How can you turn user feedback into actionable insights?
User feedback is a valuable source of information for product managers, but it can also be overwhelming and confusing. How can you make sense of the diverse opinions, suggestions, and complaints that you receive from your users? How can you turn user feedback into actionable insights that can guide your product decisions and improvements? In this article, we will share some practical tips and tools to help you collect, analyze, and prioritize user feedback effectively.
Before you start collecting user feedback, you need to have a clear idea of what you want to learn from it. What are the main questions or hypotheses that you want to test with your users? What are the key metrics or outcomes that you want to measure or improve with your feedback? Having specific and measurable feedback goals will help you choose the right methods, channels, and tools to collect user feedback, as well as filter out irrelevant or biased responses.
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Obviously having goals is essential, but we also want to ask open ended questions in case the feedback takes us in an unexpected direction. We always need to be open to being surprised.
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Transforming user feedback into actionable insights begins with clear objectives—what do we aim to achieve with this feedback? After collating feedback from diverse sources to minimize bias, the pivotal task is interpretation. It’s crucial to discern users' underlying needs, not just their expressed wants, echoing Ford's sentiment about “faster horses.” The challenge for a PM is to delve beneath the surface of user statements to extract genuine needs and desires. Analyzing this feedback meticulously, we can then translate these insights into tangible product enhancements, aligning user desires with feasible improvements.
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I know it can be hard to get good user feedback. (to collect feedback we use Grabee) You're trying to make a product that people will love, but how do you know if you're succeeding? I've been there: I've spent days on end gathering and reviewing feedback, only to find myself back at square one. But here's the thing: The solution is simple. You just need to know what your goals are. If your goal is just to gather as much feedback as possible, then great! You can do that but don't expect any results.
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A big issue in running any kind of customer discovery is failing to be clear on objectives before you start. It leads to: choosing the wrong methods, asking the wrong or less-effective questions, and ultimately leads to feedback you can't use. Always write a clear objective or at least an assumption you aim to test.
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When you understand that feedback means deepening your understanding of the problem space, and that correlates with better solutions, clearer execution and more likely to succeed it will be easy to invest in user discovery. The goal is usually simple: advance the understanding of the problem space. The sub goals should be adapted at what part within the problem space you need to close your gap of knowledge. Focus more on problem then solution.
User feedback can come from various sources, such as surveys, interviews, reviews, ratings, analytics, support tickets, social media, or user testing. Each source has its own advantages and limitations, so you should not rely on one source alone. Instead, you should collect feedback from multiple sources and compare and contrast the results. This will help you get a more comprehensive and balanced view of your users' needs, preferences, and pain points, as well as identify any gaps or inconsistencies in your feedback data.
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Diversity is positive in every angle, including the inputs and data points of your customer discovery. Seek first party and third party data. Seek face to face and remote interviews. Seek survey information and data queries. All help glue the story of the problem space. You should also adapt the investment in input based on the size of the problem and prospective solution. Not everything needs every type of input.
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Every user is different and prefers to provide feedback differently. Determining the feedback channel is immensely important. Depending on the channel, a product manager needs to have a gameplan ready - 1. Interviewing the user? Have a script ready to run through. 2. Getting feedback over written text? Make sure that everyone is on the same page, and the communication is succinct. 3. Using telemetry? Queries and analytics should be unbiased, accurate and expansive. 4. Looking at reviews? Verify if the user feedback correlates with the right product/feature. Follow up if more information is needed. There are many pitfalls of different feedback channels, but it is necessary to cover the breadth of these channels for holistic feedback.
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You don't have to rely on just one type of data for your feedback you can incorporate surveys, analytics, customer support interactions, and more so you can build up a full picture of what's going on with your customers. But don't stop there! The best way to turn those insights into actionable insights is to combine them with contextual information (like where the user lives, and how long they've been using your app or website) so you understand how specific segments of users may respond differently than others when faced with certain types of situations or problems requiring solutions and then use this understanding to craft better solutions for everyone at once so they'll all be happier customers in the end!
