What are the best data sources for product development decisions?
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As a product manager, you need to make informed decisions about your product development based on data. But what are the best data sources for product development decisions? How can you collect, analyze, and use data effectively to validate your assumptions, prioritize your features, and measure your outcomes? In this article, we will explore some of the most common and useful data sources for product development decisions and how to leverage them in your product management process.
Customer feedback is one of the most valuable data sources for product development decisions because it tells you what your customers think, feel, and want from your product. You can collect customer feedback from various channels, such as surveys, interviews, reviews, ratings, support tickets, social media, forums, and more. You can use customer feedback to identify customer problems, needs, preferences, expectations, and satisfaction levels. You can also use customer feedback to test your hypotheses, validate your solutions, and iterate on your product features.
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Ileana Marcut
Co-Founder, UX & Product Strategy at Creative Glue Lab
Using a structured approach to analyze customer feedback helps to overcome biases and get objective results. Make informed decisions when prioritizing product features and working on your growth strategy using results from customer feedback. Test early concepts before implementation to validate ideas and customer needs.
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Tomasz Tomaszewski
💎 Top LinkedIn PM Voice | Head of Product, Author, Product Coach 👉 On a mission to help 1000+ product folks go beyond the backlog manager role
I use Jira Product Discovery for systematically gathering and organizing user feedback. 👉 Each feedback is tagged and, whenever possible, linked to existing opportunities in Jira product Discovery. 👉 This methodical approach transforms our feedback database into a rich, primary data source about our users. 👉 Regularly, I dive into this feedback to conduct analyses. It's a strategic exploration to uncover new opportunities and insights. By dissecting patterns, trends, and user sentiments within the feedback, I can identify emerging needs or areas for improvement.
User behavior is another important data source for product development decisions because it shows you how your customers use your product, what actions they take, what goals they achieve, and what obstacles they face. You can collect user behavior data from various tools, such as analytics, heatmaps, session recordings, A/B testing, and more. You can use user behavior data to understand customer journeys, patterns, segments, and retention rates. You can also use user behavior data to optimize your user interface, user experience, and user value proposition.
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Clement Kao
Founder at Product Teacher
Specifically, leverage "behavioral segment analysis" for user behavior data! For just about every feature, we can split users into three different groups: power users, casual users, and non-users. These roughly correspond to "top quartile", "median", and "bottom quartile." For example, let's say that you're in charge of a transaction management product, and one of your features is a search feature. You could wind up with a usage distribution like this: * Top quartile: 10 or more searches per week * Median: 2 - 10 searches per week * Bottom quartile: 2 or fewer searches per week This info is gold! We can identify how to nudge our non-users towards becoming casual users, and we can brainstorm ways to turn casual users into power users.
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Tomasz Tomaszewski
💎 Top LinkedIn PM Voice | Head of Product, Author, Product Coach 👉 On a mission to help 1000+ product folks go beyond the backlog manager role
🛠️ HotJar is a simple and intuitive tool to record and analyse user behaviour. It can also help you with gathering user feedback and send user surveys.
Market research is a useful data source for product development decisions because it helps you understand your target market, your competitors, your industry trends, and your market opportunities. You can collect market research data from various sources, such as reports, studies, articles, podcasts, webinars, events, and more. You can use market research data to define your target market, your market size, your market share, and your market positioning. You can also use market research data to benchmark your product performance, identify your competitive advantages, and discover new market needs.
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Clement Kao
Founder at Product Teacher
Market research is a bit of a double-edged sword; be careful with how you use it! While competitive actions and industry benchmarks can be insightful, remember that your specific customer base is not the same as "the market." Too often, I've seen product folks chase "market trends" and completely forget to solve the pains of their current customers & users. When you spend too much time chasing competitors, you lose your differentiation! A better way to think about market research - be divergent! Don't limit your research to your immediate industry. Look beyond your borders, explore diverse markets, and draw inspiration from unexpected places. Sometimes, groundbreaking ideas come from connecting dots that others haven't even noticed.
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Nancy Martínez
As a product manager, it's a continuous task to constantly monitor competitors and understand the evolving trends and preferences of customers. However, the key isn't to simply copy; instead, you should use this information to develop a robust value proposition that aligns with your product's mission. In today's market, it's evident when a product is a mere copy of a competitor's, and customers recognize that lack of originality. The focus should be on creativity, market awareness, and maintaining a clear differentiation, as opposed to replicating what already exists.
