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Everyone knows user feedback is an essential component to building products customer love. But how do you turn qualitative user feedback into quantifiable and actionable data?
Product planning is a balancing act between: (1) product analytics—how your customers actually use the product and (2) user feedback—what your users tell you are their problems.
📈 Product Analytics—how your customers actually use the product.
📣 User Feedback—what your users tell you are their problems.
The key difference between the two is that product analytics is objective where as user feedback is subjective. Ultimately, answering questions quantitatively by looking at product analytics is a backbone of a data-driven team. However, while product analytics can answer a lot of what users do and don’t do, they can’t answer the why or why nots behind those user actions. The best way to understand the motivations behind those actions is by asking the user — by encouraging and nurturing user feedback. As we observed at many of these customer-oriented companies, when user feedback is an integral part of their engineering processes, it becomes the flywheel that empowers your team to pinpoint and solve the most important customer painpoints.
However, as mentioned earlier, because user feedback is subjective, biases can easily bleed in and disrupt good intentions even if you’re talking to lots of customers regularly. Here are how some of the biases that come into play:
Only the team members who talk directly to customers have a chance to shape what feedback is presented and reviewed. Often, these team members can inject their own bias. Sales teams will naturally bias towards opportunities to close new deals. Product managers tend to bias towards problems that align with a product vision.
When there is no systematic way of recording and analyzing user feedback, teams will get biased by recent remarks. If one gets the same feedback from multiple users in the same week, it may naturally heighten the priority/urgency of the ask. But it might dwarf in comparison to other requests that have consistently been made over a larger time period. Without a data driven approach, teams are highly susceptible to recency bias.
Every product team has a vision for the problem they are solving and how they are going to go about it. If asked, most teams can come up with a long roadmap. Without taking a data-driven approach, teams may become susceptible to gut feelings and/or selectively listening to customers whose feedback aligns with that vision.
It is important to weed out the aforementioned biases. Otherwise, the merits of talking to customers can easily be washed away, and may even lead your team down the wrong path. In this guide, we propose an end-to-end solution that allows your team to take a data-driven approach to user feedback, based on our learnings from customer-oriented companies like Brex, Notion, Gem, and Tandem.
Let us know if you have ideas to improve this guide — we are only an email away at email@example.com.