Using Customer Insights To Drive Product Strategy

While it can be easily believed that customers are the ultimate experts about their own needs, there are ways to gain insights and knowledge that customers may not be aware of or able to articulate directly. While customers are the ultimate source of truth about their needs, product managers can complement this knowledge by employing a combination of research, data analysis, and empathetic understanding to gain a more comprehensive understanding of customer needs and expectations. The goal is not to know more than customers but to use various tools and methods to gain insights that can lead to building better products and delivering exceptional user experiences. ➡️ User Research: Conducting thorough user research, such as interviews, surveys, and observational studies, can reveal underlying needs and pain points that customers may not have fully recognized or articulated. By learning from many users, we gain holistic insights and deeper insights into their motivations and behaviors. ➡️ Data Analysis: Analyzing user data, including behavioral data and usage patterns, can provide valuable insights into customer preferences and pain points. By identifying trends and patterns in the data, product managers can make informed decisions about what features or improvements are most likely to address customer needs effectively. ➡️ Contextual Inquiry: Observing customers in their real-life environment while using the product can uncover valuable insights into their needs and challenges. Contextual inquiry helps product managers understand the context in which customers use the product and how it fits into their daily lives. ➡️ Competitor Analysis: By studying competitors and their products, product managers can identify gaps in the market and potential unmet needs that customers may not even be aware of. Understanding what competitors offer can inspire product improvements and innovation. ➡️ Surfacing Implicit Needs: Sometimes, customers may not be able to express their needs explicitly, but through careful analysis and empathetic understanding, product managers can infer these implicit needs. This requires the ability to interpret feedback, observe behaviors, and understand the context in which customers use the product. ➡️ Iterative Prototyping and Testing: Continuously iterating and testing product prototypes with users allows product managers to gather feedback and refine the product based on real-world usage. Through this iterative process, product managers can uncover deeper customer needs and iteratively improve the product to meet those needs effectively. ➡️ Expertise in the Domain: Product managers, industry thought leaders, academic researchers, and others with deep domain knowledge and expertise can anticipate customer needs based on industry trends, best practices, and a comprehensive understanding of the market. #productinnovation #discovery #productmanagement #productleadership

Your Head of Product will tell you this: The best PMs aren’t product people. The best PMs are business people. Early in my career, I thought being a strong PM meant: ✅ Clean roadmaps ✅ On-time releases ✅ Backlog grooming like a pro I checked every box—and still missed the mark. Because none of that matters if the product doesn’t drive the business. Old way: PMs manage features, coordinate teams, and keep the engine running. New way: PMs challenge assumptions, prioritize by impact, and own outcomes—not just outputs. Before anything goes on the roadmap, ask: - What business metric does this move? - What customer problem does it solve? - Why now? When you start thinking like a business owner—not just a product owner—everything changes. Here are 3 ways to make that shift: ✅ Take the initiative to drive action. Don’t wait for direction—own the next move. -> Frame problems, not just solutions. -> Bring data and customer insights to support your case. -> Proactively align with cross-functional partners. 💡 Actionable step: Use a BLUF (Bottom Line Up Front) to pitch new ideas: - What we’re proposing - Why it matters to the business - What we need to move forward ✅ Ensure the team knows the vision you’re pursuing. People don’t rally behind features—they rally behind purpose. -> Set clear outcomes, not just outputs. -> Anchor sprints to customer impact. -> Tell the story behind the roadmap. 💡 Actionable step: Start each sprint with a one-liner: "This week, we’re solving this problem for this customer because it supports this business goal." ✅ Prioritize by business impact. Great PMs don’t chase effort—they chase outcomes. -> Tie every feature to a metric that matters. -> Cut what doesn’t move the needle. -> Make tradeoffs visible and deliberate. 💡 Actionable step: Make sure every feature on the roadmap is linked to a prioritized strategic initiative. If it doesn’t ladder up, it doesn’t ship. Final thought: You don’t need an MBA. But you do need to think like a GM. -- 👋 I’m Ron Yang, a product leader and advisor. Follow me for insights on product leadership & strategy.

I think about Jeff Bezos's "start with the press release and work backward" approach. Here is a future headline I would like to see: "Surveys are no longer the primary tool for gathering insights." To get there, surveys will have had to evolve into precision instruments used strategically to fill gaps in data. Let's call this the "Adaptive Survey." With adaptive surveys, organizations can target key moments in the customer or employee journey where existing data falls short. Instead of overwhelming consumers and employees with endless, and meaningless, questions, surveys step in only when context is missing or deeper understanding is required. Imagine leveraging your operational data to identify a drop in engagement and deploying an adaptive survey to better understand and pinpoint the "why" behind it. Or, using transactional data to detect unusual purchasing behavior and triggering a quick, personalized survey to uncover motivations. Here's how I hope adaptive surveys will reshape insight/VoC strategies: Targeted Deployment: Adaptive surveys appear at critical decision points or after unique behaviors, ensuring relevance and avoiding redundancy. Data-First Insights: Existing operational, transactional, and behavioral data provide the foundation for understanding experiences. Surveys now act as supplements, not the main course of the meal. Contextual Relevance: Real-time customization ensures questions are tailored to the gaps identified by existing data, enhancing both response quality and user experience. Strategic Focus: Surveys are used to validate hypotheses, explore unexpected behaviors, or uncover latent needs...not to rehash what’s already known. Surveys don't have to be the blunt instrument they are today. They can be a surgical tool for extracting insights that existing data can’t reach. What are your thoughts? #surveys #customerexperience #ai #adaptiveAI #customerfeedback #innovation #technology

