Build the evidence, then test it before you fund anything against it.

Where you are now

Four failure modes, and almost every company we meet has at least two of them running at once.

What it costs to leave it

Trial and error is the most expensive way to learn something you could have known in six weeks. The bill does not arrive as a line item. It arrives as a quarter of headcount pointed at a segment that was never going to buy, a sending domain you cannot use any more, and a team that has stopped believing the targeting.

The reason it keeps happening is structural. Most go-to-market plans are reasoned internally and tested nowhere. First contact with reality happens after the budget and the headcount are already committed, which is the one point at which nobody wants to hear that the premise was wrong.

A strategy that has never met the market is a hypothesis with a price tag.

What we do about it

A lab is where you test something before you scale it. Phase One is four of them, run in sequence. Each produces an output you own outright, and the fourth decides whether the first three were right.

Most strategy work stops at three. The fourth lab is the difference the whole model rests on.

You typically finish Phase One with first conversations already in motion rather than a document and an assumption. Then the lab closes. Phase two is production, not experimentation. The risk gets taken on our time, inside Phase One, before it gets taken on your budget.

Why not just use software to build the ICP?

It is a fair question and a real product. Connect your CRM, the system reads your closed-won deals, finds what the winners have in common, and writes you a profile by the afternoon. The math is not fake. The problem is the training set: it is your own history.

An ICP derived from your CRM can only recommend more of what you already chose. If those choices were right, you did not need the exercise. If they were wrong, the software reproduces the error confidently, at scale, and calls it a finding. Phase One asks the questions that leave no trace in a database, checks every answer against the deals you actually won, and then tests the result in the market before anyone builds an outbound motion on top of it.

Where this argument stops, since we would rather say it than have you find it. If you have thousands of clean closed-won records and a RevOps function maintaining them, fitting a model to that history is reasonable and you should do it. Most companies we work with have fewer than a hundred, entered by sellers in a hurry, in a system nobody has audited since the last migration. At that size the model is not reading your market, it is reading your sales manager from three years ago. Longer version in the field notes.

The motion, worked through

What the first 180 days look like when Phase One runs into execution. Phase One itself is the first block, and it stands alone.

How Outpace works

Assessment first, execution second. You are not signing a long engagement on day one. You are buying a short, defined piece of work that either proves itself or does not.

If we are not the right partner for execution, you still walk away with a plan worth having. That is not generosity, it is the only structure under which a recommendation can be honest: saying no costs us the next engagement rather than the whole relationship.

What moves the price, and what it does not cover →

Three ways to start

Pricing and timelines are engagement terms, not client results. Outpace Labs is early, and we would rather publish what we can be held to now than numbers we cannot attribute.