Nima LabsCheck the fit

For marketing leaders

An AI-first marketing team starts the week with a vision, not a to-do list.

A marketing team is AI-first when the work starts in one AI system and runs there until a person only has to judge it. The team brings the goal and the ideas. The system builds the campaign from what it knows about the company, and asks when something is missing. A person decides what changes and what goes out.

Build your AI-first organization

We check the fit first. You get a yes or a reasoned no.

Your team got faster. Did anything perform better?

The Content Marketing Institute asked 1,015 B2B marketers. 87 percent say AI made them more productive. 39 percent say it made their content perform better.

87%

say AI made them more productive

39%

say it made their content perform better

Content Marketing Institute, B2B Content Marketing Benchmarks, 1,015 B2B marketers, fielded 2025

The work got faster. The way it runs stayed the same, because every task still waits for somebody to start it, carry it, and finish it.

  1. 01

    Less goes out than the team planned.

    Every campaign gets built piece by piece: the page, the emails, the posts, the ads, one after the other, by whoever has time that week. When somebody is out, the campaign waits.

  2. 02

    Everyone uses AI, and nobody can show what it changed.

    The licenses get paid every month. The board asks what came of them, and the honest answer is a feeling, because nobody measured before.

  3. 03

    Everyone writes their own prompts for the same job.

    Each person comes at the same task with different input and different context, so nothing comes back the same way twice.

The number on top, and the number that mattered

The number on topThe number that mattered
Organic search on the main site, 28 daysAbout 6,000 clicks from searches for the brand name165 from searches without it
A whitepaper campaign55 downloads, counted as a success14 new contacts, 1 lead sales accepted, 0 pipeline
A trial email flowOpen and click rates, the only numbers anybody had on each mailHow many trials each mail turned into a paying customer was never measured

From six months inside a B2B GTM organization with 36,000 accounts in its CRM.

Automation that’s set up, and quietly isn’t working

Automation that’s set up looks the same whether it does its job or not, because nothing looks broken.

The follow-up sequence of that same whitepaper campaign
Finished and set up. It sent nothing for seven weeks. No error, no alert.
A scheduled daily routine
Skipped on every working day for a week. The task showed an error, and nothing reported it.
A nurturing flow for trial deals
91 of 303 deals, 30 percent, could never enter it, because one field was empty.

From six months inside a B2B GTM organization with 36,000 accounts in its CRM.

Each of these looked fine from the outside. What finds them is a check against what actually happened: when the sequence last sent, when the routine last ran, how many deals got into the flow. A system can run that check every week without anybody asking.

What has been built so far

Three builds inside a B2B GTM organization, each its own case. The first is in use. The other two are built, and the line under each says where it stands.

01

One campaign goal in, the whole campaign back

Someone on the team enters a campaign goal, with the context and a briefing behind it: the vision and the campaign.

When the brief leaves something out, the system asks, and keeps asking until it has what it needs. Then it builds the campaign:

  • the social graphics
  • the LinkedIn and Meta ads, with their images
  • for an event, the landing page, the blog post and the posts

They read it and say one of three things: it fits, it doesn’t, or here is what to change.

What the case log says

Built, and in daily use there, by Mario’s account. What it changed was never measured.

Built with

One AI system, and a campaign brief with its context: the vision, the goal, the campaign.

From six months inside a B2B GTM organization with 36,000 accounts in its CRM.

Built separately in the same organization

  • Ads that fit their channel.

    Skills that write the ads for Google, Meta and LinkedIn, with a script that counts each ad’s length against the channel’s limit, because that’s the one requirement in ad copy you shouldn’t estimate. They produce the ads and the settings as a spec. Nothing goes live from them.

None of these three was measured, which is why the first thing we do with you is measure before we build, so there’s an after to compare.

What changes for the people on the team

Where this is heading, in the words of Mario Schäfer, who founded Nima Labs:

In three years, the way I see it, the vision becomes the input. A marketer will no longer walk in thinking “today I have to do X”. The team meets, agrees on a vision for the next two weeks, and the marketer puts that vision into the system. The system turns it into a first draft that is close to ready, from everything it is connected to: web analytics, HubSpot, social media data and the rest.

What decides the result is what the person brings: the creativity, the knowledge, and the vision as it first exists in somebody’s head. The more detailed and the more creative that input is, the better the result.

