How Pendo Listen helps product design teams become more customer-centric

Published Feb 5, 2024
As designers, we’re inundated with constant streams of user feedback. And aligning them with our work can be a challenge.

I’m a product designer working on Pendo’s Session Replay product—where building with customer empathy has been at the forefront of every step of the process. But this is often complicated by the sheer volume of customer feedback we’re trying to leverage and  glean actionable insights from. 

But the good news is that our teams have been hard at work at a new product offering, Pendo Listen, that promises to change how teams use customer feedback to build their products. And I’ve been able to leverage it in my own work on Pendo Session Replay to transform the way I gather, triage, and analyze user feedback. Let’s take a closer look.

The issue with manually triaging customer feedback

Before Pendo Listen, I found myself searching for keywords in an overloaded spreadsheet of exported customer feedback data. Struggling to uncover themes and insights, bias would naturally enter into my process—clouding my understanding of how our users were actually experiencing the Session Replay product. 

Customer feedback is a treasure trove of valuable information, but the process of manually triaging the data is not only incredibly time-consuming—but also often results in  findings that only validate our previous assumptions, rather than teaching us something new. 

As our team sought to improve our product discovery processes and truly listen to the voice of the customer (VoC), Pendo Listen became a cornerstone of our discovery efforts—helping us unlock user sentiment and generate more impactful ideas to bring to market.

Using Pendo Listen for feature planning and development

Because Pendo Listen is part of the complete Pendo platform, our team has been able to leverage functionality like in-app guides to source real-time feedback from customers as we’ve been building the Session Replay product. And because we can port this information directly into Pendo Listen, we’re able to create one central repository for all of our feedback. Plus, the feedback is curated for Session Replay, showing me a focused-view of insights specifically for my product area, versus having to sift through every unique product’s feedback repository.

Once all of that feedback is centralized in the Pendo platform, Listen uses artificial intelligence (AI) to summarize and create themes from the data. We can then use these themes to group our feedback into product ideas. Streamlining this entire feedback management process has created a new, more direct path between receiving our users’ feedback and triaging it in a way that we can act on it.

There is immense power in this ability to combine quantitative, visual, and qualitative data. Each provides rich insight into how our users interact with our products. But combining them allows us to build even more customer empathy and deepen our understanding of how our users navigate—and what they need to be successful.

Moving from ideas to prioritization with Validate

Pendo Listen not only helped us to gather ideas as part of our product discovery, but was also key in facilitating the prioritization process through the use of Validate—a key component of Pendo Listen. 

Validate allows us to compare user-generated ideas against each other and quickly gather feedback and results—so we can hone in on the highest priority items to prototype, test, and build. After combining this feedback into ideas, we have the option to validate them using a variety of mechanisms. We can rank them by ARR, the number of customer votes they receive, or the number of accounts associated with them. We can also run “idea tests” to ask our customers to prioritize the ideas we believe are most important. This gives us additional insight by allowing us to target specific users based on the feedback they submitted, as well as their behaviors within the product. Ultimately, this leaves us with a clear front runner and a segment of users that have indicated they care deeply about a specific problem we’re looking to solve.

Here’s a specific example of how I used Pendo Listen this way, while in a design cycle for Pendo Session Replay.

A customer-centric way to design, build, and launch

I was exploring design options for the creation of the event log. Our users consistently mentioned the event log in in-app polls while watching replays, but we felt that other ideas were a higher priority. 

Knowing the context of their submissions and having an understanding of how often they use the product (thanks to all of the qualitative and quantitative data we collected in Pendo), we decided to add the event log to an idea test. Unbeknownst to us, the event log outperformed all the other ideas we were prioritizing against it. We were then able to use the segment of users provided to us by Pendo Listen to point us towards the replays we should watch, and who we should engage with in more focused user interviews. 

Pendo Listen’s ability to consolidate all of this qualitative and quantitative data proved indispensable when we were trying to find signals in the noise and better understand our users’ needs. And it’s improved all parts of our product design workflow. After launching the event log in Session Replay, we were able to go back to the initial segment of users who submitted feedback to alert them of the new feature launch, track their product usage to understand if they were engaging, and watch replays to understand if it was working for them as they had so desperately wanted. 


Pendo Listen continues to be a vital tool for us throughout the product lifecycle, enabling us to evaluate user feedback, determine what we need to build next with a customer-centric approach, and identify what needs to be reevaluated. And with its AI capabilities and streamlined feedback management, Pendo Listen ensures that we more easily stay connected with our user base—continuously refining and enhancing our product based on real user needs and experiences.

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