The Lean Startup is a book, by Eric Ries, which highlights Japanese manufacturing rapid-prototyping methodology as great approach for software development. Rather than doing time consuming market research and then building a finished product that you hope people will like, the Lean approach advocates building an early stage iteration and releasing it immediately for users to comment on and guide it’s development, by quickly releasing updates and monitoring their effect.
Our business has recently launched a new product that is potentially going to be a really useful to it’s target audience. We’re taking a “lean” approach to it’s production and have put up a very early stage BETA version on the site that people can register (with a wufoo form linked to a mailchimp account) for and download (using dropbox).
From the outset users are made aware that they are downloading a development product. Once they have downloaded it they enter into a chain of 9 mailchimp auto-responder emails ( 1 every 5 days) set up to incentive them to give us feedback. The emails are written very delicately and aim to be fun to read and warm people to us.
In return for giving us feedback, we offer them some very decent incentives: one of our other products completely free, the finished version of this product (they can only currently download the free version, the full version has not been built yet) at a massive discount, the option of buying all of products and getting this product free, and, of course, our eternal gratitude.
The aim of the feedback we receive is to guide our future shaping of the product, in terms of content (it is a learning resource), price (we can vary this to measure uptake), and delivery method.
We will know that the Lean experiment has been a success if we manage to tweak (based on user feedback) the above factors to the point where users are madly sharing the free product around, we have got great feedback that the product achieves its learning objectives, and that people are pre-ordering the full version before it is released.
Can we improve this experiment? Let me know..