7 (not-so-easy) steps to find your startup’s first customer

Hey there — JDM here. 👋

I’m hard at work prepping for an awesome conference in Calgary in a couple of weeks, but I took a few minutes to write you this email. If I had more time, I would have written a shorter email.

I hope you enjoy it.

Estimated read time: 12 minutes & 20 seconds

Successful startups begin with 1 paying customer — not 100.

That mindset shift changes everything, because getting one customer isn’t complicated.

And if you can get 1, you can get 10.

And if you can get 10, you get 100.

And so on, all the way to product-market fit.

But it starts with one.

So why do first-time founders struggle to find a customer?

Because they lack a repeatable process.

So many of the books, resources, and programs for founders teach you frameworks, tools, models, and theory.

But they don’t teach what to do first. And then what to next.

So let me share mine. I’ve used this with dozens of early-stage startups, but it’s not even very original. I just bothered to write it down.

The goal is to develop the best product-market fit hypothesis for the moment, design an experiment to test, and iterate until they buy.

Cheaply
Quickly
Without building anything.

The goal isn’t to get the hypothesis right. We can’t — it’s definitely wrong.

There are no facts inside the building — only guesses.

My favourite description of the scientific process comes from the physicist-philosopher Bernard D’Espagnat, who said:

Nature refuses to tell us precisely what she is. But, if we press her tenaciously enough, she will condescend to tell us a little bit about what she is not.

And that’s our goal: to get the market to tell us what our product isn’t — as quickly as possible.

Pivots are how we home in on reality.

But enough theory! Here’s how to do it. It’s 7 steps:

1/ Identify the customer

Design thinking 101: understand the customer as deeply as you can.

I bet you already have an hypothesis of whom you want to serve, so add some detail to it:

Demographics
Psychographics
Wants
Needs
Fears
Jobs to be done
Friends, colleagues, & influencers
etc

A common mistake is to do this through the lens of your product, but this isn’t about your product — it’s about the people.

Make some educated guesses. You’re going to be wrong, and that’s ok.

Remember — you’re picking a starting hypothesis that you can prove wrong.

2/ Design a (hopefully compelling) value proposition

This is your offering.

What pain does your customer have, and how are you solving it?

In last week’s newsletter, I talked about my favourite tool for creating compelling value propositions: experience mapping.

It’s asking: what does your customer’s life look like without your product?

They are experiencing pain, and they are doing something to try to solve the problem — right now, without you.

An experience map just a flowchart that documents that:

Start at the left with their need.
Document the process as you move rightward.
End with how they are solving the problem
without you.

Then:

List out the pain points for each step.
Find opportunities within that pain.

This simple diagram contains almost everything you need to design a compelling value proposition that you can test.

Now, you don’t just have a customer — you also have their pain and what you can do to salve it.

That’s something you can work with!

I created a free experience map template you can use as a starting point.

3/ Create a product statement / offering / PMF hypothesis

Your product has a lot going on, and the you need a clear, cogent, and concise statement of what you’re working on.

Preferably, you can share this directly with customers, co-founders, employees, investors, etc.

Take your value proposition, and create a quick summary like this:

[startup/product] is a [type/category] for [customer] who [need/opportunity]. It [has key feature] which [delivers key benefit]. Unlike [primary competitor/alternative], we [primary differentiator].

Here’s an example:

[Todorly] is an [app] for [social media influencers who focus on video] who [struggle with managing the large volume of content they create]. It [has a cross-platform social media dashboard] which [allows them to quickly see what kinds of content are resonating]. Unlike [Buffer], we [are a platform for creators, by creators].

I made all of that up just now. But you get the idea.

What’s yours? Send it to me, and I’ll give it a quick review.

4/ Where are the customers?

I often describe the startup process as:

Find customers
Understand their problem
Solve it

It seems straightforward, but too many startup founders just skip that first step!

Because it’s not findiong one customer and talking to them. It’s finding all the customers and talking to some of them.

Because your startup will hit the ground with a big thud if you build a product before you know how to get it in front of customers. And the only way to know if you can do that is to try to get in front of customers — from the start.

Here’s how to do it:

List out all the channels where you think your customers are (channels).
Rank them by how many customers are there, from most to least.
Rank them by how easy it is to reach customers on that channel, from easiest to hardest.
Pick the channel that has the most customers that are the easiest to reach.

E.g. if they’re all on Twitter, but you have few following you, and not a lot of ad dollars to spend, it’s extraordinarily difficult to reach them — even though you know they’re there!

Which channel has the most customers for the least effort for you?

Our goal is to go there, prove we’re right, and to find one customer, which brings us to:

5/ Design the experiment

Experiment, test, next step, bet, MVP, whatever — I don’t care what you call it.

Your goal is to put in as little time & money as possible to find out if you’re on the right track.

It’s pretty simple, but most founders get this part wrong.

An experiment is a controlled test of one hypothesis, for which we know both what to measure and what a successful (and unsuccessful) measurement looks like.

It looks like this:

I believe that [hypothesis].
To verify that, I will [do something].
And measure [this particular number].
I am right if [the measure is X].

Here’s an example:

I believe that my product statement will resonate with customers on LinkedIn.
To verify that, I will send InMail messages to 20 potential customers to ask for a phone call.
And measure the number of affirmative responses (conversions).
I am right if 10% get on a call.

Why 10%? More on picking the right number in step 7.

This experiment will test if my offering resonates with customers.

But I could build on this experiment by testing the call itself to see if I can get them to put their cash where their mouth is.

So, what’s your experiment? Take a moment to write it down.

Now that you’ve defined your experiment, it’s time to get out of your head and run it:

6/ Put the offer in front of customers

How will people respond? You don’t know, so let’s ask them!

Everything you did before this step was a waste of time if you don’t put it in front of customers.

The easiest thing to put in front of your customers is your product statement.

The idea? When you run the experiment:

Many will ignore you.
Some will say no.
Some will hop on a call.
And a few will become your early adopters.

Or you’re on the wrong track.

Your ability to get a response about the problem tells you whether you have the right customer, the right problem, and the right solution.

To hell with scale. We’re after one customer. No automation is allowed in this step.

Never build a damn thing until you can consistently find the “yes”.

You’re just wasting your time.

Just. Talk. To. Customers.

7/ Iterate

Getting in front of customers is unequivocally the most important step, but iteration comes second.

Because the experiment is worthless if you don’t learn from it.

When you get data back, you have to ask: what does this mean? And then you need to incorporate it into your mental model, form a new hypothesis, and go again.

So this brings us back to the measurement: how did I pick 10%?

I made it up.

You won’t know what the number should be. Heck, I don’t even know what it “should be” means here.

But the number itself is signaling the relative difficulty of making the product work. The lower that number is, the harder it will be to get customers.

It doesn’t mean you’re dead in the water.

But when your expectation doesn’t match reality, you have to ask yourself what it means:

Do I have the right customer?
The right problem?
The right solution?
Is it just not viable?
Do I just need to persevere?

Your thinking about those questions is far more important than coming up with the “right” number to start with.

And that’s it. That’s the whole process.

As you iterate, you’ll hone in on the right combination and you’ll land your first customer — and you’ll be on the strongest path to be able to scale it.

Or you’ll learn there’s no “there” there, and you’ll move on to your next startup — fast.

Which is an underappreciated win, frankly.

When you're ready, there are 3 ways I can help you.

Ask me a question during my weekly office hours (Thursdays at 11am pst).
Work 1:1 with me to tackle the most challenging parts of the startup journey (100+ first-time founders).
Run a design sprint with your startup team to find traction fast (dozens of startups).

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