You’re trying to get your startup off the ground. How can you ensure your idea is viable?

1 Define your problem and solution

The first step is to define your problem and solution clearly and concisely. What is the pain point or need that your product addresses? Who are your target customers and what are their characteristics? How does your product solve the problem or satisfy the need? How is your product different from existing alternatives? You can use tools like the lean canvas or the value proposition canvas to help you articulate your problem and solution hypotheses. These are simple frameworks that help you map out the key elements of your business model and value proposition.

2 Measure your assumptions and metrics

The next step is to measure your assumptions and metrics. You need to identify the most critical assumptions that your idea depends on, and the metrics that you will use to test them. For example, if your assumption is that people will pay for your product, your metric could be the number of pre-orders or sign-ups. If your assumption is that people will use your product frequently, your metric could be the retention rate or the usage frequency. You can use tools like the assumption mapper or the validation board to help you prioritize your assumptions and metrics. These are visual tools that help you organize your assumptions and metrics into categories and rank them by importance and uncertainty.

3 Experiment with your idea and data

The third step is to experiment with your idea and data. You need to design and run experiments that will test your assumptions and metrics with real or potential customers. Experiments are ways of collecting data and feedback that will either validate or invalidate your hypotheses. For example, you can experiment with your idea by creating a landing page, a prototype, a minimum viable product (MVP), or a pilot. You can experiment with your data by using algorithms such as A/B testing, cohort analysis, or customer segmentation. These are methods of comparing different versions of your product, measuring the impact of changes, or identifying patterns and preferences among your customers.

4 Learn from your results and feedback

The final step is to learn from your results and feedback. You need to analyze the data and feedback that you collected from your experiments, and draw conclusions and insights. Did your experiments validate or invalidate your hypotheses? What did you learn about your problem, solution, customers, and business model? How can you improve your product, value proposition, or market fit? You can use tools like the lean analytics cycle or the build-measure-learn loop to help you learn from your results and feedback. These are iterative processes that help you apply your learning to your next actions and decisions.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?