illustration - market research v1

How to Verify Your Assumptions At Small Sample Sizes

(This is a guest post by Luke Szyrmer, a Product Manager and Consultant, and author of the just released Launch Tomorrow, a book on the use of paid advertising to test, launch, and promote new products. You can find Luke on Twitter, LinkedIn or his website.)

Every block of stone has a statue inside it and it is the task of the [founder] to discover it. --Michelangelo

Your goal is to make money, not to publish peer-reviewed academic sociological research. While it's good to use the scientific method to test out a business idea, don't get lost in statistical minutiae. In particular, rigorous statistical analysis is a luxury that early stage founders can't afford. 99% certainty costs a lot of time and money. As a founder, focus on financial significance, not the rigorously high bar of statistical significance to a high level of certainty

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framework - BML Loop (1)

Guest Post: Pitching to Investors: A Lean Startup Perspective

(Andy Cars, founder of Seedcap and Lean Ventures, helps startups with strategy, business development, lean startup and fundraising, and large companies create and execute on their innovation strategies. If he’s not busy helping startups and enterprises, you can probably find him on Twitter and LinkedIn.)

Much has been written on how to pitch to investors. There's also plenty of resources available on Lean Startup. But how about pitching to investors from a Lean Startup perspective? Perhaps not so much.

Lean Startup is both a method and a mindset. If you are a Lean Startup practitioner it makes sense that your Lean Startup mindset should also to some extent carry over, or at least be noticeable, when you pitch to investors.

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illustration - focus group v1

Guest Post: Actioning Customer Discovery Interviews

(Nick Noreña, a Lean Startup Coach at TriKro, works with teams and organizations to help them implement Lean techniques in their daily business. An entrepreneur at heart, his favorite thing to do is work with early stage startups. If he’s not in his office in San Francisco, you can probably find him on a long bike ride, or on Twitter and LinkedIn.)

This is Part 2 of a two part blog post on effectively using the data you gather from customer discovery interviews. Check out Part 1 if you haven't already.

After a round of customer discovery interviews, I often find myself inundated with data. To be honest, it's a bit intimidating. I've tried lots of different approaches to organizing that data, from writing up long and verbose reports, to just giving the rest of my team the raw data and telling them to make sense of it (take a wild guess as to how well that worked). What I found was that while I had accrued lots of data I was always left begging for actionable insights.

So how do we actually interpret all of that data we worked so hard to collect?

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lean startup crew boat

Real Startup Book: Latest Update

We have a new update for the Real Startup Book available here:

For those unfamiliar with this project, please read our first update.

Updates

We updated the book's formatting to make it easier to read on computer screens Added chapters on customer discovery interviews, secondary market research, concierge test, net promotor score, and biases

Since the Real Startup Book is under Creative Commons, anyone will be able to use, remix, and rehash what we come up with under the terms of that license. If you’re not familiar with Creative Commons, it basically means the book will be like open source software: free to use for the benefit of the community.

It will also be written by the community. Everyone who contributes will be listed as an author.

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framework - lean startup playbook - generative market (1)

Guest Post: Preparing Customer Discovery Interviews

(Nick Noreña, a Lean Startup Coach at TriKro, works with teams and organizations to help them implement Lean techniques in their daily business. An entrepreneur at heart, his favorite thing to do is work with early stage startups. If he's not in his office in San Francisco, you can probably find him on a long bike ride, or on Twitter and LinkedIn.)

This is Part 1 of a two part blog post on effectively using the data you gather from customer discovery interviews. Check out Part 2 here.

As a Lean Startup coach, I get the opportunity to hear a lot of questions about the challenges of implementing Lean methodologies. One question I hear a lot is: "How do I use the data I get from customer discovery interviews?" This post is the first in a two part series on making sense of the qualitative data we get from talking with customers.

Part 1 focuses on what you can do before and during a customer discovery interview to make life easier for yourself after the conversation is done. In part 2, I will focus on finding patterns in the data you have collected.

Before the interview

Alright, so you've figured out that you should be talking to your users to learn something about your product/service. But what are you doing to prep for those conversations? How are you spending your time during those conversations? Well, the good news is that even if you don't prep for or take notes during your customer conversation, you are still doing more than the entrepreneur who is sitting at her desk all day trying to figure out what is wrong with her product. But here's how you can do more:

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