Product performance is a critical data source for product development decisions because it measures the quality, reliability, and efficiency of your product. You can collect product performance data from various metrics, such as uptime, speed, errors, bugs, crashes, and more. You can use product performance data to monitor your product health, identify your product issues, and improve your product stability. You can also use product performance data to set your product goals, track your product progress, and evaluate your product outcomes.
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Clement Kao
Founder at Product Teacher
Quantitative product metrics show you the "what" and the "how much" - that is, it'll give you insights into customer behaviors and usage patterns, but it's not going to tell you the "why." Qualitative insights e.g. customer interviews, moderated user tests, etc. will show you the "why" and the "who" - which kinds of customers do you attract, which kinds do you fail to attract, and why each segment makes the decisions that they make. While I wholeheartedly support using product metrics to inform decisions, I strongly recommend pairing metrics with qualitative insights. In other words, don't fall for the trap of being "data-driven"; data can be dangerous when used in isolation!
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Bakhytzhan Zhakazhanov
CEO & Founder at ProductBee
Assess product quality, reliability, and efficiency through metrics like uptime, speed, and error rates. Monitor product health, identify issues, and enhance stability. Set and track goals, evaluating progress and outcomes for continual product improvement.
Team feedback is a helpful data source for product development decisions because it reflects the opinions, insights, and suggestions of your product team members. You can collect team feedback from various methods, such as meetings, workshops, brainstorming sessions, retrospectives, and more. You can use team feedback to foster collaboration, communication, and alignment among your product team members. You can also use team feedback to generate ideas, solve problems, and learn from mistakes.
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Clement Kao
Founder at Product Teacher
Team feedback is critical, yes, but folks aren't going to give you feedback if they don't feel psychologically safe! As product managers, it's our responsibility to create an environment where team members feel safe and empowered to share their insights. Building trust and psychological safety is the foundation for fruitful team dynamics. On top of that, your teammates should be empowered to make proactive proposals. They shouldn't need to wait for you to "give them the floor" for presenting feedback (both for product ideas and team processes). Encourage people to raise suggestions to you in one-on-one meetings or over email & Slack. Publicly celebrate people who demonstrate the courage to speak up and share their valuable perspectives!
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Bakhytzhan Zhakazhanov
CEO & Founder at ProductBee
Harness insights from your product team through methods like meetings and retrospectives. Foster collaboration, communication, and alignment. Team feedback is a valuable resource for generating ideas, problem-solving, and learning from collective experiences.
Data quality is a key factor for product development decisions because it affects the accuracy, relevance, and timeliness of your data sources. You can ensure data quality by following some best practices, such as defining your data goals, choosing your data sources, collecting your data ethically, cleaning your data regularly, analyzing your data objectively, and presenting your data clearly. You can improve data quality by using some techniques, such as data validation, data integration, data visualization, and data storytelling.
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Bakhytzhan Zhakazhanov
CEO & Founder at ProductBee
Recognize the pivotal role of data quality in accurate decision-making. Ensure data quality by setting clear goals, ethically collecting and cleaning data, and presenting it objectively. Use techniques like data validation, integration, visualization, and storytelling to enhance data quality.
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Imran Alam
Product Manager at bKash Limited | Linkedin Top Voice in Product Management
Establishing clear data collection protocols can help defining specific metrics and ensuring consistency in data gathering methodologies enhances the reliability of the information collected. Employing data validation techniques, such as cross-referencing with multiple sources or running integrity checks should add an extra layer of assurance. It must be helpful to assess the relevance of the data to the specific product context, filtering out noise and focusing on key indicators. Advanced analytics and visualization tools can provide deeper insights, making it easier to identify patterns and outliers. Taking feedback loops with stakeholders ensures ongoing validation and refinement of data quality.
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Bakhytzhan Zhakazhanov
CEO & Founder at ProductBee
Here’s what else to consider: This space invites sharing examples, stories, or insights that don't fit neatly into previous sections. What unique considerations, anecdotes, or perspectives would you like to add?
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Olawale Omotoso
Product Manager, UX and Growth | Fintech | Innovation | B2C | B2B
I've found that leveraging competitive intelligence and industry benchmarks adds a strategic layer to decision-making. Keeping a keen eye on what competitors are up to, understanding industry trends, and benchmarking our performance against industry standards provides invaluable context. Additionally, tapping into emerging technologies and staying attuned to regulatory changes in the financial landscape ensures that our product not only meets current expectations but also anticipates and adapts to future shifts, giving us a competitive edge in the dynamic fintech arena. It's like having a compass that not only points to where we are but also helps us navigate the uncharted waters of what's coming next.