CONTINUOUS DISCOVERY HABITS
Tags: #business #product management #design #technology #customer experience #research #agile #lean startup
Authors: Teresa Torres
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Overview
In a world overflowing with products, how can we ensure we’re building the right things? This book offers a structured and sustainable approach to continuous discovery, a practice that helps product teams continuously identify unmet customer needs and create solutions that address those needs. The book is written for “product people”: product managers, designers, and software engineers. It emphasizes that digital products are never done, but can and should continue to evolve as we learn more about our market, as our customers’ needs change, and as new technology becomes available. Rather than relying on opinion battles and gut feel, the book teaches product people to balance action with doubt. You’ll learn to infuse product decisions with customer input by conducting lightweight research weekly in pursuit of a desired business outcome. The book will help you shift from an output mindset to an outcome mindset, will teach you how to identify high-impact opportunities and avoid getting bogged down by customer requests, and will give you the tools to test your riskiest assumptions, so that you can build products that customers need and love. Along the way, you’ll learn how to use visual artifacts like experience maps and opportunity solution trees to align your product trio and to manage stakeholders, so that you can build confidence in your work and in the work of your team. You’ll learn to balance the strategic work of prioritizing customer opportunities with the tactical work of testing assumptions. The book will help you discover good opportunities and effective solutions, and will show you how to adapt as you learn.
Book Outline
11. MEASURING IMPACT
It’s critical to measure not only to evaluate if your solutions are working but also to understand their impact on your product and business outcomes. Often, we’ll find that what we thought would drive our outcome, didn’t. That’s ok. It means we need to keep learning. Learning from what doesn’t work will ultimately help us find what does. Discovery feeds delivery, and delivery feeds discovery. You can’t have one without the other.
Key concept: Discovery and delivery are not distinct phases but rather parts of a continuous cycle. As you run experiments, they naturally grow in size and require more real data and real users, which blends with the work of delivery. Likewise, good delivery work is instrumented to provide valuable feedback that fuels further discovery.
10. TESTING ASSUMPTIONS, NOT IDEAS
To test your riskiest assumptions, start small and iterate your way to bigger, more reliable, and more sound tests. Small tests are faster and give us the opportunity to fail sooner. Learning comes from both successes and failures but is especially acute when we fail, as that tells us our assumptions were wrong and we need to update our beliefs. To avoid being misled by false positives and false negatives, triangulate across multiple small tests before making big decisions.
Key concept: Rather than making go/no-go decisions based on one data point, it’s critical to triangulate, combining multiple data points from a mix of research methods, before making decisions about what to do next.
13. SHOW YOUR WORK
When sharing your work with stakeholders, be sure to slow down and show them how you arrived at your conclusions rather than jumping straight to the conclusions themselves. Use the artifacts you’ve created to help them understand the customer needs and pain points you uncovered. Invite them to add to your work by sharing their own knowledge and expertise. Done well, this process can help you generate buy-in and make it more likely that your stakeholders will support the path you chose, even when it deviates from what they originally requested.
Key concept: The ‘curse of knowledge’ is a cognitive bias that makes it hard to remember what it was like not to know something, which can lead to us assuming our conclusions are more obvious than they really are. To avoid this bias, show your work, starting at the beginning. Walk your stakeholder through the journey you took to reach your conclusions.
15. WHAT’S NEXT?
Building continuous discovery habits is a journey, not a destination. Start small and iterate from there. The keystone habit of continuous discovery is continuous interviewing. Engage with your customers at least once per week. If you can’t talk to customers, find people who are like your customers and talk to them instead. Make next week better than last week. If you can do that, you are on the right path.
Key concept: Continuous discovery, like exercise, is a keystone habit. Keystone habits start a process that, over time, transforms everything. When product teams engage with their customers week over week, they don’t just get better at interviewing – they also start rapidly prototyping and experimenting more often. They do a better job of connecting what they are learning from their research activities with the product decisions they are making.
6. MAPPING THE OPPORTUNITY SPACE
Finding the right opportunity to pursue is critical for product success, but the opportunity space can feel vast and overwhelming. A critical step in taming the opportunity space is to map it out on an opportunity solution tree, using the tree structure to break down big, intractable opportunities into smaller more solvable sub-opportunities. The tree will also help us prioritize – focusing our efforts on the opportunities with the highest potential impact on our outcome.
Key concept: Many product teams are devoted to serving their customers and, when they hear about a need or pain point, they want to solve it. But our job is not to address every customer opportunity. Our job is to address customer opportunities that drive our desired outcome. This is how we create value for our business while creating value for our customers.
7. PRIORITIZING OPPORTUNITIES, NOT SOLUTIONS
Once we’ve mapped the opportunity space, it’s time to assess and prioritize opportunities. Instead of evaluating each opportunity in isolation, use the tree structure to help you focus your efforts. Evaluate opportunities by comparing and contrasting them with their siblings, helping you make better decisions about where to focus.