I’m not asking my CSMs to resolve support tickets. I’m asking them to leverage them. Support tickets aren’t just a backlog of problems; they’re customer truth bombs waiting to explode. If you’re not mining them for insights, you’re flying blind—and that’s exactly how churn sneaks up on you. Every Customer Success team I’ve ever led has been trained to use Support tickets strategically. Why? Because they’re packed with insights that make us better at our jobs. ✅ We learn more about the product. ✅ We spot trends before they become problems. ✅ We understand our customers’ use cases more deeply. If you’re not tapping into support data, here’s what you’re missing: 🔥 Emerging Pain Points Recurring issues expose friction in the customer journey. Ignore them, and those minor frustrations turn into churn-worthy headaches. 🔥 Product Gaps Customers vote with their tickets. If the same feature requests or usability complaints keep surfacing, your roadmap is practically writing itself. 🔥 Engagement Risks A spike in tickets isn’t just noise—it’s a flare. Users don’t submit tickets when they’re thriving; they do it when they’re stuck, frustrated, or in need of more enablement. Here are a few ways my team and I are using these insights: ✅ Spot & Engage Struggling Users A surge in ticket volume? Proactively reach out before frustration turns into a cancellation. ✅ Create Targeted Content If the same questions keep coming up, turn those insights into help docs, webinars, or office hours. ✅ Surface Expansion Opportunities Seeing frequent feature requests? Build them—or better yet, use them to tee up expansion conversations. ✅ Map Out User Behavior Support tickets tell you who’s onboarding, who’s adopting new features, and who’s stuck. Use that data to drive deeper engagement. ✅ Collaborate with Product Your product team needs this intel. Share support trends regularly to influence meaningful fixes and features. High ticket volume isn’t necessarily a bad thing—but you need to know how to use it to your advantage. Bottom line? CSMs don’t need to fix support tickets. But the best ones know how to use them to drive retention, expansion, and adoption. _____________________________ 📣 If you liked my post, you’ll love my newsletter. Every week I share learnings, advice and strategies from my experience going from CSM to CCO. Join 12k+ subscribers of The Journey and turn insights into action. Sign up on my profile.

We surveyed 1,244 product teams over the last 6 months and uncovered a reality that blew our minds: While all product teams are trying to create products that better satisfy customer needs, over 80% of product teams do not agree on what a customer "need" even is! Teams define "needs" as exciters and delight-ers, pains and gains, specifications and requirements, features, value drivers, wants and benefits, wishes, aspirations... ...and the list goes on, as if any of these inputs will correctly inform the innovation process. Here's the problem: THEY DON'T! Just like any process, only precise inputs lead to a great result. So what is the right input? We know that people buy products and services to get a "job" done. So, let's start by defining customer "needs" as the metrics customers use to measure success when getting a job done. If we know how customers measure success, we can create solutions that help them get their jobs done better--and win in the marketplace. These metrics, which we call the customer's desired outcomes, are tied to the customer's job-to-be-done and are unique in many ways. They are: - measurable and controllable, - actionable, - unambiguous, - solution independent and, - stable over time. When listening to music, for example, a music enthusiast may want to: “minimize the time it takes to get the songs in the desired order for listening.” This is one of many outcomes associated with the job of listening to music. Using these customer inputs as customer need statements, you're able to: 1. Understand how your customer measures success. 2. Measure how well your solutions get the job done. 3. Give your team clear instructions on how to improve your solutions. Watch your team transform when they're aligned with the metrics your customers use to measure success. #CustomerNeeds #InnovationProcess

