Wow ! I think it is great to see the comments on this thread. Thanks jwillgoesfast for asking this question.
I have actually been working on building a Product/Market Fit (Customer Dev) as Service product for the last 12 months and before that I had been advising (mostly on shaping up ideas to get the product definition right) / helping out two new startup teams every month, for about 7 years now. This happened primarily because I enjoy meeting startups and because I was part of a large alumni network which would reach out.
The key assumption for the P/M-F service is whether something like this can be scalable and work in a self-serve mode (i.e. where I am not in the room)
So I have kept iterating on the framework, took inputs from the founders I had advised in the past. My key question to them was "How did I help you even though I was not really a expert in the marketing you were targeting?"
I also conducted lean canvas workshops with startups in US and India (and across sectors including one 7-year old pharma company trying to launch a product) till I could start standardizing (so that it could then be coded into software) the P/M-F process and build a self-serve tool. The tool has now taken the shape of an "intelligent" software which asks startup founders questions and assigns them tasks to do.
There is a lot of complexity in the tool. And it needs to be much more intelligent as well. We have explored using machine learning at the backend, but so far the intelligence is based more on a decision tree structure, rather than any machine learning.
Currently in private alpha, testing with some startups and an accelerator, and will release this soon for others, hopefully by end of this month.
I have actually been working on building a Product/Market Fit (Customer Dev) as Service product for the last 12 months and before that I had been advising (mostly on shaping up ideas to get the product definition right) / helping out two new startup teams every month, for about 7 years now. This happened primarily because I enjoy meeting startups and because I was part of a large alumni network which would reach out.
The key assumption for the P/M-F service is whether something like this can be scalable and work in a self-serve mode (i.e. where I am not in the room)
So I have kept iterating on the framework, took inputs from the founders I had advised in the past. My key question to them was "How did I help you even though I was not really a expert in the marketing you were targeting?"
I also conducted lean canvas workshops with startups in US and India (and across sectors including one 7-year old pharma company trying to launch a product) till I could start standardizing (so that it could then be coded into software) the P/M-F process and build a self-serve tool. The tool has now taken the shape of an "intelligent" software which asks startup founders questions and assigns them tasks to do.
There is a lot of complexity in the tool. And it needs to be much more intelligent as well. We have explored using machine learning at the backend, but so far the intelligence is based more on a decision tree structure, rather than any machine learning.
Currently in private alpha, testing with some startups and an accelerator, and will release this soon for others, hopefully by end of this month.
http://www.uberstarter.com