How do you balance testing product assumptions with delivering value and solving problems?

Some changes are reversible and others are irreversible. When prioritizing tests, focus on the ones which will be irreversible changes to your product.

Assumptions can be categorized into three different types: problem, solution, and implementation. One approach that I find useful is to use a problem statement, which clearly and concisely describes the pain point or opportunity that the product aims to address. This helps focus on the customer's needs and the value proposition of the product.

One approach I've found useful in identifying opportunities is to map out the entire customer journey of your product, and overlay the conversion %s from screen to screen to see the dropoffs. Gantt charts can be useful to help with this visualization. Next, look for the areas of greatest drop-off. Do they seem to follow your intuition? Why or why not? By comparing and contrasting the observed data with your expectations, you'll be able to quickly whittle down the opportunity set to the highest-impact areas to focus on.

Follow the CIRCLES method. Note there are 4 types of product assumptions. Clearly lay out what needs to be true for the product to be successful. 1. Desirability assumptions 2. Viability assumptions 3. Feasibility assumptions 3. Usability assumptions

Em um fluxo saudável de melhoria continua esse processo deveria se auto resolver, mas caso esse processo n?o exista implementar partes de sustenta??o do SRE podem fazer com que o time ganhe essa maturidade.

The diversity of testing methods from interviews to analytics ensures a well-rounded understanding of your product in the real world. Tailoring these methods to your specific assumptions can unearth rich, actionable insights, directly impacting product development with precision. Use the method that best aligns with the nature of your assumption, balancing depth with breadth to gather meaningful data.

Selecting the right methods for testing is key. A/B testing, user interviews, and data analysis have been my go-to tools. For example, while working on increasing B2B MQLs, we leveraged A/B testing extensively to understand what resonated best with our target audience, focusing on both content and delivery channels.

- Identify Appropriate Testing Methods for Each Assumption ???? - Consider a Mix of Qualitative and Quantitative Approaches ???? - Choose Methods That Align with the Nature of the Assumptions and the Product ????? - Prioritize Methods That Provide Insights into User Needs and Preferences ????? - Utilize Prototyping and User Testing for Early Validation ??????? - Conduct Surveys or Interviews to Gather User Feedback ????? - Analyze Market Trends and Competitor Strategies ???? - Implement A/B Testing or Pilot Programs to Compare Different Approaches ?????? - Iterate and Refine Testing Methods Based on Results and Feedback ???? - Continuously Monitor and Adjust Testing Methods Throughout the Product Lifecycle ????

When considering how to test your assumptions and goals, you have various methods to choose from based on your specific needs. Interviews are valuable for gaining insights into customer needs, preferences, pain points, and feedback in a more qualitative manner. Surveys provide a way to collect quantitative data from a broader audience, offering insights into larger trends and patterns. Experiments allow you to test assumptions in controlled or real-world settings, providing concrete evidence of their validity. Additionally, analytics tools like Google Analytics and Mixpanel can be instrumental in validating assumptions by analyzing actual user behavior and engagement metrics.

Interviews provide qualitative insights into customer needs, preferences, and pain points, enabling a deeper understanding of user perspectives. Surveys, on the other hand, are valuable for collecting quantitative data from a broader audience, offering statistically relevant insights. Experiments allow for hypothesis testing in controlled or real-world scenarios, providing empirical evidence to validate assumptions. Additionally, leveraging analytics tools such as Google Analytics and Mixpanel enables the examination of actual user behaviors, validating assumptions with real data.

Evidence-based conclusions drive product evolution, steering you clear of costly misdirection. Embrace the outcomes of your tests, whether they pivot, persevere, or iterate, as each provides a clear path forward. This rigorous validation process not only refines your product but also builds a stronger, evidence-backed strategy.

Transforming data into actionable insights is key. Analyze your findings through frameworks like Lean Startup or Validation Board. This reveals if your initial assumptions hold true. Based on the results, pivot, persevere, or iterate: invalidated assumptions necessitate strategic shifts, validated ones allow further development, and partial validation suggests targeted adjustments. Ultimately, use data to guide your product's journey, whether refining its direction, solidifying its strategy, or charting a course correction.

- Define Clear Criteria for Validating or Invalidating Assumptions ???? - Gather Data and Evidence to Test Each Assumption ???? - Utilize Both Qualitative and Quantitative Methods for Validation ???? - Analyze Feedback from User Testing and Market Research ????? - Compare Assumptions Against Real-world Observations and Metrics ???? - Look for Patterns and Trends in Data to Inform Decisions ???? - Iterate and Refine Assumptions Based on Validation Results ???? - Communicate Findings to Stakeholders and Development Team ????? - Adjust Product Strategy and Roadmap Accordingly ????? - Continuously Monitor and Re-evaluate Assumptions as the Product Evolves ????

