How can you ensure unbiased and accurate MVP validation techniques?

Pichler's Product Visions Board is a great starting point. It's a great tool to help frame the problem you're trying to solve. The Product Vision board gets you thinking about the market or market segment the product addresses; the need or the problem solved; what's the product and why is it different to other products in the same market segment; the business benefit your product brings. This is a great way to communicate how your product aims to solve the problem and enables stakeholders to feed in and challenge.

In my journey as a founder, one thing I observed was the critical role of embracing a 'lean startup' mindset. We often fell into the trap of 'solution bias', being too infatuated with our product. To combat this, we adopted a rigorous, hypothesis-driven approach. We asked, "What are the core assumptions?" and "How can we test them with minimal resources?" MVP validation is more than a step in the product development process; it's a mindset that embraces flexibility, customer-centricity, and data-driven decision-making. This approach not only validates your product but also strengthens your team's ability to adapt and thrive in a competitive landscape.

One of the effective ways of unbiased validation for an MVP is direct user testing in two way. First, the product has to be made available to a focus group who would use the product to specific use cases and share their feedback. Secondly, providing free access to the product for a limited time with most prominent features test the company is planning to pivot on will provide an unbiased evaluation. Thus the data from both the focus group and the freemium users can be used to understand the product behaviour in use cases and popular features. To understand the price point, the company can either choose a penetrating price or a skimming price strategy depending upon the market they are entering and the incumbent competition.

In my experience, a recurring challenge that I've seen in trying to define a hypothesis continues to be the difficulty in staying in the problem space, naturally, people want to "solve the problem" or "answer the questions" in the moment. Focusing on setting up a strong hypothesis encourages alignment with the product vision while also providing a direct line to learning. I've seen too many organizations hand-wave this step at their peril. This step is both crucial and humbling.

Avoid confirmation bias Confirmation bias is where we seek out and interpret information that confirms our existing beliefs. When validating your MVP, we should be careful not to ignore or dismiss information that contradicts your expectations.

Choosing the right validation method for your MVP (Minimum Viable Product) is crucial, and it's a decision that should align with your specific hypothesis, resources, and product stage. Like prototypes are best for user experience and design feedback. They give a tangible form to your idea without full development. A prototype can range from a basic wireframe to an interactive model. For instance, Airbnb's initial prototype helped them iterate on their booking flow based on early user feedback.

For the recent rollout of a generative AI feature on an e-commerce platform, I initiated a pilot program, prioritizing a clear understanding of the target audience to customize our feedback approach. Given the nuances of emergent technologies like generative AI, it was crucial to address ethics, trust, and privacy head-on. Opting for individual feedback sessions allowed me to gather direct and frank insights, fostering an authentic exchange of ideas in real time. This progressive loop of feedback, where each session informed and improved the next, proved essential for a seamless and effective launch.

Here, I would recommend refer to OPA documents to get the lesson learned directory, so that we can build our own dictionary of what would not be good or best, this will let us know what we are not going to do. Knowing what option or techniques are not relevant, will do half of your work. With appropriate testing or validation methods, the product will be an optimised version.

Don’t limit your audience to the economic buyer. Using a persona matrix to ensure you collect feedback from the technical buyer, economic buyer, compliance buyer and end users are essential to getting diverse feedback. It helps to ensure you are including customers from all industry segments.

An essential aspect of unbiased MVP validation is adopting iterative feedback loops, especially to help identify and correct biases early. Iterative feedback involves repeatedly testing, obtaining feedback, and refining the MVP. This process should not be a one-time activity but a continuous cycle that evolves with your MVP. For instance, with prototypes, gather user feedback on usability and feature set, then refine the prototype accordingly. In Beta testing, use user feedback to fix bugs and enhance features, then release updated versions for further testing. This approach not only helps in fine-tuning your MVP but also ensures that the validation process remains dynamic and adaptable to user needs and expectations.

In my experience, the best way to quickly validate a MVP is to build lean and fail fast and when you fail (and that will happen often), pivot quickly. But before you do that, the most critical part is identifying your correct target audience and getting your product in front of them quickly and efficiently. The precision in understanding your target audience will not only help you validate your MVP but also push your product towards product-market fit

Finding a target audience nowadays is not difficult, converting the same into a relevant audience is the task. One of the best ways I believe can offer great insight is the grievance cell or consumer courts, if we can have access to customer pain points or issues, then what they actually want or looking out will become easy to find. Subsequently, any other method can be used to identify the target audience.

When validating our MVP for an online platform to help students find study partners, we used a Google Form. It was an effective, low-cost way to gauge interest and gather insights. The form asked about study habits, partner preferences, and challenges in finding study mates. The responses were eye-opening, revealing a strong demand and specific features students desired, like chat functions and schedule matching. One memorable feedback came from a transfer student struggling to find a study group during remote learning, highlighting our platform's potential impact. This simple validation step was crucial in shaping our MVP to meet real student needs.

If you're having difficulty figuring out how to select/reach your target audience, perfect is the enemy of good. You don't need the perfect selection criteria. It's more important to start with some initial assumptions and verify if you're reaching the right target from the responses. Start small and test, you don't need to only do one large expensive engagement.

