value and already understand how to use it. You don’t need to spend time explaining the product or interface to the user because they have experience.

This position means you can instead focus on showing the customer why the paid option is even better than the free product they already use. They have a value baseline and know what they’re willing to pay. Add a limited discount, and convincing them to subscribe is relatively straightforward.

How To Identify Product Qualified Leads

To improve your lead quality, it's essential to identify those users who are most likely to convert to paying customers. 

Why Not All Users Are PQLs

First, it’s important to note that not all current free trial or freemium users are PQLs. While many might be intrigued by the free offering, it doesn't necessarily equate to a commitment to buy. For instance, some users sign up for a free trial and either never engage with the service or cancel it as soon as the trial ends. Targeting these users for conversion would be a futile effort.

Defining Your Target Client Description

For a free user to be a PQL, they must meet your target client description. Someone outside of your ideal demographic may use the free product but will never pay for it. 

A target client description is essentially a profile of your ideal customer. While it's tempting to think everyone could be a potential customer, the reality is different. 

These criteria examples can help you narrow down the list of potential leads:

  • The industry they operate in

  • Their location

  • The size of their business

For example, a small business owner in the tech industry might have different needs than a large corporation in the retail sector. Understanding your target demographic makes you better equipped to tailor your offerings and marketing messages to them.

Reading the Signs of a Potential PQL

User actions often offer insights into their intent. Potential PQLs often exhibit behaviors that differentiate them from casual users. For instance:

  • Engagement Levels: Regular logins and usage suggest genuine interest. A user who accesses the freemium version daily might be exploring its features in-depth and understanding its value.

  • Collaborative Features: Creating a team or inviting others to use the product might indicate that they see potential for broader application within their organization.

  • Price Page Visits: Spending significant time on the pricing page or engaging with your chatbot to inquire about features and benefits can be a clear sign of purchase intent.

Utilizing Data for Insights on Products

While direct interaction might be minimal with SaaS users, the digital footprints they leave behind can offer a wealth of information. Contrary to what one might think, this lack of direct engagement isn't detrimental. 

The data accrued from their actions can be pieced together to compile a comprehensive picture of user behaviors, preferences, and needs. This, in turn, can guide targeted marketing and engagement strategies.

Harnessing Technology for Deeper User Insights

With advancements in technology, several tools can help businesses dive deeper into user analytics. Using AI-driven tools or advanced CRM systems can help track and analyze user data, allowing businesses to predict user needs and potential churn risks and even identify upselling opportunities.

Three Types of SaaS Lead Data

Three types of SaaS lead data help you see the big picture of your users, such as explicit data, implicit data, and behavioral data. 

Explicit Data

Explicit data is information the customer gives you when they sign up to use the product. This information may only include their name and email address for a free trial. However, you may want to ask for more information to understand how people use the program.

For example, you may want to know their industry, business size, and expected usage. This data can help you understand if a company needs help with payroll and customer management, how likely they are to buy a team license, and how often they’ll use the platform.

You don’t have to ask these questions upfront. Some people will try a freemium product if there’s a low barrier to access. Giving anything beyond their name and email might make them leave the page. 

In that case, you should have the questionnaire ready after they engage with the product a few times. You can install a widget with a survey pop-up in the browser after they've used your product a certain number of times or for a specific duration. 

They know more about what they'll get from the service and are more likely to answer the questions.

Implicit Data

Implicit data is information you learn from behind the scenes. You can see how many times they’ve logged into the program and how long they work with it daily. You can see if one user accesses the account or multiple computers log in. This data helps you understand the business and how they use your product.

Using implicit data gives you a foundation for your upsell pitch. You don’t have to guess why the customer needs your service because you already know how often they use it and why. 

You can reach out to them with solutions instead of needing to ask them more questions and risk losing them in the process.

Behavioral Data

Combining explicit and implicit data gives you a detailed visual of your customer. However, behavioral data can provide you even more information to reach them where they are.

Behavioral data shows you how the user engages with the platform. It may include page views, interactions with the chatbot, e-commerce transactions, video plays, and downloads.

Tracking behavioral data can help give your users more of what they interact with most. It gives you an idea of the user experience to streamline the process and retain your customers. 

You get all this information without needing them to complete surveys, so it’s a win-win for everyone involved.

By using behavioral data, especially combined with explicit and implicit information, you can market directly to current users and give them what they want, streamlining the marketing approach to make it more effective and cost-efficient.

Why Are Product Qualified Leads Important?

PQLs are important because they help you increase revenue without spending more of the budget on marketing and customer acquisition. You can use general marketing campaigns to pull in users without worrying about pinpointing your ideal demographic. 