After analyzing your data, use frameworks like Lean Startup or Validation Board to interpret findings. Determine if assumptions are validated or invalidated and decide next steps: pivot, persevere, or iterate. For invalidated assumptions, consider changing product strategy. Validated assumptions guide product development. Adjustments may be needed for partially validated assumptions. Acting on these insights refines your product and boosts market success

Once you have collected and analyzed your data, it's crucial to interpret the results and draw conclusions. Use frameworks like the Lean Startup or the Validation Board to organize and communicate your findings. These tools help you determine whether your assumptions are validated or invalidated by the evidence and guide your next steps. If an assumption is invalidated, you might need to pivot and change your product's direction or strategy. If it is validated, you can continue building and improving your product or feature. If the assumption is partially validated, consider making adjustments or additions to your product. This approach ensures that your product development is evidence-based and aligned with market needs.

Continuous testing intertwined with product development ensures you're always on the right track, delivering real value. Adopt an iterative approach, where each test informs the next step, keeping the product development agile and aligned with customer needs. This balance is crucial; it ensures that your product remains relevant and impactful without getting lost in an endless cycle of testing.

- Define Clear Objectives for Testing and Delivering Value ???? - Prioritize Assumptions and Problems Based on Impact and Importance ???? - Allocate Resources and Time According to Priorities ???? - Utilize Agile or Lean Methodologies to Iterate Quickly ????♂? - Conduct Incremental Testing While Continuously Delivering Value ????? - Implement Feedback Loops to Gather Insights and Adjust Priorities ???? - Maintain Flexibility to Adapt Testing Plans Based on Emerging Needs ???? - Communicate Progress and Adjustments Transparently with Stakeholders ????? - Regularly Review and Reassess Testing and Delivery Strategies ???? - Strive for a Balanced Approach that Supports Both Testing and Delivery Goals ????

Testing assumptions continuously informs and shapes product evolution, ensuring that value creation and problem-solving remain central to product efforts. Balancing testing with delivery involves adopting agile principles, such as testing early and often using minimum viable products (MVPs) or features to gather actionable feedback efficiently. Smart and selective testing focuses on prioritizing critical and risky assumptions, optimizing resource allocation, and maximizing insights. When testing, having a clear purpose, hypothesis, and an open, critical mindset fosters meaningful learning and informed decision-making. By following these strategies, uncertainty is reduced, confidence is increased, and product development is steered.

Iterative Validation: Embrace a continuous testing cycle to consistently validate and refine product assumptions, ensuring alignment with customer needs through iterative feedback and rapid prototyping. Strategic Testing: Prioritize testing the most critical and uncertain assumptions using Minimum Viable Products (MVPs) or features, balancing the need for thorough validation with timely delivery of value to customers. Purposeful Hypothesis: Approach each test with a clear hypothesis and objective, maintaining an open yet critical mindset to adapt based on findings, thereby reducing uncertainty and enhancing product decision-making.

While testing underpins successful product development, it's an ongoing dialogue, not a monologue. Continuously validate assumptions through low-risk MVPs and features, prioritizing testing the riskiest aspects. Approach each test with intent, hypotheses, and open-mindedness to learn from your findings. This iterative process reduces uncertainty, builds confidence, and guides decisions, ultimately shaping a product that truly solves customer problems and delivers lasting value.

Every product journey is unique, filled with unexpected insights and challenges that textbooks don't cover. Share these stories widely; they're invaluable for the community and can spark innovation or offer solace. Remember, the shared wisdom from real-world experiences often provides the best guidance for navigating the complex landscape of product development.

- Ensure Alignment with Overall Product Vision and Goals ???? - Foster Collaboration Between Testing and Delivery Teams ???? - Encourage a Culture of Experimentation and Learning ???? - Set Realistic Expectations for Testing and Delivery Timelines ??? - Seek Continuous Feedback from Users and Stakeholders ????? - Monitor Key Performance Indicators (KPIs) to Measure Progress ???? - Stay Agile and Adapt to Changing Market Conditions ???? - Celebrate Successes and Learn from Failures ???? - Invest in Tools and Technologies to Streamline Testing and Delivery Processes ????? - Regularly Review and Reflect on Testing and Delivery Practices for Continuous Improvement ????

- Speed vs. Quality: Rapid testing can lead to fast results, but ensure the quality of insights isn’t compromised. - Stakeholder Communication: Keep stakeholders informed about the testing process and outcomes. This transparency helps manage expectations and demonstrates the value of thorough testing. - Iterative Learning: Every test, whether successful or not, provides valuable insights. Adopting an iterative approach to testing and product development ensures continuous improvement and learning. Remember, the goal is not just to test but to learn and adapt quickly, ensuring that every step taken is one towards greater value creation and problem-solving for your users. ??