How do you use data and analytics to support or challenge user feedback?
User feedback is essential for product managers to understand the needs, preferences, and pain points of their customers. However, not all feedback is equally valid, reliable, or actionable. How do you use data and analytics to support or challenge user feedback? In this article, we will share some tips and best practices for validating user feedback and making data-driven decisions.
Before you collect and analyze user feedback, you need to have a clear idea of what you want to achieve and how you will measure it. What are the key outcomes and indicators of success for your product? How do they align with your business objectives and user needs? Define your goals and metrics upfront and communicate them to your team and stakeholders. This will help you focus on the most relevant and meaningful feedback and avoid getting distracted by irrelevant or conflicting opinions.
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To define goals and metrics for a product, understanding the current state and user pain points is crucial. Depending on where your product is in its lifecycle, it may be challenging to identify all the user pain points, making goal-setting difficult. Generative user research helps identify user pain points in a product's lifecycle, leading to new ideas and concepts by exploring user behavior and motivations. Narrow down on a product area to improve to define key outcomes and indicators of success. Leverage validation testing to confirm assumptions and test and validate hypotheses.
User feedback can come from various sources, such as surveys, interviews, reviews, ratings, social media, support tickets, and user testing. Each source has its own advantages and limitations, and may provide different insights and perspectives. To get a comprehensive and balanced view of user feedback, you should collect and compare feedback from multiple sources and methods. This will help you identify patterns, trends, and gaps in user feedback and avoid relying on a single or biased source.
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Collecting user feedback from multiple sources can provide a comprehensive and nuanced understanding of user needs and pain points. It provides diverse perspectives, helps identify trends and patterns, identifies new user segments, new areas of improvements that may be outside the product. It can help verify assumptions and help assess improvements made. However, collecting and analyzing feedback from various sources can be time-consuming and resource-intensive. Sometimes feedback can be conflicting or won't represent your target user base. So it's important to deep dive on the feedback you get by identifying key themes, patterns, and trends. Use that feedback to further engage with users to gather additional context and insights.
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As a former corporate librarian, I agree that collecting feedback from multiple sources is essential. Choosing the official or appropriate source for the information you are using is as important as the feedback. As a language model, I've learned that relying on a single source of information can lead to incomplete or biased perspectives. The same applies to user feedback, where multiple methods can comprehensively understand users' needs and expectations. By collecting and comparing feedback from various sources, businesses can gain valuable insights that can help improve their products or services and ultimately enhance user satisfaction.
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Analyzing all qualitative feedback sources as opposed to just a sample is important for the most accurate insights. Feedback analytics platforms like Rargus provide a shared understanding of customer needs by triangulating feedback from all sources to provide actionable insights, taking into account a holistic view. This enables teams to grasp customers' needs, expectations, and preferences which leads to better performance against metrics like NPS, CSAT, while boosting growth and retention.
User feedback is not always accurate, consistent, or representative of your entire user base. Sometimes, users may not be able to articulate their needs or preferences, or they may have unrealistic or conflicting expectations. To validate user feedback, you need to use data and analytics to verify, quantify, and contextualize it. Data and analytics can help you answer questions such as: How many users share the same feedback? How does the feedback affect user behavior and satisfaction? How does the feedback relate to your goals and metrics? How does the feedback vary across different segments, channels, or scenarios?
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Basing your product decisions solely on data and analytics works perfectly when your underlying data is perfect. However, in reality, no set of customer or user data is ever a perfect reflection of the user experience. Therefore, we often have the best experience when using feedback to explain and validate the analytics. If you see that customer retention is low, the feedback can help explain why customers are dropping off. Ultimately, your business goal might be to improve customer retention (not to improve *customer feedback*), but the feedback can inform the strategies for how you accomplish that.
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Eric Malnati
Results-Oriented SaaS Account Executive | 5 Years of Experience Driving Revenue Growth
(edited)Feedback analytics platforms provide a way to effortlessly consolidate, analyze and leverage mass amounts of qualitative customer feedback from any source, at scale. For example, incorporating insights from feedback analytics platforms like Rargus while designing user interviews results in much more effective user research results. Your existing qualitative feedback can be used first to guide the interview process and establish an understanding of which information will be most impactful to collect. AI-powered feedback analytics platforms provide insights based on all feedback from all sources, facilitating an accurate, holistic understanding of the customer's voice.
User feedback can provide you with many ideas and suggestions for improving your product, but you cannot implement them all at once. You need to prioritize feedback based on the impact and effort required to address it. Impact refers to the potential value and benefit of the feedback for your users and your business. Effort refers to the time, cost, and resources needed to implement the feedback. You can use a simple matrix or framework to rank feedback according to these criteria and decide which feedback to act on first, later, or never.
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As you gather ideas and suggestions, it's critical to have an objective way to determine what will be implemented and when. The RICE method, the kano model, and a MoSCoW analysis are ways to ground implementation decisions in objectivity and focus on the value for customers. Do all ideas that add value need to be implemented? Possibly. Do they all need to be implemented now? Probably not. Using a framework helps to determine the sequencing.
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Let's leverage the Pareto Principle (80/20 rule) to focus our efforts. This principle suggests that a majority of results (80%) stem from a minority of causes (20%). Here's the plan: Analyze user feedback to identify the top 20% of issues causing the most problems. Develop a strategic effort to address those core issues. By focusing on these high-impact areas, we can significantly improve the overall user experience. This approach ensures we're tackling the root causes that drive the most negative feedback, leading to lasting improvements.
User feedback is not a one-time event, but an ongoing process. You need to test and iterate on feedback to validate your assumptions, measure your results, and learn from your experiments. Testing and iterating on feedback can help you avoid wasting time and resources on ineffective or harmful changes, and optimize your product for better user experience and performance. You can use various methods and tools to test and iterate on feedback, such as A/B testing, prototyping, usability testing, and analytics dashboards.
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Regularly testing and iterating on feedback allows you to validate your assumptions and make data-driven decisions that lead to improved user experience and better performance. It's important to avoid making assumptions about what your users want or need and instead gather feedback through various methods and tools, such as A/B testing, prototyping, usability testing, and analytics dashboards.
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Eric Malnati
Results-Oriented SaaS Account Executive | 5 Years of Experience Driving Revenue Growth
(edited)Designing user interviews based on insights from customer feedback channels leads to more effective results and a deeper understanding of your customers. Your triangulated qualitative feedback from support tickets, sales calls, app reviews, social channels and every other qualitative source can all be used to guide the interview process. This establishes an understanding of the information that will be most impactful to collect in your 1:1 conversations. AI-powered feedback analytics platforms provide insights based on all this feedback to facilitate an accurate, holistic understanding of the Voice of Customer in ways that manual analysis cannot.
User feedback is not only valuable for you, but also for your users, your team, and your stakeholders. You need to communicate feedback and results to keep them informed, engaged, and satisfied. Communicating feedback and results can help you build trust and rapport with your users, show them that you care about their opinions and needs, and encourage them to provide more feedback in the future. Communicating feedback and results can also help you align your team and stakeholders on your goals and priorities, showcase your achievements and challenges, and solicit their support and feedback.
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Sharing user feedback with internal teams facilitates collaboration and alignment, promoting a common understanding of user needs and goals. It cultivates user empathy with users and serves as a cross-functional alignment tool. This approach increases the likelihood of developing the best solutions as the team contributes to addressing user pain points. Additionally, sharing user feedback with users demonstrates that you listen to their feedback, helps in gaining user trust and promoting user, engagement and loyalty. It also serves as a validation tool for what you are building.