How do you validate and test your assumptions based on customer empathy maps?

Priorizar las suposiciones críticas e inciertas es clave en el desarrollo de innovaciones. Las críticas, si son incorrectas, pueden invalidar la propuesta de valor, y las inciertas carecen de evidencia de respaldo. Use una matriz de prioridad para clasificar estas suposiciones, enfocándose primero en aquellas que son críticas e inciertas. Esto asegura una validación temprana que fortalece su modelo de negocio.

Customer empathy maps are a collaborative tool that help you and your team visualize your customer’s needs and allow you to separate what you think your customer wants from what your customer really wants. You need to consider what your customer says, does, thinks and feels.

Prioritizing assumptions is fundamental in innovation. It’s essential to distinguish between what’s known and unknown. For instance, when I developed a new beverage, I assumed taste was the priority. However, market analysis revealed that health benefits were paramount. This led to a pivot towards nutritional value without compromising on flavor, addressing both critical and uncertain assumptions effectively.

Assumptions can also be broadly grouped into [problem], [customer], [solution]. Prioritize derisking assumptions around the problem and customer before focusing on potential solutions. If the problem doesn't exist (or significant enough) for the described customer segment, not point in testing a solution at this stage.

To validate assumptions with customer empathy maps, first use the maps to understand customers' needs and pain points. Then, form hypotheses about potential solutions and create prototypes or MVPs. Conduct user testing with a target audience segment to gather feedback. Analyze this feedback to see if it confirms or challenges your assumptions. Iterate on your solution based on insights gained, refining your product or service to better align with customer needs through a cycle of empathy, experimentation, and feedback.

Formular hipótesis claras facilita probar suposiciones y medir resultados. Ejemplo: "Creemos que la falta de acceso rápido a información para peque?os empresarios se resuelve con una plataforma móvil accesible. Sabremos que es cierto cuando el uso de la app aumente un 30% en seis meses." Esto define el aprendizaje y las métricas clave, orientando el proceso de validación hacia resultados medibles y claros.

Don’t hypothesize. Empathize. The genius of human empathy? It allows you to dispense with assumptions. Best to stop hypothesizing and start learning the perceived reality of your actual audience. “So you find banking complex? Tell me about that!” Soon you’re exploring anxieties around savings, challenges of numeracy, insecurities about the future, hidden pains from childhood, dashed hopes amid inspired dreams, hopes and aspirations. The wonder of the human condition is that we all operate in our own unique contexts. By interrogating personal individual experiences you discover that your flawed assumptions would have slowed you down, led you astray, or produced the wrong solution to a problem you only belatedly came to understand.

After consulting executive leaders and leading $1M high-stakes projects primarily in pharmaceutical and healthcare, we start nearly all of our innovation engagements by looking at our biases and filling in an assumption map. After mapping our assumptions across interest categories, we plot the riskiest and most critical to address in our test. The following exercise is to check our biases: optimistic bias, confirmation bias, availability bias, etc. The influences behind your assumptions are essential to raise to the surface. Once you have these two foundational pieces ready, you can move on to defining your specific hypothesis based on the assumptions to debunk.

A partir de meras suposi??es você precisa elaborar uma ou mais hipóteses. As hipóteses s?o caminhos efetivamente criados para a resolu??o de um problema. A partir daí você precisa usar meios claros de checar se a sua hipótese está correta ou se ela precisa ser descartada. Portanto, n?o se apegue às suas hipóteses por melhores que elas pare?am ser. Pode ser que ela se provem erradas, e o ganho com isso é muito grande também.

Clearly define each assumption and outline how it relates to your customers’ needs, pain points, and desires, as captured in the empathy map.

Experimentar con suposiciones es fundamental para validar ideas. Pruebe su hipótesis con clientes reales mediante entrevistas, encuestas, prototipos o pilotos, según su objetivo y recursos. Por ejemplo, una encuesta rápida puede confirmar el interés en una nueva función, mientras que un prototipo ayuda a ver reacciones directas. Seleccione el método adecuado para obtener resultados confiables y minimizar riesgos.