Once they try the software, the people who can benefit most from the program are more likely to subscribe.

Eliminate Customer Acquisition Concerns

Software used to require extensive demos to acquire new customers. But today, SaaS has made offering free trials or freemium accounts easier for customers to explore the product independently. 

They have the time to decide if the software meets their needs and can learn how to use the dashboard with experience instead of seeing a demo.

This new model involving PQLs eliminates the need for a lot of marketing, making SaaS more self-service than ever before. 

You’ll have initial marketing fees to promote the product in more general methods. Then, you can allow customers to create freemium accounts or start free trials and upsell themselves after they engage with the program.

Overcome Common Challenges

Without PQL data, acquiring new customers means you'd have to start from scratch. You'd already have users with free trials and freemium accounts but wouldn't know how to leverage them into paying customers. Therefore, you'd have to return to marketing campaigns to attract new users and encourage them to pay for a subscription.

This approach would require a lot of extra time and marketing efforts, so you'd spend more than you make by bringing in new users.

However, using PQL data shows salespeople what customers already use the product so they can focus their marketing efforts on a smaller population. They can put in less work to transition those users into paying customers because they already use the service and need less convincing.

It’s also possible to use PQL data to upsell current customers, especially if your service has options for multiple users and teams or packages with more advanced features.

Instead of starting from scratch, the company uses existing information on current users to increase revenue without spending more on the process. This approach can help the business grow exponentially.

How To Leverage Product Qualified Leads

PQLs represent a unique segment of users who are primed for conversion. Harnessing the power of this data effectively requires a cross-departmental approach. Here's how you can do just that:

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Understanding the Multi-Faceted Value of PQL Data

Recognizing that PQL data is not just a single data point but a treasure trove of insights is essential. This data helps pinpoint potential paying customers and can guide strategy across multiple departments, ensuring a cohesive growth plan.

Leveraging Marketing for Attraction and Engagement

The marketing department plays a pivotal role in the initial stages of the PQL journey:

  • Targeted Outreach: Armed with the understanding of what defines a PQL, marketing teams can devise campaigns specifically designed to attract users fitting the PQL profile. This could involve targeted advertising, content strategies, or even partnerships.

  • Freemium and Trial Engagements: To convert free users to PQLs, the marketing team can launch engagement campaigns. These involve sending educational content, hosting webinars, or offering tutorial sessions, making sure users extract maximum value during their trial/freemium period.

Capturing Conversions through Sales

Once a user is identified as a PQL, the sales team steps into the limelight:

  • Personalized Outreach: Using the PQL data, sales teams can craft personalized outreach strategies. This might involve sending tailored proposals or offers that resonate with the specific needs and behaviors exhibited by the PQL.

  • Upselling and Cross-Selling: Beyond converting them into paying subscribers, there's potential for upselling or cross-selling additional features, services, or products that align with their needs.

Retaining Buyers with Customer Service

Keeping PQLs and converted customers satisfied with quick and effective support ensures that any issues PQLs or customers face are addressed promptly. As such, it increases their likelihood of converting or staying loyal. Additionally, keeping users in the loop regarding product updates, new features, or any other changes enhances trust and showcases continuous value.

Maximizing Product Development and Launch Cycles

You must have a feedback loop every time you launch a new product or feature. PQL data can be invaluable to product teams, offering insights into user preferences, potential feature requests, and areas of improvement.

Moreover, ensure that PQLs and existing customers are aware of new releases. This can lead to account upgrades or expanded usage.

Collaborating Across Departments for Scalable Growth

The power of PQL data is amplified when all teams collaborate. Regular cross-departmental meetings, shared dashboards, and aligned strategies ensure the entire organization is moving in harmony, leveraging the insights from PQL data for maximum growth.

Measuring the Product Qualified Lead Rate

The PQL rate provides valuable insight into the efficiency of your product in converting trial users or free users into paying customers. 

Understanding the Importance of PQL Rate

The PQL rate isn't just another SaaS metric. It's a window into the effectiveness of your product and the experience it provides during a trial or freemium phase.

A higher PQL rate suggests that users are finding real value in your offering and are more likely to convert. On the other hand, a low PQL rate can indicate potential bottlenecks or friction points that may need attention.

How to Calculate the PQL Rate

This is the formula for computing the PQL Rate: 

PQL Rate = (Number of PQLs / Total New Registrations) × 100

For instance, if you had 100 new signups in a month, and 20 of them became PQLs, your PQL rate would be 20%.

Diving Deeper into the Metric

While the base calculation is simple, there are more layers to consider:

  • Segmented Analysis: Different user segments may have varying PQL rates. For instance, users from a particular source (like a specific marketing campaign) might convert to PQLs at a higher rate. Segmenting the analysis can offer more granular insights.

