What Are You Trying to Learn?
“If I had an hour to solve a problem, I’d spend 55 minutes thinking about the problem and 5 minutes thinking about solutions.”
—Albert Einstein
In school, we’re constantly taking tests to gauge how well we learned last week’s material. We cram geographic boundaries, the dates of battles, and multiplication tables into our heads, and then we spit out the results.
Those rote memorization skills used to answer set questions don’t help us as entrepreneurs. When building a new business model, there is no test or quiz that we can cram for. It’s a wildly unstructured dive into the unknown.
As an entrepreneur (or intrapreneur), we can’t build a product or solution before we figure out what the customers actually need. If we take a guess and build a fully functioning product, it’s likely that the market will judge us wrong and punish us with a silent cash register.
Our job as entrepreneurs is to first ask the right questions, and only then can we find the right answers.
Don’t Read This Book Straight Through
This book is backwards. It starts with the Index.
Do not read this book straight through. There is no plot or narrative that you’re going to miss by jumping around.
This book is not a Step 1, Step 2, Step 3 guide to building a startup. Startups don’t work like that.
Think of this book as a toolbox organized by the Index.
The Index isn’t alphabetical, chronological, or ontological. It’s ordered by what you’re trying to learn. Are you trying to learn about your customer? How to price your product? What will make your users come back?
To navigate, first we identify the question to ask and then we use the Index to navigate to the right research and experimental methods to answer that question.
Understanding the Index
The Index is organized into quadrants of market vs. product and generative vs. evaluative. The questions we ask and the methods we can use to answer those questions are listed in each of those quadrants.
It’s organized to help us find what we’re looking for when we need it. When we need a way to test market demand, there’s a section on evaluative market experiments. When we’re looking to prioritize our ever-growing feature list into a minimum viable product, there’s a section on generative product research.
If you’re not familiar with those terms, do not panic.
This is not an overly technical manual although there is some jargon. This book is written for everyone.
The Foundations section will walk you through the process of identifying business risks, turning them into questions, classifying them into the quadrants, and understanding the methods themselves.
If you’re already familiar with those distinctions and are ready to jump in… go for it! Find the right quadrant for your key question and jump straight to the individual method pages to find real answers.
A Typical Journey
When starting a new business, a team might go through the four quadrants of this book in sequence:
- Generative Market Research — Interview customers, discover a clear market segment, and prioritize the pain point with the biggest impact.
- Evaluative Market Experiments — Test the pain point with a landing page value proposition test and confirm willingness to pay.
- Generative Product Research — Observe customers, ideate with them, and try to solve the pain manually with a concierge test. Narrow in on one clear solution that might scale to a full business.
- Evaluative Product Experiments — Test solutions with increasing levels of complexity. Start with a quick prototype, then iterate with A/B tests all the way to a full product, until customers are using it daily.
But most paths are not straight lines. Most teams repeat each quadrant multiple times or move backwards as they learn more about their customers and their market.
The Backwards Journey
The most common mistake for a new business is starting in the wrong quadrant.
A team builds a prototype, throws up a landing page A/B test, gets a 1.5% conversion rate, and concludes “no one wants this.” But the test was an Evaluative Product Experiment run before any Market hypothesis was established — so the data is misleading.
Was conversion low because the product is wrong? Because the audience is wrong? Because the pricing is unclear? Because the segment never had the pain at all? With no market hypothesis behind the test, every possible cause is still in play.
It’s common for more mature businesses to start with an established market hypothesis already validated by an existing business. Even so, those teams usually find they still need to go back to generative research — to re-segment the market and understand how customer needs have changed over time.
As a rule of thumb: don’t run an evaluative experiment until you can write the hypothesis it’s testing. If you can’t write the hypothesis, do generative research first.
When in doubt, start with the foundations.