A few of my favorite examples of experiments: Airbnb founders tested their concept by renting out air mattresses in their apartment to conference attendees, validating the viability of peer-to-peer room sharing. Dropbox used a simple explainer video to validate customer interest in online storage, significantly boosting its waitlist without building the full product first. Zappos validated demand for online shoe purchasing by posting shoe photos online and then running to purchase from stores after receiving an order.

A/B testing never fails ! You'll succeed or you'll learn anyway. So get a lot of options/assumptions to try! At times, you may completely go in the wrong direction, and this is the beauty of SERENDIPITY !

Innovation thrives on experimentation. My approach has always been to start small and scale with success. For instance, when testing market viability for a new product, I began with A/B testing on landing pages, which provided clear, actionable data without extensive resource investment. This method not only validated the product concept but also refined our marketing strategy, proving crucial for the product’s eventual success.

As suposi??es devem ser validadas com base em dados reais, coletados diretamente com os usuários. Métodos como entrevistas com clientes, questionários ou grupos focais podem ser úteis. Ao fazer perguntas específicas que desafiam as suposi??es do mapa de empatia, é possível verificar se essas percep??es refletem verdadeiramente a realidade dos clientes.

El cuarto y último paso es aprender de sus suposiciones mediante el análisis de los datos y comentarios que recopiló de sus experimentos. El aprendizaje no se trata solo de confirmar o rechazar su hipótesis, sino también de descubrir nuevos conocimientos y oportunidades de mejora. Puede utilizar herramientas como el lienzo lean, el tablero de validación o la tarjeta de aprendizaje para documentar y comunicar sus hallazgos. En función de su aprendizaje, puede decidir si pivotar, perseverar o iterar en su desarrollo de innovación.

Analyze the results of the experiments to determine whether the assumptions hold true or need to be adjusted. If the assumptions are validated, incorporate them into the product or service development process. If they are disproven, iterate on the assumptions and design new experiments to gather additional insights.

Learning from assumptions is a cornerstone of innovation. In my endeavors, I’ve found that it’s not just about validation but also about uncovering hidden opportunities. For example, when testing a new food packaging concept, customer feedback led to an unexpected yet valuable pivot towards eco-friendly materials, which significantly enhanced the product’s appeal and aligned with the growing environmental consciousness among consumers. This experience underscored the importance of being receptive to feedback and ready to adapt, ensuring that innovation is both responsive and responsible.

Na minha vis?o, uma boa prática é usar quadros de valida??o para organizar e analisar o feedback coletado. Isso facilita a identifica??o de novos insights e oportunidades, ajudando a tomar decis?es informadas sobre continuar, ajustar ou mudar a dire??o de suas iniciativas de inova??o.

Analyze the results of your experiments to extract insights. Use this feedback to refine your understanding of customer needs and iterate on your solutions, ensuring alignment with the empathy map.

Prioritize Your Assumptions: Identify the most critical assumptions derived from your empathy maps that directly impact your product or service. Focus on those that hold the highest risk if incorrect. Hypothesize Your Assumptions: Formulate hypotheses around these assumptions, detailing what you expect to learn from testing them and how they relate to customer needs and behaviors. Experiment with Your Assumptions: Design experiments or prototypes to test your hypotheses. This could involve surveys, interviews, A/B testing, or developing minimum viable products (MVPs) to gather feedback. Learn from Your Assumptions: Analyze the results of your experiments to understand whether your assumptions were correct.

Iterative Approach: Recognize that the validation process is iterative and may require multiple rounds of experimentation and refinement. Cross-functional Collaboration: Involve cross-functional teams, including designers, developers, marketers, and customer support, in the validation process to gain diverse perspectives and ensure alignment.