🧠 Deep dive — to find product market fit faster, focus on this metric
What you measure is what you improve, and "time-to-customer" is the single most impactful way to improve your team's performance.
Hey friend 👋
Many founders obsess over perfection, but rapid customer feedback is the real catalyst for product-market fit.
That’s not a very interesting take. Very unoriginal.
But what does “rapid” mean, and how do you know if you’re on the right track?
Simple: measure your “time-to-customer” (TTC) — the time it takes to get your idea in front of customers. Fast validation means quicker feedback, leading to more value, reduced costs, and, most importantly, faster product-market fit.
In fact, measuring your team’s TTC is the fastest route to achieving product-market fit.
Strap in. It’s time to dive deep. 👇
What’s the first rule of startup club?
Always favour the shortest possible time-to-customer.
TTC is the amount of time it takes to go from idea to test.
You can use it to measure the entire product lifecycle (idea → MVP). But it’s much broader than that. You can measure your TTC for:
New product features (suggestion → prototype)
Market opportunities (idea → value prop test)
Pricing/packaging strategies (cluster analysis → landing page test)
Customer satisfaction (problem → survey results)
And just about anything else you’ll do.
In each case, the time-to-customer is just the amount of time that passes between when you think of something in your head, and when you first expose that idea to real customers for feedback.
In other words:
It’s the time it takes before you learn something.
Your TTC can be long, or short.
The classic example of a long TTC is the time it takes to build a minimum viable product (MVP) or any nontrivial or functional prototype, like a wizard-of-oz. It involves a number of steps, a bit of planning, diverse resources, and cash.
Even a minimal product can take months to build and launch.
Less obvious examples of long TTCs include the time it takes set up landing pages, run complex marketing campaigns, or leverage SEO.
Examples of short TTCs, on the other hand, include:
Customer interviews
Writing online
etc
They take minutes or hours — end-to-end! — and you can learn actionable data from them on day one.
You might be objecting here. Some things take longer than others, right? Yeah, and I’ll return to that in a bit.
But some of you are probably wondering: don’t you learn less from smaller prototypes?
No, and for a weird reason.
But let’s take a step back:
Why is a shorter TTC always better?
For one, because time equals risk.
The longer the time it takes to find out if you’re right, the riskier the proposition. You’re probably wagering more money and more effort. Certainly, you’re wagering more of your life — and, not to be too grim, but time is the one resource you can never earn back.
If you’re a visual person:
The more time you spend, the more effort you expend, the more you’re front-loading risk, and the more you have to lose if the bet doesn’t pay off. That’s just math.
But that’s not the biggest problem.
Here’s something more insidious and counter-intuitive: the longer the time-to-customer, the less we actually learn.
Why?
First, you’re asking fewer questions and running fewer cycles. One big experiment in ten days yields one data point. Ten small experiments in ten days yield ten data points.
Duh.
But you might think that the one big data point is worth more than the ten smaller data points.
But it doesn’t. In fact:
We learn less with long TTCs because bigger bets ask less specific questions.
Let’s take the typical startup example: a landing page test.
You build a nice landing page, with a clear value proposition and strong calls-to-action to sign up for the product. Cool. You then create social media ads to drive a bunch of traffic to the site, identifying a specific target audience and addressing a specific pain point.
But no one converts.
Why didn’t it work? What did we learn?
Very little. Because we don’t know what was wrong. Did we have the wrong:
Delivery mechanism?
Landing page order?
Value proposition?
Call-to-action?
Customer?
Problem?
We just don’t know! One big data point can’t answer granular questions.
The problem is that our big, general question came with a huge burden of assumptions:
who the customer is;
where we can find them;
what problem they have;
how they would describe it;
that they want a solution to it;
that they want this solution to it;
that this is the right offer to propose;
that this copy will convince them;
and more!
That’s enough to make William of Ockham roll in his grave.
It’s too much, and all we learned was that the whole package didn’t work.
Instead, what if we ditched the assumption burden and ran a series of much smaller experiments:
Can we find the audience?
Do they respond to the problem?
Do they want this solution to the problem?
Do they want it delivered to them in this way?
Can we get them to sign on the line that is dotted?
Et cetera.
Each of these experiments gives us specific information — actionable information, no less! — and the learning from those experiments compounds over time: only 1% better each day is a whopping 37x better after one year.
In other words, in the same time period it took to run one big experiment, we can run a series of smaller experiments, through which series we learn more — not less.
The more time it takes to run an experiment, the less valuable it is AND the greater the risk in running it.
Let’s return to that graph:
To maximise learnings, always heed the razor: favour the shortest available time-to-customer.
But that doesn’t mean TTC is always fast.
Some things just take longer, and that’s ok.
It’s not that time-to-customer should always be hours or days, and anything longer means something has gone wrong.
The idea is that shorter is better relatively.
You want the shortest possible TTC relative to the other options that give you the same learning. If what we really need to learn is X, and we can only do it by building this big, time-consuming thing, then that big thing is the shortest possible time-to-customer.
Any shorter and we don’t learn what we need to learn.
That leads us to the TTC skill, which is learning to ask yourself the question:
Why is this the most important thing to learn right now?
Yet this is the most common blunder of the first-time founder.
We focus on what we think we need to learn, knowing it takes a long time to see it through.
But why tho? Why do we do it? Why are we naturally predisposed to favour longer TTCs?
It’s actually fairly basic human psychology:
Long TTCs push into the future the soonest point we can experience failure and rejection.
Broadly speaking… people don’t like rejection that so much. 😅
Conversely, the less time it takes to put something in front of a customer, the more immediate and more real the possibility they can tell us our idea sucks.
And if there’s one thing founders resist most, it’s that their idea sucks.
Anyway, entrepreneurship isn’t complicated.
It’s hard, but it’s not complicated. We make it complicated so that we can avoid the rejection and the failure that comes from being publicly wrong — sometimes, very publicly very wrong.
It’s not conscious. It’s buried deep.
And our brains devise clever schemes to give us things to do that seem like they’re productive, and those things push the time-to-customer out into the future — just coincidentally, of course.
I call it “procrastivity”:
We spend time on things that feel productive, but are just helping us procrastinate on the issue that is important and immediate: is there a “there” there?
Resist procrastivity with your last ounce of strength.
If you find yourself thinking “I shouldn’t do that yet”, it’s the strongest probably signal that you should do it now.
In other words, for any idea you want to pursue — in any domain, at any time — discover the shortest possible path to find out if you’re right, and take it.
Immediately.
Best case? You find out that you’re on the right track.
Worst case? You get time back to pursue something of value.
And time is the one resource you can never earn back.
TL;DR: Lower TTC = less risk + lower cost + more learning
What you measure is what you improve, so measure your team’s time-to-customer, and optimise for it.
Put the metric on your dashboard, and for any effort ask two questions:
Is this the most important thing to learn next?
And is this the fastest way to learn it?
Don’t overcomplicate entrepreneurship.
Startups that prioritise measuring their 'time-to-customer' find product-market fit faster.
It’s that simple.
—jdm
PS: If you enjoyed this deep dive, I’d appreciate you sharing it with a friend. This newsletter grows exclusively by word of mouth, and I’ve been humbled this year by your readership.