{"id":46451,"date":"2019-09-19T15:57:50","date_gmt":"2019-09-19T10:27:50","guid":{"rendered":"https:\/\/vwo.com\/blog\/?p=46451"},"modified":"2025-05-01T12:40:54","modified_gmt":"2025-05-01T07:10:54","slug":"optimize-pqls-in-saas","status":"publish","type":"post","link":"https:\/\/vwo.com\/blog\/optimize-pqls-in-saas\/","title":{"rendered":"How SaaS Businesses Can Optimize for Product Qualified Leads in 4 Steps"},"content":{"rendered":"\n

The term Product Qualified Leads (PQLs) is not new\u2014It\u2019s been used by tech and SaaS companies for many years now. One of the first online mentions of PQLs was back in January 2013 by venture capitalist Tomasz Tunguz. Now the managing director at venture capital firm Redpoint, Tunguz defines PQLs as:<\/p>\n\n\n\n

Potential customers who have used a product and reached pre-defined triggers that signify a strong likelihood to become a paying customer.<\/em><\/p>\n\n\n\n

Download Free: Customer Engagement Guide<\/span><\/a><\/em><\/h2>\n\n\n\n

Since then, many thought leaders, tech and SaaS companies have introduced variations of the term in an effort to explain what PQLs are and why they are important<\/strong> for today\u2019s fast-growing companies. PQLs are different than Marketing Qualified Leads (MQLs) or Sales Qualified Leads (SQLs). One common misconception here is that PQLs are better than Marketing Qualified Leads (MQLs) and\/or Sales Qualified Leads (SQLs). <\/p>\n\n\n\n

They are different since they allow us to measure product growth. In this article, I\u2019ll be sharing with you a simple 4-step process to optimize for PQLs<\/strong> for your tech or SaaS company. If you\u2019re looking to build a product-led organization using PQLs as a way to measure product growth, this is the process you\u2019ll need to follow. <\/p>\n\n\n

Step 1: Define the Product Actions that Indicate Qualification<\/h2>\n\n\n

The PQL approach uses in-product insights to predict when a lead is ready to make a serious commitment, either after the trial or within a limited-time offer period. Unfortunately, a 2019 survey of more than 500 SaaS founders reports that only one in four companies currently track PQLs. <\/p>\n\n\n\n

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Image source: Openviewpartners<\/a><\/figcaption><\/figure>\n\n\n\n

By measuring PQLs, you can essentially identify the users who demonstrate buying behavior related to bottom-of-the-funnel actions, rather than middle-of-the-funnel ones. These actions or events show us that a) the user is experiencing value out of the product and b) the user is now ready to become a paying customer.<\/strong> Of course, as with MQLs and SQLs, PQLs are not the same for every company. <\/p>\n\n\n\n

According to the product engagement platform, Sherlock, success in terms of product qualification for a SaaS company is a combination of two things:<\/p>\n\n\n\n

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  1. Activation\u2014Is the account set up? Has the user reached the first meaningful outcome? <\/li>\n\n\n\n
  2. Engagement\u2014Is the user engaged during the free trial? What are the features they are using more often and what kind of actions are they taking? <\/li>\n<\/ol>\n\n\n\n

    This shows us that if we want to measure PQLs, it\u2019s imperative that we start defining both activation and product engagement criteria. These criteria (actions) indicate qualification<\/strong> and can help us identify PQLs for our organization. Let\u2019s put that into perspective with some examples from existing SaaS companies, some of which you may already know.  <\/p>\n\n\n

    Airtable\u00a0<\/h3>\n\n\n

    Airtable is a very cool and easy-to-use software for teams that need access to a database that works like a spreadsheet. What\u2019s more, teams can build their own spreadsheets within Airtable that can be used for various activities such as project management, campaign tracking, content marketing, and more. <\/p>\n\n\n\n

    \"Screenshot
    Image Source: Airtable<\/a><\/figcaption><\/figure>\n\n\n\n


    Airtable is a product-led company that uses a freemium model as a way to acquire customers. It also offers a variety of free templates that users can use and edit as a way to activate users more quickly. This also helps Airtable significantly reduce time-to-value<\/strong>, as users     experience value<\/a> from the product right away. <\/p>\n\n\n\n

    \"Screenshot
    Image Source: Airtable
    <\/figcaption><\/figure>\n\n\n\n

    The question is, how can Airtable define product qualification and identify the users that are more likely to become paying customers? In other words, how can Airtable know when a user is a PQL?<\/em> <\/p>\n\n\n\n

    For a company that offers a freemium model like Airtable, it could be something like the following: users who have created more than 5 Airtable bases (product terminology for databases) and invited more than 10 of their friends to join the tool are considered to be PQLs. <\/p>\n\n\n\n

    Author\u2019s Note:<\/strong> This is just an assumption for the sake of example, and has no relation to the actual metrics that indicate product qualification for Airtable. <\/p>\n\n\n\n

    To come up with these benchmarks for your product, you need to monitor user behavior before and after someone becomes a PQL. Put simply; you need to be able to find how measurable actions on a product level (i.e., create 5 Airtable bases) affect the likelihood of a user sticking with the product. And these actions have to be strictly related to the value someone gets from your product.  <\/p>\n\n\n

