How to be a data-driven internal product manager

Published May 16, 2024

When you think of a product manager, you likely think of someone who builds and manages software products for external customers and end users. Increasingly, though, companies are turning to product managers to conceptualize and optimize digital tools for internal users: their employees.

Internal product management is all about building solutions that improve business processes, increase efficiency, and contribute to the overall effectiveness of the organization. And while the role of an internal product manager (PM) has some unique differences from an external PM, one area where they don’t differ is the importance of data.

Why internal product managers should leverage data

Today, you’d be hard-pressed to find a product manager who doesn’t believe in the importance of collecting and analyzing product data. The reality is simple: The PMs who can get the best product data and glean the most insights about their users are the ones who will gain a competitive advantage. 

This notion has an equally impactful application for employee-facing software: The internal PMs who can get the best product data and glean the most insights about their users are the ones who will more effectively increase internal efficiency and drive business success.

Let’s go over five ways internal product managers can utilize product analytics data to make better, data-driven decisions.

1. Understand how employees use the product

One of the most important ways internal product managers should use product analytics data is to see how employees are engaging with the product or products they manage. This helps you uncover areas of the product that need improvement—and better understand if employees are getting maximum value from it.

You might first see which features employees use the most, or whether users are engaging with key areas of the product. It’s also helpful to leverage Paths and Funnels. Paths help you discover what users are doing before or after using a specific page or feature, and Funnels allow you to measure how users move through a defined series of steps that you want them to follow. 

For example, if you’re responsible for an internal learning management system, you might use a Funnel to see what percentage of employees get all the way through the steps of registering for a new training course.

2. Inform what to build

The second way internal product managers can use data is to inform what to build. When you have access to product analytics data, you can prioritize internal product improvements based on what employees actually use—and value—the most. 

For example, you might not realize that a feature is crucial to a certain workflow until you see that the majority of employees access the feature every week. This insight might help you prioritize optimizing that feature instead of putting resources into building something new.

3. Measure adoption of new functionality

The best product teams—including those who work on internal apps—know that what they deliver is only as valuable as what’s actually used by their users. 

After releasing a new product or feature, product analytics data provides direct insight into whether or not employees are actually using what you built. If your product serves multiple teams across the business, it’s helpful to use segmentation to drill into feature adoption for different groups, for example the sales team versus the marketing team.

4. Identify features to sunset

Product teams often focus on effectively launching and driving adoption of new features. But sometimes, the most strategic (and cost-effective) move is to actually remove a feature from the UI.

As you dig into overall adoption data for your internal product, take note of any pages or features that have low or no activity over a period of time—like 30 to 90 days—as these may be good candidates for a potential sunset

It’s also important to remember, though, that low usage levels might be a sign of discoverability and usability problems, not necessarily that employees no longer find the functionality valuable. Try to determine the reasons for low usage before flagging a feature to be removed, and even consider asking employees directly if—or why—they find the particular feature valuable.

5. Add context to employee feedback

If a particular feature is the subject of a lot of employees’ feedback, product analytics data can help paint a clearer picture of how employees actually engage with the feature in question. Examine how many users actually utilize the feature, and see if you can identify any shared characteristics among those users. This will help you determine whether or not you should prioritize taking action on the feedback in question.

Want to dig deeper into internal product management best practices? Take Pendo and Mind the Product’s free Digital Adoption Certification Course.