Product Discovery Processes

Do you know the right situations to leverage different types of quantitative product discovery? What about the most common missteps people make when conducting it? I was joined by Behzod Sirjani for Part 2 of our our three part installment on Mastering Product Discovery. At over an hour long read, we tried to created the canonical resource on Quantitative Discovery methods — where you use quantitative data to inform decisions about your product development. Bookmark it and come back to it whenever you have a question. We covered every quantitative discovery method you could reasonably execute without millions of dollars: ❓ Surveys and Questionnaires 🔬 A/B and Multivariate Testing 📈 Analytics and Usage Data 📉 Cohort Analysis 🔻 Funnel Analysis 🐭 Clickstream Analysis 🔥 Heatmaps ✔ Benchmark Studies 📣 NPS (Net Promoter Score) 🤗 CSAT (Customer Satisfaction) 🤔 True Intent Studies 💪 Task Success and Time-on-Task Analysis You’ll learn: 1️⃣ What it is and when to use it 2️⃣ What size and state of company you should be at to leverage it 3️⃣ How execute successfully 4️⃣ Common mistakes to avoid 5️⃣ Artifacts and templates you can leverage 6️⃣ Stories on successful execution and outcomes 7️⃣ Software you can leverage to help you with each type We pulled in some of our favorite examples examples from: Jack McDermott Ben Williams, Fareed Mosavat, Matt Bilotti, Crystal Widjaja, Shaun Clowes, Austin Hay, John Egan, Benjamin Lauzier, Daniel Wolchonok, Elena Verna and of course Behzod Sirjani and myself. We told stories from Slack, Patreon, Lyft, Meta, and more. Bookmark it at the link in the comments and get ready for Part 3, dropping in 2024.

Product discovery isn’t just an event—it’s an ongoing journey where the customer is always at the center. After diving into “Continuous Discovery Habits” by Teresa Torres, it’s clear that successful product teams make continuous learning a habit, not a phase. This book is a must-read for product owners and their teams to foster a truly collaborative process where decisions aren’t made by one person but through shared understanding and teamwork. One key insight? From the initial stages to later iterations, customer understanding should never stop. 💡 Customer interviews and feedback loops are critical throughout the lifecycle—not just at the start. 🌳 Solution tree mapping helps teams visualize possibilities, keep track of what’s being tested, and align on what truly solves the customer’s problem. 🤝 Most importantly, involving cross-functional teams in these practices ensures everyone—from design to development—has a shared understanding of the problem space and can contribute meaningfully to the solution. In my work, both for my own products and client projects, I’ve adopted: 💬 Frequent customer interviews to deepen our insights 🌿 Collaborative solution mapping to explore ideas and align the team 📊 Regular sharing of findings to keep everyone in sync The result? We don’t just build—we learn, adapt, and improve continuously with the customer in focus. If you’re a product owner or part of a product team, this book is a game changer. It helps you foster a habit of customer-centric discovery while ensuring alignment across all roles. Are you already practicing continuous discovery in your teams? How do you ensure customer understanding remains at the heart of your product journey? Let’s exchange ideas! 🔍💬 #CustomerFirst #ProductDiscovery #Collaboration #SolutionMapping #ContinuousLearning #ProductManagement #TeamAlignment #MustRead

What if we reimagined the Double Diamond through the lens of Jobs-to-be-Done? 🤔 Product Management is about mastering various methodologies and knowing when to apply them. No single framework fits all scenarios - the key is understanding how different approaches can complement each other to drive better outcomes. I have been learning and practicing the art and science of Innovation through the concepts of JTBD, Human Centered Design, Design Thinking, Customer Driven Innovation, Continuous Discovery, Product Discovery, Lean, etc., I've found these methodologies aren't just related, they're deeply interconnected pieces of the same puzzle. I took the classic double diamond design thinking framework and applied JTBD to it and here is how it looks in my view. While the double diamond model divides the journey into Problem → Solution spaces, the evolved version speaks the language of jobs and outcomes 💎Left Diamond: Transformed from problem-finding to "Jobs & Outcomes" - focusing on understanding what customers are trying to achieve in their contexts. 🌉The Bridge: "Opportunity Statements" replace "Problem Definition" - shifting from fixing issues to unlocking potential. Opportunity Statements are what Tony Ulwick calls "Hidden Growth Opportunities". These statements guide our innovation direction. 💎Right Diamond: Maintains the Design/Develop and Iterate/Deliver phases, but shifts validation focus to measuring how effectively we enable customers to achieve their desired outcomes. This framework moves beyond problem-solution thinking to create value through deep understanding of customer progress and success metrics in the form of jobs and outcomes. Have you integrated different innovation frameworks in your work? What have you learned? Would love to hear your experiences! #innovation #JTBD #designthinking #productdiscovery

Should product discovery be done differently for Platforms vs. Products? Let's Explore! Product discovery is crucial, but it's not one-size-fits-all. While there's no shortage of materials on consumer product discovery, the unique challenges of platform product discovery often go unaddressed. Here's what makes platform product discovery distinct: 👨💻 𝗙𝗼𝗿 𝗠𝗶𝗱𝗱𝗹𝗲 𝗨𝘀𝗲𝗿𝘀: Whether they're internal teams or external developers, these users need tools that enhance their ability to innovate on your platform. Does your platform equip them to efficiently meet end-user needs? 🚀 𝗙𝗼𝗿 𝗘𝗻𝗱 𝗨𝘀𝗲𝗿𝘀: It’s all about the final experience. Does the platform serve the end goals of the ultimate customers effectively? 🤝 Dual-Layer Discovery: Platform products require a two-pronged approach: • 𝗘𝗻𝗱 𝗨𝘀𝗲𝗿 𝗙𝗼𝗰𝘂𝘀: Dive into understanding their specific goals and needs. What fundamental capabilities should your platform have to serve these needs?    • 𝗠𝗶𝗱𝗱𝗹𝗲 𝗨𝘀𝗲𝗿 𝗙𝗼𝗰𝘂𝘀: Assess whether the platform provides the necessary tools for these key developers. Is it easier and more cost-effective for them to use your platform than starting from scratch? Combining insights from both user types ensures your platform is not just functional but preferred choice. How do you approach product discovery for platform products? Do you find it differs significantly from consumer products? Share your thoughts and strategies in the comments!👇 #ProductDiscovery #ProductManagement #PlatformProductStrategy

