Informing your team when users become product-qualified leads
Sound the alarm? Probably not. But PQLs are definitely worth sharing with your team—and in this playbook, we’ll go over some practical considerations and tips for automating your team’s PQL tracking.
What you’ll learn:
What the key components of identifying your product-qualified lead (PQL) are.
How to leverage user data to flag PQLs accurately.
Which strategies are needed to optimize team communication around PQL alerts.
What essentials to know for creating and implementing a robust automation system for PQL tracking.
Why it’s important to have a comprehensive testing and rollout strategy for your PQL automation.
What you’ll need:
A clear understanding of your product's aha moment and the user personas.
Access to user data and a data analytics platform (like Appcues, Mixpanel, or Heap Analytics).
Integration of your data platform with your CRM (like HubSpot, Salesforce) or automation tools like Zapier.
A team communication platform like Slack.
Alignment within your team regarding notification preferences.
Suggested playbooks to check out before starting this one:
5 steps to keep your team in the know of new PQLs:
Step 1: Define your product-qualified lead (PQL) criteria.
Establish a measure of product engagement that signals a user's readiness for a conversation.
Generally, users experiencing your product's aha moment are good PQL candidates.
You can elevate your PQL criteria by incorporating multiple product engagement factors.
Remember that PQL criteria can vary depending on your product, industry, and user behavior.
It's essential to revisit and adjust your PQL criteria as your product and user behavior evolve over time.
Step 2: Identify your product engagement data source.
Once you've set your PQL criteria, identify the data analytics platform that houses this information.
Tools like Appcues, Mixpanel, or Heap Analytics should have the necessary user data. Make sure these platforms integrate with your CRM—either natively or through tools like Zapier—which will be essential for step 4.
Make sure your data source is reliable and updated regularly to ensure accurate PQL identification.
Collaborate with your data team to ensure that you're leveraging all available data.
Step 3: Decide how your team wants to be notified about PQLs.
You could choose to send a Slack notification in a channel specifically designed for PQLs, or update a field in your CRM (like Salesforce).
Ensure alignment within your team on notification intake. Who gets them?
Decide on the frequency of these notifications. Should they be instant or compiled into a daily/weekly report?
Consider creating a backup notification system in case of any technical issues with the primary one.
Step 4: Set up an automation.
Once you have your product engagement data source, your PQL criteria, and your preferred notification method, you're ready to create an automation.
If you're using Appcues, you can natively integrate with HubSpot and Salesforce to update custom fields.
If you wish to send team notifications via Slack, you can use a tool like Zapier.
Make sure your automation is scalable. As your user base grows, you’ll want to ensure the system keeps up.
Include a system for tracking the automation's success and areas for improvement.
Step 5: Test and launch the automation.
Before going live, it's crucial to test your automation to ensure it works as expected. Check that the correct data is pulled, the notifications work, and the updates in your CRM are accurate.
Once confirmed, publish your automation and start benefiting from real-time PQL updates.
Remember to monitor the automation post-launch to identify any areas for improvement.
Plan for periodic reviews and updates to the automation based on your growing business needs and user behavior patterns.
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