Key concept: Instead of making ‘whether or not’ decisions – ‘Should we do this?’ – shift to making ‘compare and contrast’ decisions – ‘Which of these is most important for us to address right now?’
3. FOCUSING ON OUTCOMES OVER OUTPUTS
The foundation for continuous discovery is shifting from an output mindset to an outcome mindset. An outcome is a change in human behavior that drives business results. It’s important to distinguish business outcomes – how well the business is progressing – from product outcomes – how well the product is moving the business forward. A product trio should be focused on a product outcome that is within their span of control to deliver and that is believed to be a leading indicator of a lagging indicator, business outcome. Set the product outcome by having a conversation with your product leader, sharing what impact the team believes they can have on a specific metric in a quarter.
Key concept: The Opportunity Solution Tree (OST) is a simple visual representation that helps product teams stay focused on outcomes. The OST helps product teams: Resolve the tension between business needs and customer needs Build and maintain a shared understanding of how they might reach their desired outcome Adopt a continuous mindset Unlock better decision-making Unlock faster learning cycles Build confidence in knowing what to do next Unlock simpler stakeholder management
4. VISUALIZING WHAT YOU KNOW
To avoid groupthink, start individually by creating an experience map that reflects what you currently know about your customers’ experience. Then share your maps as a team, asking questions to make sure you understand each other’s point of view. Look for the differences. Work together to merge your individual perspectives into a single, more comprehensive shared experience map.
Key concept: As you explore your teammates’ perspectives, ask questions to make sure you fully understand their point of view. Give them time and space to clarify what they think and why they think it. Don’t worry about what they got right or wrong (from your perspective). Instead, pay particular attention to the differences. Be curious.
8. SUPERCHARGED IDEATION
For strategic opportunities that require an innovative solution, you’ll want to generate several ideas to ensure that you uncover the best ones. Ideation is best done by first generating ideas alone and then sharing those ideas with the team. This process should be repeated several times to allow each team member to be inspired by the ideas of others. Remember, your first ideas are rarely your best ideas.
Key concept: Don’t try to spend an hour generating ideas. Take frequent breaks. Spread it out throughout your day. Try to generate ideas in the few minutes you have between meetings. After lunch, go for a walk, and daydream about what you might build. A change of scenery can often inspire new ideas. Try generating ideas at different times of the day. Some of us will be better first thing in the morning, when we have a lot of mental energy; others might find the late afternoon to be the optimal idea-generation time. Experiment. Find what works best for you.
5. CONTINUOUS INTERVIEWING
Talking to customers is a critical discovery habit, but the way most of us interview is deeply flawed. We tend to ask direct questions and ask our customers to speculate about their behavior. However, decades of research shows that interview participants struggle to answer direct questions accurately, and, even when they give a reasonable answer, we can’t be sure if the answer represents their actual behavior or their ideal behavior. To avoid this pitfall, ask your customers to share stories about recent instances. Memories about their actual behavior are far more reliable.
Key concept: Memories about recent instances are more reliable than our generalizations about our own behavior or our answers to direct questions.
9. IDENTIFYING HIDDEN ASSUMPTIONS
Product teams are often overconfident about the success of their ideas. One way to combat overconfidence and to de-risk our work is to identify the hidden assumptions that we need to be true for our solutions to succeed. We do this by generating many assumptions for each of our solution ideas and then prioritizing them based on two criteria: importance and evidence. We then start testing the assumptions with the least evidence that are still critical to success.
Key concept: Good tests kill flawed theories; we remain alive to guess again.
12. MANAGING THE CYCLES
Throughout our continuous discovery work, we’ll learn new things that may require us to revisit previous steps. The key to managing these cycles is to trust the process. A round of assumption tests will help you assess if an opportunity is the right one to pursue now. If it’s not, go back to assessing and prioritizing opportunities. There is no need to overcommit to an opportunity that isn’t a good fit for your current context. Continuous discovery also helps us make mid-course corrections. If your solution set isn’t resonating with customers, go back to ideation and generate a new set. The key is to remain flexible and to continuously adapt your approach based on what you learn.
Key concept: Discovery is messy, iterative, and rarely follows a linear path. Most of the work in discovery isn’t following the process but managing the cycles.
Essential Questions
1. What is Continuous Discovery and why is it valuable?
Continuous discovery is about creating a sustainable cadence for ongoing customer learning, ideally involving weekly touchpoints with customers by the product team who is building the product. This research is done to ensure that the team understands the customer needs, pain points, and desires that are most relevant to their current work, and to ensure that the product the team is building is delivering value for the customer in a way that drives value for the business.