During 20 years, Tristan and I have observed how the most effective organizations handle product discovery. Here are the 4 conclusions we came to: 1. By nature, discovery is difficult because it opens up a world of possibilities. The more you explore, the harder it becomes to choose. 2. In the best discovery organizations, people don’t have better judgment, talent or creativity. They are just more disciplined, thanks to an environment that supports them. 3. Of course, these organizations are good at interviewing users or testing hypotheses. But what sets them apart is how those activities are part of a holistic approach, making their excellence in discovery visible everywhere. - They prioritize explorations that are aligned with the company strategy. - They decide when to rely on A/B tests, user interviews or bold convictions. - They articulate stories that deeply resonate with users. - They nurture a culture where diversity of perspectives are seen as a blessing. - They know when to end discovery, and how to rapidly transition to delivery. - They ship fast, with confidence. - They promote managers who set high ambitions and coach with care. 4. Such success happens when a clear operational and organizational model is acted on, every single day, by everyone. Excelling at product discovery requires a simple and solid playbook — one that fits the specificities of your organization. (At Discovery Discipline, we are the experts in the creation and implementation of such discovery playbooks. Contact me if you'd be interested in working with us.)

How Not to Waste Time and Effort Building the Wrong Things There's no one sure-fire approach, but these principles should help: 1. Start with (outcome-based) goals, not ideas 2. For any given goal think of multiple ideas. Most ideas will not create a measurable improvement, so we need to have more than one. 3. To find the ideas that work, you have to repeatedly evaluate and test them, then invest only in those ideas that show supporting evidence (product discovery). 4. Managers and stakeholders don’t have the time, tools, skills, and subject-matter expertise to evaluate and test ideas and to analyze evidence. Product teams should do this work, but they have to do it transparently and objectively, working towards agreed and measurable goals, and with feedback from managers. 5. Having product teams own product discovery as well as delivery is not disempowering managers and stakeholders. On the contrary it's making them far more effective at their roles. #productmanagement #productdiscovery

Many startups that skip or inadequately perform a 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 often fail because they miss crucial insights about their target market. Customer Discovery is the process of identifying and validating the target market's needs, pain points, and behaviors before fully developing a product or service. It involves direct engagement with potential customers through interviews, surveys, and observations to gather insights that guide product development, ensuring a strong product-market fit. This process helps startups avoid some of the following pitfalls: 𝐔𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝𝐢𝐧𝐠 𝐍𝐞𝐞𝐝𝐬 Without Customer Discovery, startups might develop products or services that do not truly address their target customers' needs or pain points. This misalignment means that even if the product is technically sound, it may not resonate with the intended audience, leading to poor adoption rates. 𝐀𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬 𝐯𝐬. 𝐑𝐞𝐚𝐥𝐢𝐭𝐲 Startups often base their product development on assumptions rather than validated insights. These assumptions might not hold true in the real market, leading to a product that customers do not want or need. 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐂𝐨𝐬𝐭𝐬 Without proper customer insights, startups risk spending significant time and money developing features or products that ultimately don’t meet market demand. This misallocation of resources can drain a startup’s budget and limit its ability to pivot or adjust. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐚𝐧𝐝 𝐒𝐚𝐥𝐞𝐬 𝐄𝐟𝐟𝐨𝐫𝐭𝐬 If a product doesn’t align with customer needs, marketing and sales efforts may also fail, as the messaging and value proposition might not resonate with the target audience. 𝐑𝐞𝐬𝐢𝐬𝐭𝐚𝐧𝐜𝐞 𝐓𝐨 𝐂𝐡𝐚𝐧𝐠𝐞 Startups that skip Customer Discovery may become overly attached to their original idea, making it challenging to recognize when a pivot is necessary or what direction to take. 𝐋𝐚𝐜𝐤 𝐨𝐟 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 Investors typically look for evidence that a startup understands its market and customer base. A lack of Customer Discovery can lead to skepticism about the startup’s market fit and scalability, making it harder to secure funding. Read more about Customer Discovery here: https://lnkd.in/e7NxeqfG

Today, I experienced a swift AI-driven product discovery process, yielding impressive results. The rise of AI tools signals a shift in our approach, moving from traditional methods to AI-assisted processes. Here's a breakdown of our recent innovation: - Initially, we operated with a conventional process outlining sessions like defining personas, mapping journeys, and prioritizing stories. - I transformed the board steps into key questions. - Subsequently, I conducted an interview with the client, leveraging AI to transcribe the discussion automatically. - By inputting the transcript into GPT, I tasked it with generating personas, journeys, and stories based on the conversation. In just one hour with the product architect, we extracted substantial data for accurate estimations and MVP planning. While this process isn't flawless, it signifies our progress towards expedited implementation. As software development accelerates in coding, the discovery phase is also evolving. Eventually, stories will inform tools like Cursor for code creation, optimizing the software development lifecycle. In this new AI era, we are redefining our workflows to enhance efficiency. We'll iterate and optimize our new workflow. We're migrating to a new process and bringing AI accelerated value to our clients. Not tomorrow. Right now! Zallpy Digital Zallpy North America