Wed Dec 28

Data Driven PQLs

Data Driven PQLs are a new way to identify and qualify leads. They are based on the idea that you can use data to identify and qualify leads, rather than relying on intuition or guesswork.

Written by: Jonathan Haas

Data Driven PQLs

As an enterprise marketer, you know that one of the most important aspects of your job is generating high-quality leads that will eventually turn into paying customers. However, with the vast amount of data that is available today, it can be difficult to know where to start when it comes to creating a data-driven PQL (product qualified lead) scoring process.

Here are a few tips to get you started:

  1. Define what a PQL is for your business.

This may seem like a no-brainer, but it’s important to make sure that everyone on your team is on the same page when it comes to what constitutes a PQL. By having a clear definition, you’ll be able to create a more targeted and effective scoring process. For example, if you’re a B2B company, you may want to define a PQL as a lead that has a certain job title, a certain level of seniority, and a certain level of influence within their company. If you’re a B2C company, you may want to define a PQL as a lead that has a certain level of engagement with your brand, a certain level of engagement with your website, and a certain level of engagement with your social media channels. By defining what a PQL is for your business, you’ll be able to create a more targeted and effective scoring process.

  1. Collect data from a variety of sources.

In order to create an accurate score, you’ll need to collect data from a variety of sources. This includes everything from website analytics to customer surveys. By pulling data from multiple sources, you’ll be able to get a well-rounded picture of each lead. For example, if you’re a B2B company, you may want to collect data from your product analytics, your customer surveys, and your social media channels. If you’re a DTC company, you may want to collect data from your Shopify analytics, your customer surveys, and your social media channels. By collecting data from a variety of sources, you’ll be able to get a well-rounded picture of each lead.

  1. Use a weighting system to score leads.

One way to score leads is to use a weighting system. This means that you’ll assign a certain number of points to each piece of data that you collect. For example, if you collect data from a customer survey, you might assign a value of 5 points to each question. By assigning a value to each piece of data, you’ll be able to create a more accurate score. You can also use a weighting system to determine which data points are more important than others. Some data points may indicate that a lead is more likely to convert, while others may indicate that a lead is less likely to convert. By assigning a value to each piece of data, you’ll be able to create a more accurate score, and ultimately, a more accurate PQL.

  1. Centralize your data.

Once you’ve collected data from a variety of sources, you’ll need to centralize it. This means that you’ll need to create a single source of truth for all of your data. By centralizing your data, you’ll be able to ensure that all of your data is accurate and up-to-date. You’ll also be able to ensure that all of your data is being used in the most effective way possible. If you’re a B2B company, you’ll probably want to centralize your data in a data warehouse with an external reference to a CRM identity. We use Salesforce as our CRM, so we use a Salesforce identity as our external reference. If you’re a DTC company, you’ll probably want to centralize your data in a data warehouse with an external reference to a Shopify identity. Not every company has the resources to centralize their data, but it’s definitely something to consider. Doing so can minimize the amount of time that you spend on data collection and analysis, and it can also help you to create a more accurate PQL, because you’ll be certain that all of your data is accurate and up-to-date, allowing you to make more informed decisions about which leads to target.

Now that you have a better understanding of how to create a data-driven PQL scoring process, you can start to implement it in your business. If you’re interested in learning more about how to create a data-driven PQL scoring process, feel free to reach out to us at [email protected]. I’d love to help you get started!