“The vision and the creativity stay with the people. The execution sits with the system.”
Mario Schäfer, founder of Nima Labs

Two ways it runs

  1. 1

    When you ask.

    A campaign, a new topic, a competitor move. You say what you need, the system does the work, and you get on with something else.

  2. 2

    On a schedule.

    The weekly report, the monthly review. They start on their own at a set time and arrive finished.

A thought experiment

Two companies, the same four weeks

Picture two companies side by side. In the first, a two-hour meeting on Monday sets the vision for the coming weeks, using what the data from its tools says, and the work goes straight into execution with the creativity of the people behind it.

In the second, the team sits down and starts working out which assets it needs, which processes, and what else has to be done. Then somebody is out sick, and somebody else isn’t there, and the work stops.

At the end of the four weeks the first company has results, maybe not the right ones and maybe not good enough yet, but it has them. The second is still stuck in execution. So which one gets more customers? Which one can grow, and which one shrinks?

What the system needs to know about your company

An AI system works from what is written down and from the data it’s connected to. From a marketing view, the written part is above all:

  • your positioning, your offering and your messaging
  • how the company presents itself: the brand design, the colors
  • who you sell to: the ICP and the personas
  • what you know about your existing customers

What gets automated comes out of the work your team already does every week, never from a wish list. Where none of it is written down yet, it gets written first, in the Discovery.

How it starts, and what you own at the end

1 to 2 weeks

Discovery

Which marketing processes are worth rebuilding first, and what each one takes today. We measure before we touch anything, so you can see later what changed.

within the first month

First build

The first process goes live. It starts on its own, runs through, and a named person on your team releases the result.

about 3 months

Full build

The rest, in order of how often each one runs and how much work it takes today. One or two of your people trained to run it and build the next one.

What you own at the end is a repository: your positioning, your tone of voice, your playbooks and the processes themselves. Your next marketing manager gets access and works the way your team works from the first day.

Who this is for

Seven things have to be true before it works. We check them before we start, and we say no in writing when they aren’t.

  • Your campaigns repeat every week.

    Weekly posts, the newsletter, the follow-up after every event. What never runs the same way twice can’t be handed to a system.

  • Your data lives in systems.

    A CRM that’s maintained, a website with a content system behind it, and it’s settled which customer data a system may read.

  • AI is already in use.

    Tools are rolled out, and part of the team works with them every day.

  • Something already runs without you.

    One automated process, however simple. The step from everything by hand straight to this one is too big.

  • Leadership wants it and says why.

    More coverage, more speed, better quality. If the main goal is fewer people, we say no, because the team hears it either way.

  • One AI system works for you.

    Claude, OpenAI, or Gemini, whichever you already use. One system for everything.

  • Someone on your team builds with us.

    One or two people who take over when we leave.

What marketing leaders ask

“We already use AI. What would change?”

Almost everyone does: in the Content Marketing Institute’s sample of 1,015 B2B marketers, 95 percent say their organizations use AI-powered applications. What changes is that one campaign process in your team starts in the system and runs through to a result somebody only has to judge.

“Will it sound like us?”

Only if your voice is written down in a way a system can check. Adjectives like “direct and honest” can’t be checked. Reflexes can: the things your best writer always catches, written as checks the system runs on every draft. That gets written in the Discovery.

“What if the AI makes things up?”

It does, when nothing stops it. In one test Mario ran inside a B2B GTM organization, a borrowed email prompt with no guard rail invented a result that nothing in the input supported. So every process carries the rule that a number comes from the input or from an approved list, and a person reads every result before it goes out.

“How do we show the board what it changed?”

With numbers per process, measured before the build and again after: how often it ran, how long it took from goal to released result, what came out, and what it changed. Usage statistics don’t count, and neither do estimated time savings.

“Will we lose people over this?”

Your leadership decides that, we don’t. If fewer people is the main goal, we’ll tell you in writing that this isn’t the way. What changes is what people spend the day on: the vision, the judgment and the creative work, with the execution in the system.

Does this fit you?

We check the fit first: leadership behind it, the AI decision made, and a shared view of what the first build can and can’t do. No sales call, no deck. You get a written yes, or a written no with reasons.

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