  • Time-based Analysis: Tracking how the PQL rate changes over time can provide insights into the impact of product updates, marketing campaigns, or other strategic initiatives. For example, a surge in the PQL rate after a feature update can suggest that the new feature is resonating with users.
    Comparing with Industry Benchmarks: It's beneficial to know where you stand in relation to competitors or industry standards. If your PQL rate is significantly lower than the industry average, it might indicate a need for improvement.

Taking Action Based on PQL Rate Insights

Armed with insights from the PQL rate, teams can undertake actionable steps:

  • Optimizing Onboarding: If the PQL rate is lower than expected, it may be worth revisiting the onboarding process. Simplifying steps, providing clearer instructions, or offering guided tutorials can make a difference.

  • Enhancing Product Features: Listening to user feedback can identify which features or elements of the product resonate most with PQLs. Enhancing or promoting these can elevate the PQL rate.

  • Tailored Marketing Initiatives: Tailoring marketing campaigns based on what drives higher PQL rates can lead to better overall conversion. This might involve highlighting specific product features or offering specialized promotions.

Creating a Product Qualified Lead Process

If your company doesn’t have a PQL process, you can take three quick steps to initiate it.

Find Your Target Client

First, you need to think about your target client. What service does your product provide? Who uses it? What do they need from SaaS to streamline their workflow?

Your target client may be small businesses that need a payroll program. It may focus on client management, with distinct tiers based on company size. 

You may need to create multiple examples of your target client in many cases. Your pitch to a small business will differ from your approach to a larger corporation.

With this information, you'll know what businesses you can approach. You'll already know the solutions to their major issues and can present them in a way that shows the target client that you know what you're doing. 

The more you customize the target client profiles, the more likely you'll win them over by presenting the perfect solution to their pain points.

Focus on the Product Activated Lead

You can set a product activated lead based on specific criteria. 

For example, a user may reach an activation point after they use the service for the seven-day free trial or log in a certain number of times. You may think they're a product activated lead by the time they try to interact with features only available in the paid version of the program.

Having a product activated lead helps you know when to reach out to the customer to upsell them into a subscription. It helps keep your sales and marketing teams organized because they won't approach people before they can see what you have to offer. 

Being too heavy-handed with your pitch can turn off potential customers, so having a specific metric as your product activated lead keeps things running smoothly.

Use Both to Find Product Qualified Leads

When you combine your target clients with the product activated lead, your SaaS should sell itself. 

You know it offers what the user needs to run their business efficiently, and they've already interacted with the program enough to understand how it works. They're hooked, and you can now help them become a paid subscriber.

Using both metrics cuts down on the work of your sales and marketing teams because the legwork is already complete. However, they’ll still need to make some effort to complete the sale unless you choose to automate the PQL process.

How To Automate the Product Qualified Lead Process

Many customer relationship management (CRM) platforms automate the PQL process by tracking certain user data points, like activity usage. 

However, it’s a basic platform that might require customization. You might need to add specific tags and commands to ensure it combs the users and pulls the relevant data.

Moreover, the evolving nature of SaaS businesses means user behaviors and indicators of purchasing intent might shift over time. As such, even if your CRM captures relevant data today, it might miss crucial information tomorrow. Regular reviews and updates to the parameters and tags you've set up will be necessary to ensure you're capturing the most relevant leads.

Furthermore, as businesses scale, the sheer volume of data can become overwhelming. Relying solely on a basic automated process could mean missing out on valuable insights or misidentifying potential PQLs. 

This is where dedicated PQL automation tools come into play. These tools are designed to streamline identifying and managing product qualified leads. Their algorithms, integration capabilities, and user-friendly dashboards offer a level of specificity and precision that general CRM platforms might lack.

Since the automated process is pretty basic, you should upgrade to dedicated PQL automation tools. Many options integrate with your CRM to pull from your existing data and simplify the process. Depending on your business's budget, it will take away some of your employees' work, so it may be worth the investment.

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Your Guide to Premium Subscriptions

PQLs aren't the most common metric for SaaS, but they can significantly benefit your business if you use them properly. Learning to leverage the data and appeal to your current users reduces the marketing budget and substantially increases paying customers.

Since PQL data shows how much users interact with the product, you know when to approach them about becoming subscribers. You're letting your product sell itself by giving users a self-service option. They explore the platform and learn how the service can simplify their workflow, making them more likely to subscribe to a product they already use.

Use the data points outlined above to create a PQL process for your SaaS and see how easy it is to convert current free trial and freemium users into paying customers.

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