Experimental Product Design with Python (Lean Startup)

There’s been a lot of buzz about “Lean Startups,” “Customer Development,” “Business Model Generation” and related topics lately. And there is a real transformation in the way we design and build products at work behind all that buzz.

But the fundamental principle behind all of them is applying scientific and experanmental methodologies to product design decision making. The tools of Lean Startups are:

• data collection and analysis
• writing hypothesis and models
• creating experiments to test those models
• learning from those experiments, and refining/redesigning the model

Fortunately Python is a great tool for those looking to apply the tools of science to product design. Python can help with everything from statistical analysis, to rapid development of viable products, to the creation of complex models that can be used to tweak the levers of growth, and it’s easy to combine these with off the shelf tools that help you analyze traffic patterns and figure out what product changes actually make a difference.

SourceForge.net is not a lean startup, it’s an established site with 40 million unique visitors a month, but applying scientific principles and data analysis still critical to creating better experiences, and generating value for our various types of customers. And it’s my belief that all kinds of companies, charities, and even government organizations, can benefit from using python to implement these principles.

This talk will have lots of sourceforge.net examples, as well as a number of other examples from startups, and other organizations that are using these principles to create more valuable products.