Let's discuss prototyping on a shoestring by focusing on key assumptions, then building and testing a clear hypothesis using data and analytics.
The Build, Measure, Learn cycle, also known as The Lean Startup methodology, is a systematic entrepreneurship approach focusing on rapid experimentation and iteration. Eric Ries popularized it in his book "The Lean Startup." I love this approach because I've seen it help entrepreneurs many times.
According to this approach, startups should focus on building a minimal viable product (MVP) and then measuring its performance through analytics and other forms of data. Based on this data, the startup can make informed decisions about what to do next, whether iterating on the MVP, pivoting to a new direction, or scaling up.
Prototyping on a shoestring refers to the idea that startups should aim to create prototypes or MVPs with limited resources, often using agile development techniques and lean principles. This allows them to test their assumptions quickly and cheaply rather than investing a lot of time and money into a product that may not be viable.
One key aspect of the lean startup methodology is focusing on critical assumptions or the underlying beliefs that drive a startup's product development and business model. Then, by testing these assumptions through data and analytics, startups can better understand their customers and the market and make more informed decisions about moving forward.
Overall, the Build, Measure, Learn cycle and the lean startup approach are designed to help startups build products and businesses grounded in reality and responsive to customer needs. By continuously testing and iterating on their ideas, startups can minimize risk and maximize their chances of success.
Entrepreneurs can follow these steps to apply the Build, Measure, Learn cycle to their product idea:
Define the problem: Start by defining the problem you are trying to solve with your product. Identify your target customer and the specific pain points or needs your product will address.
Identify key assumptions: Next, identify the fundamental assumptions that underlie your product idea. These might include beliefs about what features your customers will value, how you will reach and acquire customers, or how you will generate revenue.
Build a minimal viable product (MVP): Based on your key assumptions, create a minimal viable product (MVP) that allows you to test these assumptions as cheaply and quickly as possible. An MVP is a basic version of your product that includes only the essential features required to solve the problem and test your assumptions.
Measure performance: Once you have an MVP, start collecting data on how it is being used and how it is performing. This could include metrics such as customer acquisition, retention, and revenue.
Analyze results and learn: Based on the data you collect, analyze the results to understand how your MVP is performing. Use this information to validate or invalidate your key assumptions and determine what to do next. If your MVP is successful, you may want to iterate on it or scale up. If it is not performing as expected, you may need to pivot to a new direction or make significant changes to your product or business model.
Iterate and repeat: Continuously repeat the Build, Measure, Learn cycle by testing new assumptions, building new MVPs, and collecting and analyzing data. This will help you refine your product and business model over time and increase your chances of success.
This method will increase your likelihood of success by validating assumptions and demonstrating value over time.