2. Why should product teams focus on outcomes and not outputs?
While many product teams focus on delivering outputs - features, releases, and roadmaps - an outcome-focused team focuses on the impact those features have on both the customer and the business. An outcome is a change in human behavior that drives business results. When a product team is tasked with delivering a specific outcome, it gives them the latitude to explore the best outputs that might drive that outcome, allowing them to create the most value for the customer and the business.
3. How can we make sense of the vast opportunity space and how do we prioritize opportunities?
Finding the right opportunity to pursue is critical for product success. However, the opportunity space is vast and overwhelming. To avoid falling into the trap of reacting to customer requests, or of chasing the next shiny object, product teams need to take the time to map out the opportunity space. This is done using an opportunity solution tree. The opportunity solution tree helps the team break down big, intractable opportunities into smaller more solvable sub-opportunities. The opportunity solution tree also aids in decision making by helping the team focus their assessment efforts on the opportunities with the biggest potential impact.
4. Why is it important to consider multiple solutions and how can we effectively generate ideas as a team?
While it’s easy to overcommit to a great idea, we’ll make better decisions about what to build if we consider several solutions for each opportunity. This involves first individually generating ideas, then sharing our ideas across the team, and repeating this process until we’ve generated 15-20 ideas. We then use dot-voting to whittle our set down to three diverse ideas. We avoid dot-voting down to one idea, as the goal is to use assumption testing to help us decide which of these three ideas best delivers on our target opportunity.
5. What are assumptions, why are they so dangerous, and how can we test them?
Product teams often have a blind spot for the hidden assumptions that must be true in order for their solutions to succeed. To avoid being blindsided by what we didn’t consider, we need to develop a ‘prepare to be wrong’ mindset. This involves generating as many assumptions as possible for each of our three ideas and then prioritizing them based on their importance and the strength of the evidence that supports them. We then start testing our riskiest assumptions with lightweight assumption tests.
Key Takeaways
1. Focus on Outcomes, Not Outputs
Outcomes provide a clear direction for product development, ensuring the team’s efforts are aligned with business goals. By focusing on outcomes, the team shifts from a feature-factory mindset to a value-creation mindset. Rather than chasing the next shiny object, the team remains focused on making a meaningful impact.
Practical Application:
A team at a social media company is tasked with improving user engagement. Instead of focusing on adding new features, they first identify the desired outcome: Increase daily active users. They then conduct customer interviews to understand user behaviors and motivations. They discover that users value connecting with close friends and family but struggle to find meaningful content amidst the noise. Based on this insight, the team focuses on improving content filtering algorithms and notifications that help users surface relevant posts from their inner circle. By prioritizing the outcome of increased daily active users and grounding their solution in customer needs, the team is more likely to create a product that delivers value for both their users and their business.
2. Visualize the Customer Experience
Experience maps provide a shared understanding of the customer journey, helping the team identify opportunities for improvement. By visualizing the steps users take and the challenges they face, the team gains empathy for their customers and can develop solutions that address real needs.
Practical Application:
A team at a travel booking website is asked to improve the booking process. Instead of assuming they know where users struggle, the team creates an experience map to visualize the existing customer journey. They identify key steps, such as searching for flights, selecting dates, and entering traveler information. The map helps them understand the flow of the experience and reveals potential areas for improvement. By visualizing the customer journey, the team can identify specific pain points to address, such as lengthy forms or confusing navigation, ensuring their efforts are focused on making a tangible improvement to the user experience.
3. Test Your Assumptions
Assumption testing allows teams to quickly validate or invalidate their beliefs about user behavior and product functionality. By testing their riskiest assumptions early on, teams can avoid investing time and resources in building the wrong solutions. Testing also provides valuable data that can be used to inform product strategy and prioritization.
Practical Application:
An AI product engineer is designing a chatbot for customer support. The engineer identifies several assumptions about user behavior: Users will be willing to interact with a chatbot, users will clearly state their issue, and the chatbot will accurately understand user intent. To test these assumptions, the engineer develops a simple prototype and conducts user testing with a small group of customers. The testing reveals that users are hesitant to share sensitive information with a chatbot, preferring human interaction for complex issues. This insight allows the engineer to iterate the design and prioritize features that build user trust and provide a seamless transition to human support when needed.
4. Show Your Work
By showing their work, product teams can bring their stakeholders along on the discovery journey, building trust and increasing buy-in. This approach allows stakeholders to understand the rationale behind the team’s decisions, leading to greater support and collaboration.
Practical Application:
A product manager is presenting a new feature idea to their stakeholders. Instead of focusing on the feature’s technical specifications or projected ROI, the product manager starts by reminding stakeholders of the shared business outcome: Increase customer satisfaction. They then walk stakeholders through the discovery journey, using an opportunity solution tree to highlight the customer needs that drove the feature idea and the assumption tests that validated their approach. By showing their work, the product manager helps stakeholders understand the rationale behind the decision and builds confidence in the proposed solution.