Target audience can be found in many ways. Thanks to meetups, conferences and online media ... one can find ways to reach the audience. It is also equally important to understand the skill maturity levels of the persona in your target audience, especially for enterprise SaaS products. One will find that the responses to MVP prototypes will differ significantly based on the work context in which the persona operates.

Consider implementing a "contextual feedback" approach. Instead of only collecting feedback in a controlled environment, gather insights in the context where users naturally interact with your MVP. This could involve observing user behavior in real-life scenarios or collecting feedback at the moment of user interaction. Contextual feedback provides a more authentic understanding of user experiences and helps uncover insights that might be missed in traditional feedback collection settings.

Ensuring unbiased and accurate MVP validation involves a methodical approach to collecting and analyzing feedback. Use diverse methods like surveys, interviews, analytics, and user testing to gather comprehensive insights. Crafting open-ended, neutral questions helps prevent bias in responses. Segmenting and sampling your audience based on relevant criteria ensures you're capturing diverse perspectives and needs. Testing multiple MVP variations allows for comparative analysis, providing a clearer picture of what resonates best with your audience. Balancing both qualitative and quantitative feedback, and corroborating them with other evidence, provides a more holistic and accurate validation of your MVP.

Remember, the goal is not just to collect data but to interpret it in a way that genuinely informs your product development decisions. Quantitative data from surveys or analytics provides measurable insights into how users interact with your MVP, such as usage patterns or feature popularity. Qualitative data from interviews or open-ended survey questions, on the other hand, offers depth and context, revealing why users behave a certain way or prefer certain features. For instance, if quantitative data shows a feature is rarely used, qualitative insights can explain why. This triangulation helps in validating the accuracy of the feedback and provides a more rounded understanding of user experiences and perceptions.

Iteration is at the heart of Agile methodology. After validating your MVP, it's vital to apply the feedback in iterative cycles. This means not just making incremental improvements but also being ready to pivot if the data suggests a different direction is needed. Documenting these iterations and sharing them with stakeholders and team members is crucial for transparency and continuous improvement. Each iteration should be viewed as an opportunity to learn more about the product and customer needs. The key is to maintain a balance between speed and thoroughness – iterate quickly but ensure each cycle is informed by robust analysis of user feedback.

Introduce a "wild card" element in each iteration. Encourage your development team to experiment with a new and unexpected feature or improvement that isn't directly aligned with the initial feedback. This creative wildcard can sometimes lead to innovative solutions and unexpected positive outcomes, fostering a culture of continuous improvement and adaptability.

Here I cannot help highlighting the beauty of Agile method. While repeating all ceremonies, such as stand up/backlog grooming/planning/sprint review/retrospective meeting, there are continuous iterative review and wonderful opportunities of improvement. Especially there is no harm to demo as part of sprint review for different business stakeholders, by splitting this demo for each different audiences, they are more comfortable to express their frank opinion for future improvement. Keep repeating is always best!

Iterations and improvements are key to success. It is a chicken and egg situation at times. We need to pyritize iterations based on the 'MAX IMPACT' items and which would take us to closer to our goals or which would serve a max number of users.

Continuous iteration is vital for unbiased and accurate MVP validation. Use feedback to validate or invalidate hypotheses and learn about customers and the product. Apply insights to iterate and improve the MVP or pivot as needed. Document and communicate findings to stakeholders. The MVP validation is an ongoing, cyclical process, fostering continuous learning and product enhancement for better customer outcomes.

There are several other factors to consider in refining the MVP: User Experience Design is crucial to focus on a user-friendly interface. Users should find it intuitive and engaging. Consider incorporating elements that appeal to your target demographic, like a clean, modern design or gamification features. Plan for scalability from the start. As your user base grows, the platform should be able to handle increased traffic and data without compromising performance.

Finding the right target audience is the linchpin of accurate MVP validation. For instance, when Apple launched the iPod, they didn't just target music lovers; they focused on the intersection of technology enthusiasts and music connoisseurs. The precision in identifying your audience ensures not just validation but a resonating product-market fit.

Pricing - a key element of MVP. A right pricing would be very important. Free is not always a strategy. If its free, you need to have the revenue generation plans. Else, you need to to A/B testing on pricing also before you roll out the beta version of the product.

This wouldn’t always be applicable, but if possible, it’s very important to also test the proposition. Getting a crystal clear articulation of the proposition ready for testing can be the trickiest to get right. This can then be tested separately ahead of any design work, or in conjunction with the MVP prototype. This ensures that you test the bigger picture as well as the hands-on experience.

Starting with a product-idea, identifying MVP features, validation through trial adoption, and delivering it to the market is the traditional way to engineer products. Despite two decades of experience, I now find this to be less effective than the Amazonian painful but rewarding practice leading to a MLP. This starts with a (fictitious) press release (PR) with real-customer quotes of their related pain points. The press release is augmented by frequently asked questions (FAQ) about this "product release". This PRFAQ starts with customers but is then socialized with internal stakeholders. For example, with internal finance team for pricing, legal advisor for legal considerations, with sellers for reality checks from the field, etc.