Strategic PMM teams start with INSIGHT and then impact every part of the GTM motion, end to end. This is how product marketing should add value to every part of the process: 1️⃣ Insights capture The most strategic PMM orgs co-own insights programs with product. They: Conduct market, customer, and competitive research Gather actionable insights that reveal market opportunities Build the foundation that informs all subsequent decisions 2️⃣ Commercial strategy This is where the insights get transformed into quantifiable business opportunities. This is the part that is most similar to the work of management consultants: Develop segmentation and targeting frameworks Create pricing and packaging structures Craft positioning that should ideally PRECEDE product development 3️⃣ Product strategy While PMs own the product strategy, a PMM should have a strong influence on it: Collaborate with product managers on vision and roadmap Ensure market needs directly influence product direction Provide the crucial market context that shapes what gets built 4️⃣ Product development While PM and Eng work on developing the product, PMMs have a crucial role in ensuring the success of the product: Validate product through beta programs Gather customer feedback during development cycles Ensure the final product delivers on its market promise 5️⃣ Outbound go-to-market This is the part the PMM owns and takes charge of, while orchestrating with other field teams. Develop channel promotion strategies Create compelling messaging frameworks Enable internal teams with sales tools and training Execute successful product launches --- Unfortunately, many product marketing teams are confined to just the final pillar - launch execution - without the strategic influence of the preceding four. The true opportunity lies in working towards the left from launch to insights, gaining that "seat at the table" where product marketing becomes a strategic force. This framework can serve as a maturity model for you. Whether you're: --> Looking to expand your influence within your current company --> Building a new product marketing function from scratch --> Interviewing for a strategic PMM role Remember: Product marketing at its best is business strategy plus execution. The more pillars you can effectively own, the more strategic your function becomes. What's your experience? #ProductMarketing #GoToMarket #ProductStrategy #MarketingLeadership

Survey data often ends up as static reports, but it doesn’t have to stop there. With the right tools, those responses can help us predict what users will do next and what changes will matter most. In recent years, predictive modeling has become one of the most exciting ways to extend the value of UX surveys. Whether you’re forecasting churn, identifying what actually drives your NPS score, or segmenting users into meaningful groups, these methods offer new levels of clarity. One technique I keep coming back to is key driver analysis using machine learning. Traditional regression models often struggle when survey variables are correlated. But newer approaches like Shapley value analysis are much better at estimating how each factor contributes to an outcome. It works by simulating all possible combinations of inputs, helping surface drivers that might be masked in a linear model. For example, instead of wondering whether UI clarity or response time matters more, you can get a clear ranked breakdown - and that turns into a sharper product roadmap. Another area that’s taken off is modeling behavior from survey feedback. You might train a model to predict churn based on dissatisfaction scores, or forecast which feature requests are likely to lead to higher engagement. Even a simple decision tree or logistic regression can identify risk signals early. This kind of modeling lets us treat feedback as a live input to product strategy rather than just a postmortem. Segmentation is another win. Using clustering algorithms like k-means or hierarchical clustering, we can go beyond generic personas and find real behavioral patterns - like users who rate the product moderately but are deeply engaged, or those who are new and struggling. These insights help teams build more tailored experiences. And the most exciting part for me is combining surveys with product analytics. When you pair someone’s satisfaction score with their actual usage behavior, the insights become much more powerful. It tells us when a complaint is just noise and when it’s a warning sign. And it can guide which users to reach out to before they walk away.

Revitalizing a Legacy Product: A Strategic Approach Taking on an older product with outdated code and limited documentation can be daunting. Where do you start when institutional knowledge is sparse? My approach is to go back to the source - connect directly with long-time employees and current users. Interview employees to reconstruct original motivations and use cases. Conduct usability testing and discovery interviews with customers to see how they leverage the product today. This field research uncovers valuable insights: ►Key workflows the product enables ►Functionality that customers actually use ►Opportunities to improve and solve new problems Don't just replicate the past. Leverage customer context to reimagine what's possible. New technologies may now enable you to build a far superior product. Watch users directly to identify core functionality versus unnecessary bloat. Collaborating closely with engineers is crucial too. Review the codebase for optimization opportunities. Determine if replatforming is needed to support modern architecture and experiences. In summary, let customer needs guide your vision. The problems users face today are likely different than when it was first built. Maintain a beginner's mindset. Then, architect creative solutions to exceed customer expectations. By coupling curiosity with technology, legacy products can transform into an organization's most impactful assets. There are hidden opportunities in the old - you just have to dig them out. What approaches have you found effective for modernizing legacy products? I'd love to hear your experiences! Listen now 🎧 Youtube: https://lnkd.in/eD3ABYH3 Website: https://lnkd.in/eU6RfMFe Do you have a burning product-related question for me? Feel free to submit one here DearMelissa.com and you might find your question featured and answered in an upcoming episode. #ProductThinking #DearMelissa #LegacyProducts #ProductModernization #CustomerCentric #TechInnovation

🎯 For many product teams, the best product insights don’t always come from user interviews or analytics—they come from your support team. Over the past few years, I've spent hours weekly reading support tickets. This helped me learn: 💡 What frustrated customers most. 💡 What “quick wins” could move the needle. 💡 How customers actually use products (often in ways we never imagined). One discovery from a weekly product-support review helped us fix a small onboarding issue. Another revealed a way users were "mis-using" our product which turned into a popular new product feature. At Decagon, we’re helping product teams unlock the power of support data with tools that surface trends, track key metrics like CSAT and deflection, and amplify the voice of the customer. In my blog post linked below, I share how product teams can unlock support insights to drive better decisions and deliver products customers love. 👇 What’s been your biggest learning from partnering with support?