5. Continuously Measure Impact
Continuous discovery and delivery are intertwined. As you build, you’ll discover new needs, uncover new opportunities, and refine your understanding of customer behavior. By continually measuring the impact of your work and making adjustments as needed, you can optimize for both short-term wins and long-term success.
Practical Application:
An AI development team is building a product recommendation engine for an e-commerce platform. Initially, they focus on increasing click-through rates on product recommendations. However, they also track the long-term impact on customer lifetime value and revenue. Over time, they observe that, while click-through rates increase, customer lifetime value and revenue remain stagnant. This insight prompts the team to revisit their assumptions and explore alternative product outcomes, such as add-to-cart rates or purchase completion rates, to ensure they’re driving meaningful business results. By continuously measuring the impact of their work and making adjustments as needed, the team can optimize their product for long-term success.
Suggested Deep Dive
Chapter: Chapter 11: Measuring Impact
This chapter addresses the critical need for measuring the impact of product decisions, not only on user behavior but also on key business outcomes. This is especially relevant for AI product engineers who need to ensure that their systems are driving measurable value for both users and the business.
Memorable Quotes
Chapter 1. The What and Why of Continuous Discovery. 14
Let’s start at the beginning. All product teams do a set of activities to decide what to build and then do a different set of activities to build and deliver it. While you’ll learn that these activities can and should overlap and interweave with each other, the work that is required to do each is fundamentally different. In this book, I’ll refer to the work that you do to decide what to build as discovery and the work that you do to build and ship a product as delivery.
Chapter 2. A Common Framework for Continuous Discovery. 22
“If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.”
Chapter 3. Focusing on Outcomes Over Outputs. 39
“An outcome is a change in human behavior that drives business results.”
Chapter 4. Visualizing What You Know. 52
“If we give each other time to explain ourselves using words and pictures, we build shared understanding.”
Chapter 5. Continuous Interviewing. 61
“People don’t know what they want until you show it to them. That’s why I never rely on market research. Our task is to read things that are not yet on the page.”
Comparative Analysis
While this book shares a great deal with other books in the field, its unique contribution is the practical application of continuous discovery. It is not a book about theory, but about practice. The book shares dozens of examples from product trios who have successfully applied the methods, and while it acknowledges the impact of modern research on these methods, it isn’t a research book, either. For product people who are seeking guidance on how to get started with continuous discovery or how to improve their practice, this book is a must read. The book covers much of the same ground as Marty Cagan’s INSPIRED, but with a heavier focus on the early stages of the discovery process. For readers looking for a deeper dive into assumption testing, David Bland’s Testing Business Ideas is a great choice. For those who want to dive deeper into qualitative testing methods, I recommend Laura Klein’s UX for Lean Startups. And for teams who are struggling to adopt an outcome mindset, I suggest Christina Wodtke’s Radical Focus.
Reflection
Continuous Discovery Habits presents a compelling argument for shifting from an output-driven product development process to an outcome-focused one. The author’s extensive experience coaching product teams lends credibility to the practical advice and real-world examples shared throughout the book. While the emphasis on continuous customer learning and assumption testing is valuable, the book could benefit from a more nuanced discussion of quantitative data analysis and A/B testing, particularly in the context of AI and machine learning, where large datasets play a crucial role. The book primarily focuses on qualitative research methods, which are valuable for uncovering customer needs and testing early assumptions, but may not be sufficient for optimizing complex AI systems that require robust statistical validation. Additionally, the book’s focus on relatively small teams and short development cycles may not fully address the challenges of developing large-scale AI products that require extensive collaboration and long-term planning. Despite these limitations, the book provides a valuable framework for continuous discovery and a strong foundation for building better products. The emphasis on customer-centricity, outcome orientation, and assumption testing is particularly relevant for AI product engineers who need to ensure their systems are aligned with user needs and deliver tangible value.
Flashcards
What is an outcome?
A change in human behavior that drives business results
What are business outcomes?
Metrics that measure how well the business is progressing
What are product outcomes?
Metrics that measure how well the product is moving the business forward
What is a product trio?
A product manager, a designer, and a software engineer working together to develop products for their customers
What are opportunities?
Customer needs, pain points, and desires, collectively
What is an opportunity solution tree?
A visual representation that helps us map out and understand the paths to reach a desired outcome
What does an experience map represent?
The customer’s experience as it currently is
What is the working definition of continuous discovery in the book?
At a minimum, weekly touchpoints with customers by the team building the product, where they conduct small research activities in pursuit of a desired outcome
What is an interview snapshot?
A one-pager that captures your key learnings from a customer interview
What are the five assumption categories discussed in the book?
Desirability, Viability, Feasibility, Usability, and Ethical