    Expensify<\/h3>\n\n\n

    Let\u2019s move on to the second example. Expensify is a receipt and expense management software tool. It follows a product-led approach and offers a free trial for each of its four pricing plans. <\/p>\n\n\n

    \n
    \"Screenshot

    Image source:     Expensify<\/a><\/figcaption><\/figure>\n<\/div>\n\n\n

    The learning curve here is short, and users can experience value within the product relatively quickly. What could indicate product qualification after someone has subscribed to one of Expensify\u2019s pricing plans? It has to be an action that\u2019s strictly connected to the value<\/strong> users get from the product. <\/p>\n\n\n\n

    For Expensify, it could be when someone sends more than five invoices within a month. If you think about it, the volume of invoices a user sends is directly correlated with the value the user gets from the tool. Thus, once again, the action(s) that indicate qualification is connected to the value that users experience within the tool. <\/p>\n\n\n\n

    The first step is to turn data into PQLs to take a look at the actions that indicate qualification. As you can see, these actions are different for every company.<\/strong> Your job is to find the actions that indicate both activation and product engagement for yours and qualify your leads<\/a> based on how users perform those actions. Let\u2019s move on to the second step.<\/p>\n\n\n

    Step 2: Segment Users Based on Product Engagement Scoring Using The Product-Led Growth Flywheel<\/h2>\n\n\n

    The Product-Led Growth Flywheel is a framework developed by Appcues<\/a>. It divides users into four main categories based on product engagement and usage criteria:<\/p>\n\n\n\n

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    1. Evaluators\u2014Users who are interested in some features of your product as a potential solution to a problem they have.<\/li>\n\n\n\n
    2. Beginners\u2014Users who understand how your product can help them and spend more time with it.<\/li>\n\n\n\n
    3. Regulars\u2014Users who are proficient with the core features of your product and now want to expand in other use cases.<\/li>\n\n\n\n
    4. Champions\u2014Users who have developed a strong relationship with your product and recommend it to other users.<\/li>\n<\/ol>\n\n\n
      \n
      \"Screenshot
      Image Source: Appcues<\/a>
      <\/figcaption><\/figure>\n<\/div>\n\n\n

      At this stage, you need to segment users based on the category they fall into. This segmentation\u2014as mentioned earlier\u2014should be based on actions that indicate product qualification,<\/strong> which is, in turn, is based on activation and engagement criteria. Let\u2019s see what this process looks like for an existing company. <\/p>\n\n\n

      SaaS<\/h3>\n\n\n

      Bonjoro is a SaaS company that helps companies across different industries convert users into customers using video. Bonjoro<\/a> managed to reduce its churn by 60% back in 2018 by focusing on PQLs. You may be wondering how it\u2019s possible to reduce churn by that much while focusing only on PQLs.<\/p>\n\n\n

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      \"Screenshot

      Image Source: Bonjoro<\/figcaption><\/figure>\n<\/div>\n\n\n

      After doing some research, Bonjoro understood that it should segment users based on the number of videos its user was creating on a weekly basis. Thus, it did so using the following five categories:<\/p>\n\n\n\n

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      1. Non-starter (< 5 per week)<\/li>\n\n\n\n
      2. Beginner (5 -10 per week)<\/li>\n\n\n\n
      3. Medium (10 -20 per week)<\/li>\n\n\n\n
      4. Heavy (20 – 50 per week)<\/li>\n\n\n\n
      5. Power User (50+ per week)<\/li>\n<\/ol>\n\n\n\n

        While the categories are not split into four as in The Product-led Growth Flywheel, the thought-process behind the segmentation is practically the same. The company segments users based on a value metric that indicates product qualification, making it easier for them to reach decisions on a product, marketing, sales, and even operations level.<\/p>\n\n\n\n

        Segmenting your users based on how they behave is essential to not only understand who are qualified to become paying customers,<\/strong> but also to be able to identify patterns and create strategies to increase free-to-trial conversion, reduce churn and improve product engagement. Now that you\u2019ve learned how to segment your users based on product engagement, let\u2019s move on to the next step.<\/p>\n\n\n\n

        Download Free: Customer Engagement Guide<\/span><\/a><\/em><\/h2>\n\n\n

        Step 3: Identify Patterns & Do Exploratory User Research<\/h2>\n\n\n

        Are there any patterns in your case that have emerged from the previous step? Have you managed to get closer to understanding your users<\/a>? How can you use these patterns to optimize your performance in various stages of the customer lifecycle? These are some of the questions you need to answer in the third step.<\/p>\n\n\n\n

        The segments you\u2019ve created in the previous step will tell you how engaged users are with your product, what features they are most interested in<\/strong> and mostly using, and also help in identifying patterns about the users themselves (i.e. what roles they have, how many years of experience they have or in what kind of companies they work for). <\/p>\n\n\n\n

        This process is not only important on a product level. It can also help you on a marketing and sales level. Let me give you an example. Let\u2019s assume you\u2019ve used the Product-Led Growth Flywheel to segment your users and come up with four categories of users:<\/p>\n\n\n\n