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"Triangulation" - the process of comparing observations from multiple sources - is the best way to check your assumptions and make sure that, for example, what you heard in interviews is mirrored in another feedback source. Triangulating helps build confidence that a pattern exists at enough scale that it's worth focusing on.
User feedback can be either qualitative or quantitative, depending on the type and format of the data. Qualitative feedback is more descriptive and subjective, such as comments, stories, or emotions. Quantitative feedback is more numerical and objective, such as ratings, scores, or statistics. Both types of feedback are important and complementary, but they require different methods of analysis. Qualitative feedback can be analyzed with methods such as thematic analysis, sentiment analysis, or affinity diagramming, which help you identify patterns, themes, or trends in your feedback data. Quantitative feedback can be analyzed with methods such as descriptive statistics, correlation analysis, or regression analysis, which help you measure, compare, or predict the impact of your feedback data on your metrics or outcomes.
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In early stage, new products, zero to one, or B2B always choose qualitative data. You want to understand what is in between the lines. Facial expressions, pauses, digressions are way more valuable than summarized data points. If you’re focusing on B2C, late stage product or multi markets, run quantitive as the limited sample might bias your decisions.
User feedback can be overwhelming and conflicting, especially when you have a large amount of data or a diverse user base. How can you decide which feedback to act on and which to ignore or postpone? How can you align your feedback priorities with your product goals and resources? To answer these questions, you need a framework or a tool to help you prioritize your feedback effectively. A common framework is the RICE framework, which stands for Reach, Impact, Confidence, and Effort. This framework helps you score and rank your feedback based on how many users it affects, how much it improves their satisfaction or retention, how confident you are in your estimates, and how much time or money it costs to implement. A common tool is the feedback matrix, which helps you categorize your feedback based on its importance and urgency. This tool helps you decide which feedback to do now, later, delegate, or eliminate.
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This can be great in a collaborative workshop style setting too. Using a 2 X 2 you can work with your team to prioritise your feedback.
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A simple way to go about this is using the STAR framework. What are the Situations? Identify and being your chain of thought (constructive feedback identifying painpoints being the situation) What is the Task at hand !? What tasks can I pursue keeping the vision and business acumen in mind which can help alleviate the situation? What are the Action items? Break the tasks into action items that can be prioritized, delegated and closed. What is the Result? Monitor closely what results you want to achieve , what the actual results are , the deviation from expectancy and how you can better prioritise / improve your task identification process
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One thing that I would add here is making sure you understand your Ideal Client. You will always want to prioritize the feedback of someone who fits your target profile higher than someone who might be an outlier or an occasional user.
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We're using Grabee, a tool for prioritizing user feedback so we can act on it quickly and easily without having to worry about what to do next or where to start. I know that dealing with user feedback can sometimes feel overwhelming because there's just so much of it and it's coming at you from all sides! That's why we started using Grabee: so we could spend less time sifting through data and more time focusing on what matters most: making sure our product is meeting the needs of our users.
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There are many tools that can guide your process to gather feedback. More than frameworks, follow what experts in the field do. Often the tool you choose will have expert content on better gathering information. If not, start simple: understand principles of talking with users (The mom test is a great reading here) and apply common sense. Use your mouth and ears proportionally (listen twice as much as you talk)
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Successfully finding insights that you can act on starts at the beginning, before running customer discovery, and involves having clear "checks" along the way. If you're running continuous discovery, for example, you'll want to take time after each user sessions to check - did we get answers that addressed our main objective or assumption? At the end of a round of user sessions, ask yourself the same question. Then, during and after analysis, at least applying frameworks to check (1) how much evidence supports an insight and (2) how strong the signal was from users can help make sure you focus on the right insights of the pile to start building on.
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• Profile and segment your users • Collect qualitative data via surveys, interviews. • Group feedback based on similarities and analyze it for understanding the root causes. • At the same time check your quantitative data analytics for deeper insights. • Finally, prioritize based on frequency and impact but always having in mind your product goals.
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