Title: Understanding User Feedback: Unraveling the “Too Expensive” Disconnect
In our recent analysis of user feedback, we encountered a recurring theme in our exit surveys: multiple users reported that our service was “too expensive.” At first glance, this feedback seemed unexpected, particularly given that our subscription is priced at $29 per month—a figure that typically wouldn’t deter users. Committed to understanding this trend better, we decided to investigate one user’s experience in depth.
Upon reaching out, the user promptly responded, revealing that their primary reason for cancellation was not the cost, but rather a perceived lack of utility from our service. This crucial insight prompted us to dive deeper into our data.
Utilizing our analytics tool, PostHog, we reviewed the user’s session recordings and discovered a concerning pattern: in their last few sessions, they had logged into the app, accessed the dashboard briefly, and exited without engaging with any features. This behavior had persisted for nearly a month prior to their cancellation.
Our inquiry didn’t stop there. We also sifted through our support email archives and unearthed two communications from this user. One was a query about the user interface that left them confused, while the other requested a specific feature. Although we had responded to both inquiries and closed the threads, we failed to follow up or track their ongoing engagement effectively.
Additionally, an analysis of their event data revealed a significant drop-off in usage of a certain feature that they had actively engaged with during the initial weeks of their subscription. This feature had been updated, and it appeared that the changes had affected its usability for this user, leading to their disengagement.
What became clear through this investigation was the fact that these insights were not hidden; they resided in disparate data points that we had not connected cohesively. The effort to manually compile this information for a single user was time-intensive and highlighted a major gap in our analysis approach—one that we recognized could not be sustained as we scale.
This experience raises critical questions for our organization and potentially resonates with other founders: Are we adequately synthesizing user feedback, behavioral data, and support interactions? Have we inadvertently overlooked patterns that could inform our product development and user engagement strategies?
In addressing these questions, it’s crucial to develop mechanisms that enable us to track these metrics holistically. By fostering a structured approach to user feedback and data analysis, we can better understand our users’ needs, enhance retention, and ultimately create a more valuable experience for our customers. Recognizing these blind spots is the first step toward improvement, and we are committed to enhancing our processes moving forward.
